# Primordial and primary prevention of peri-implant diseases: A systematic review and meta-analysis

Maria Clotilde Carra, Nicolas Blanc-sylvestre, Alexandre Courtet, Philippe Bouchard

► To cite this version:

Maria Clotilde Carra, Nicolas Blanc-sylvestre, Alexandre Courtet, Philippe Bouchard. Primordial and primary prevention of peri-implant diseases: A systematic review and meta-analysis. Journal of Clinical Periodontology, 2023, 50 (S26), pp.77-112. 10.1111/jcpe.13790. hal-04467254

HAL Id: hal-04467254

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Submitted on 20 Feb 2024

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Distributed under a Creative Commons Attribution 4.0 International License
# Primordial and primary prevention of peri-implant diseases: A systematic review and meta-analysis

Maria Clotilde Carra, Nicolas Blanc-sylvestre, Alexandre Courtet, Philippe Bouchard

► To cite this version:

Maria Clotilde Carra, Nicolas Blanc-sylvestre, Alexandre Courtet, Philippe Bouchard. Primordial and primary prevention of peri-implant diseases: A systematic review and meta-analysis. Journal of Clinical Periodontology, 2023, 50 (S26), pp.77-112. 10.1111/jcpe.13790. hal-04467254

HAL Id: hal-04467254

https://uvsq.hal.science/hal-04467254v1

Submitted on 20 Feb 2024

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
# Primordial and primary prevention of peri-implant diseases: A systematic review and meta-analysis

Maria Clotilde Carra<sup>1,2,3 ID</sup> | Nicolas Blanc-Sylvestre<sup>1,2,4 ID</sup> | Alexandre Courtet<sup>1,2 ID</sup> |
Philippe Bouchard<sup>1,4 ID</sup>

## Correspondence

Maria Clotilde Carra and Philippe Bouchard, Department of Periodontology, Université Paris Cité. Service of Odontology of the Rothschild University Hospital, AP-HP, 5, rue Santerre, 75012 Paris, France.

Email: mclotildecarra@gmail.com and philippe.bouchard.perio@gmail.com

## Abstract

**Aim:** This systematic review and meta-analysis aims to assess the efficacy of risk factor control to prevent the occurrence of peri-implant diseases (PIDs) in adult patients awaiting dental implant rehabilitation (primordial prevention) or in patients with dental implants surrounded by healthy peri-implant tissues (primary prevention).

**Materials and Methods:** A literature search was performed without any time limit on different databases up to August 2022. Interventional and observational studies with at least 6 months of follow-up were considered. The occurrence of peri-implant mucositis and/or peri-implantitis was the primary outcome. Pooled data analyses were performed using random effect models according to the type of risk factor and outcome.

**Results:** Overall, 48 studies were selected. None assessed the efficacy of primordial preventive interventions for PIDs. Indirect evidence on the primary prevention of PID indicated that diabetic patients with dental implants and good glycaemic control have a significantly lower risk of peri-implantitis (odds ratio [OR] = 0.16; 95% confidence interval [CI]: 0.03–0.96; I<fnref n="2" />: 0%), and lower marginal bone level (MBL) changes (OR = -0.36 mm; 95% CI: -0.65 to -0.07; I<fnref n="2" />: 95%) compared to diabetic patients with poor glycaemic control. Patients attending supportive periodontal/peri-implant care (SPC) regularly have a lower risk of overall PIDs (OR = 0.42; 95% CI: 0.24–0.75; I<fnref n="2" />: 57%) and peri-implantitis compared to irregular attendees. The risk of dental implant failure (OR = 3.76; 95% CI: 1.50–9.45; I<fnref n="2" />: 0%) appears to be greater under irregular or no SPC than regular SPC. Implants sites with augmented peri-implant keratinized mucosa (PIKM) show lower peri-implant inflammation (SMD = -1.18; 95% CI: -1.85 to -0.51; I<fnref n="2" />: 69%) and lower MBL changes (MD = -0.25; 95% CI: -0.45 to -0.05; I<fnref n="2" />: 62%) compared to dental implants with PIKM deficiency. Studies on smoking cessation and oral hygiene behaviors were inconclusive.

**Conclusions:** Within the limitations of available evidence, the present findings indicate that in patients with diabetes, glycaemic control should be promoted to avoid peri-implantitis development. The primary prevention of peri-implantitis should involve regular SPC. PIKM augmentation procedures, where a PIKM deficiency exists,

This is an open access article under the terms of the [Creative Commons Attribution-NonCommercial-NoDerivs License](https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

© 2023 The Authors. *Journal of Clinical Periodontology* published by John Wiley & Sons Ltd.

<figure><img src="image_2.png" /></figure>

<footnote n="1"><sup>1</sup>U.F.R. d'Odontologie, Université Paris Cité, Paris, France</footnote>

<footnote n="2"><sup>2</sup>Service of Odontology, Periodontal and Oral Surgery Unit, Rothschild Hospital (AP-HP), Paris, France</footnote>

<footnote n="3"><sup>3</sup>Population-Based Epidemiologic Cohorts Unit, Inserm, UMS 11, Villejuif, France</footnote>

<footnote n="4"><sup>4</sup>URP 2496, Université Paris Cité, Paris, France</footnote>
# Primordial and primary prevention of peri-implant diseases: A systematic review and meta-analysis

Maria Clotilde Carra<sup>1,2,3 ID</sup> | Nicolas Blanc-Sylvestre<sup>1,2,4 ID</sup> | Alexandre Courtet<sup>1,2 ID</sup> |
Philippe Bouchard<sup>1,4 ID</sup>

## Abstract

**Aim:** This systematic review and meta-analysis aims to assess the efficacy of risk factor control to prevent the occurrence of peri-implant diseases (PIDs) in adult patients awaiting dental implant rehabilitation (primordial prevention) or in patients with dental implants surrounded by healthy peri-implant tissues (primary prevention).

**Materials and Methods:** A literature search was performed without any time limit on different databases up to August 2022. Interventional and observational studies with at least 6 months of follow-up were considered. The occurrence of peri-implant mucositis and/or peri-implantitis was the primary outcome. Pooled data analyses were performed using random effect models according to the type of risk factor and outcome.

**Results:** Overall, 48 studies were selected. None assessed the efficacy of primordial preventive interventions for PIDs. Indirect evidence on the primary prevention of PID indicated that diabetic patients with dental implants and good glycaemic control have a significantly lower risk of peri-implantitis (odds ratio [OR] = 0.16; 95% confidence interval [CI]: 0.03–0.96; *I*<fnref n="2" />: 0%), and lower marginal bone level (MBL) changes (OR = -0.36 mm; 95% CI: -0.65 to -0.07; *I*<fnref n="2" />: 95%) compared to diabetic patients with poor glycaemic control. Patients attending supportive periodontal/peri-implant care (SPC) regularly have a lower risk of overall PIDs (OR = 0.42; 95% CI: 0.24–0.75; *I*<fnref n="2" />: 57%) and peri-implantitis compared to irregular attendees. The risk of dental implant failure (OR = 3.76; 95% CI: 1.50–9.45; *I*<fnref n="2" />: 0%) appears to be greater under irregular or no SPC than regular SPC. Implants sites with augmented peri-implant keratinized mucosa (PIKM) show lower peri-implant inflammation (SMD = -1.18; 95% CI: -1.85 to -0.51; *I*<fnref n="2" />: 69%) and lower MBL changes (MD = -0.25; 95% CI: -0.45 to -0.05; *I*<fnref n="2" />: 62%) compared to dental implants with PIKM deficiency. Studies on smoking cessation and oral hygiene behaviors were inconclusive.

**Conclusions:** Within the limitations of available evidence, the present findings indicate that in patients with diabetes, glycaemic control should be promoted to avoid peri-implantitis development. The primary prevention of peri-implantitis should involve regular SPC. PIKM augmentation procedures, where a PIKM deficiency exists,

## Correspondence

Maria Clotilde Carra and Philippe Bouchard, Department of Periodontology, Université Paris Cité. Service of Odontology of the Rothschild University Hospital, AP-HP, 5, rue Santerre, 75012 Paris, France.

Email: mclotildecarra@gmail.com and philippe.bouchard.perio@gmail.com

This is an open access article under the terms of the [Creative Commons Attribution-NonCommercial-NoDerivs](https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

© 2023 The Authors. *Journal of Clinical Periodontology* published by John Wiley & Sons Ltd.

<footnote n="1">¹U.F.R. d'Odontologie, Université Paris Cité, Paris, France</footnote>

<footnote n="2">²Service of Odontology, Periodontal and Oral Surgery Unit, Rothschild Hospital (AP-HP), Paris, France</footnote>

<footnote n="3">³Population-Based Epidemiologic Cohorts Unit, Inserm, UMS 11, Villejuif, France</footnote>

<footnote n="4">⁴URP 2496, Université Paris Cité, Paris, France</footnote>
may favour the control of peri-implant inflammation and the stability of MBL. Further studies are needed to assess the impact of smoking cessation and oral hygiene behaviours, as well as the implementation of standardized primordial and primary prevention protocols for PIDs.

KEYWORDS

dental implants, implant-supported rehabilitation, mucositis, peri-implant diseases, peri-implantitis, prevention, risk factors, risk indicators, survival

Clinical Relevance

*Scientific rationale for study:* Risk assessment and risk factor control are necessary to prevent the development of peri-implant diseases in patients who are candidates for dental implant(s) (primordial prevention) and in those who have received dental implant(s) and currently have healthy peri-implant tissues (primary prevention).

*Principal findings:* Risk factor control is necessary to preserve peri-implant health and to avoid PIDs. In patients with diabetes, special attention should be paid to improving glycaemic control. The primary prevention of peri-implantitis should be based upon regular supportive periodontal/peri-implant care. Increasing PIKM where a deficiency exists may be considered to preserve peri-implant health.

*Practical implications:* Risk factor control should target all modifiable patient-, implant-, and clinician-related risk factors identified for a specific patient, by implementing multiple preventive interventions simultaneously to maintain peri-implant health over time.

1 | INTRODUCTION

Implant-supported restorations are widely employed for the rehabilitation of partial or complete edentulism. Despite favourable dental implant outcomes and long-term survival rates, the occurrence of peri-implant diseases (PIDs) is common and represents a significant disease burden that needs to be addressed with effective preventive interventions (Gurgel et al., 2017; Jepsen et al., 2015).

PIDs include peri-implant mucositis (hereafter referred to as “mucositis” in this review) and peri-implantitis. They are initiated by dysbiotic microbial biofilms on the hard, non-shedding surfaces of the implant-supported restoration, which causes local inflammation at the level of the peri-implant mucosa (i.e., mucositis) and progressively the peri-implant bone (i.e., peri-implantitis) (Renvert et al., 2018; Salvi et al., 2012). However, the aetiology and pathophysiology of PIDs remain under investigation, with several risk factors/indicators advocated as potential contributors to peri-implant tissue breakdown<fnref n="1" /> (Fu & Wang, 2020; Schliephake, 2022). These include smoking (Javed et al., 2019; Rinke et al., 2020), diabetes (Chambrone & Palma, 2019; Genco & Borgnakke, 2020; Jiang et al., 2021), periodontitis (Schwarz et al., 2018), limited/lack of provision of supportive peri-implant care (Jepsen et al., 2015), inadequate personal biofilm control (Renvert & Quirynen, 2015), reduced peri-implant keratinized mucosa (PIKM) (Rinke et al., 2020; Sanz et al., 2022; Thoma et al., 2018, 2021), and some characteristics of the implant-supported restoration design

(Koutouzis, 2019; Schwarz et al., 2021; Staubli et al., 2017). Furthermore, genetics, stress, diet, and other lifestyle habits may be considered as potential risk factors for PIDs (Loos et al., 2015; Loos & Van Dyke, 2020). The level of risk, as well as the quality of the associated literature, differs significantly depending on the specific factor considered. Current evidence does not allow the identification of “true” risk factors, that is, specific to PIDs, because of the paucity of long-term prospective longitudinal studies evaluating a potential causal relationship between the exposure (the risk factor) and the outcome (peri-implant health/disease). Moreover, in view of the potential continuum of progression from mucositis to peri-implantitis, similar to gingivitis and periodontitis, peri-implant mucositis is considered a predictor of peri-implantitis (Jepsen et al., 2015).

The European Federation of Periodontology (EFP) has been addressing the importance of PID prevention for several years (Jepsen et al., 2015; Tonetti et al., 2015) by listing a series of recommendations for dental professionals, which include the management of the major risk factors for PIDs (Berglundh et al., 2018). Indeed, risk assessment is part of professional preventive care. An effective preventive approach needs to be personalized to the individual patient's risk profile, addressing all potential local and systemic risk factors for PIDs that can be modified. This personalized approach to prevention also requires specific approaches to patient education and motivation for behavioural change, with patients taking responsibility for their own health under the guidance and support of the oral care team (Tonetti et al., 2015). Preventive measures can even be implemented prior to implant placement in order to prevent exposure to risk factor(s) and ultimately reduce the incidence of new disease. In this situation, we

<footnote n="1">¹For the sake of simplicity, the term “risk factors” will be used in this article to generally refer to all indicators that have been significantly associated with PID occurrence despite the difference level of supporting evidence.</footnote>
may favour the control of peri-implant inflammation and the stability of MBL. Further studies are needed to assess the impact of smoking cessation and oral hygiene behaviours, as well as the implementation of standardized primordial and primary prevention protocols for PIDs.

KEYWORDS

dental implants, implant-supported rehabilitation, mucositis, peri-implant diseases, peri-
implantitis, prevention, risk factors, risk indicators, survival

Clinical Relevance

**Scientific rationale for study:** Risk assessment and risk factor control are necessary to prevent the development of peri-implant diseases in patients who are candidates for dental implant(s) (primordial prevention) and in those who have received dental implant(s) and currently have healthy peri-implant tissues (primary prevention).

**Principal findings:** Risk factor control is necessary to preserve peri-implant health and to avoid PIDs. In patients with diabetes, special attention should be paid to improving glycaemic control. The primary prevention of peri-implantitis should be based upon regular supportive periodontal/peri-implant care. Increasing PIKM where a deficiency exists may be considered to preserve peri-implant health.

**Practical implications:** Risk factor control should target all modifiable patient-, implant-, and clinician-related risk factors identified for a specific patient, by implementing multiple preventive interventions simultaneously to maintain peri-implant health over time.

1 | INTRODUCTION

Implant-supported restorations are widely employed for the rehabili-
tation of partial or complete edentulism. Despite favourable dental
implant outcomes and long-term survival rates, the occurrence of
peri-implant diseases (PIDs) is common and represents a significant
disease burden that needs to be addressed with effective preventive
interventions (Gurgel et al., 2017; Jepsen et al., 2015).

PIDs include peri-implant mucositis (hereafter referred to as
"mucositis" in this review) and peri-implantitis. They are initiated by
dysbiotic microbial biofilms on the hard, non-shedding surfaces of the
implant-supported restoration, which causes local inflammation at
the level of the peri-implant mucosa (i.e., mucositis) and progressively
the peri-implant bone (i.e., peri-implantitis) (Renvert et al., 2018; Salvi
et al., 2012). However, the aetiology and pathophysiology of PIDs
remain under investigation, with several risk factors/indicators advo-
cated as potential contributors to peri-implant tissue breakdown<fnref n="1" />
(Fu & Wang, 2020; Schliephake, 2022). These include smoking (Javed
et al., 2019; Rinke et al., 2020), diabetes (Chambrone & Palma, 2019;
Genco & Borgnakke, 2020; Jiang et al., 2021), periodontitis (Schwarz
et al., 2018), limited/lack of provision of supportive peri-implant care
(Jepsen et al., 2015), inadequate personal biofilm control (Renvert &
Quirynen, 2015), reduced peri-implant keratinized mucosa (PIKM)
(Rinke et al., 2020; Sanz et al., 2022; Thoma et al., 2018, 2021), and
some characteristics of the implant-supported restoration design

(Koutouzis, 2019; Schwarz et al., 2021; Staubli et al., 2017). Further-
more, genetics, stress, diet, and other lifestyle habits may be consid-
ered as potential risk factors for PIDs (Loos et al., 2015; Loos & Van
Dyke, 2020). The level of risk, as well as the quality of the associated
literature, differs significantly depending on the specific factor consid-
ered. Current evidence does not allow the identification of “true” risk
factors, that is, specific to PIDs, because of the paucity of long-term
prospective longitudinal studies evaluating a potential causal relation-
ship between the exposure (the risk factor) and the outcome (peri-
implant health/disease). Moreover, in view of the potential continuum
of progression from mucositis to peri-implantitis, similar to gingivitis
and periodontitis, peri-implant mucositis is considered a predictor of
peri-implantitis (Jepsen et al., 2015).

The European Federation of Periodontology (EFP) has been
addressing the importance of PID prevention for several years (Jepsen
et al., 2015; Tonetti et al., 2015) by listing a series of recommenda-
tions for dental professionals, which include the management of the
major risk factors for PIDs (Berglundh et al., 2018). Indeed, risk assess-
ment is part of professional preventive care. An effective preventive
approach needs to be personalized to the individual patient's risk pro-
file, addressing all potential local and systemic risk factors for PIDs
that can be modified. This personalized approach to prevention also
requires specific approaches to patient education and motivation for
behavioural change, with patients taking responsibility for their own
health under the guidance and support of the oral care team (Tonetti
et al., 2015). Preventive measures can even be implemented prior to
implant placement in order to prevent exposure to risk factor(s) and
ultimately reduce the incidence of new disease. In this situation, we

<footnote n="1">¹For the sake of simplicity, the term “risk factors” will be used in this article to generally refer to all indicators that have been significantly associated with PID occurrence despite the difference level of supporting evidence.</footnote>
<figure><img src="image_2.png" /></figure>

**FIGURE 1** Definition of the different types of prevention. Primordial prevention consists in the prevention of risk factor development; it targets the population of individuals who do not have the disease (have not yet received dental implants) to avoid risk factor exposure, for example, promoting healthy behaviours (e.g., no addiction, good oral hygiene, etc.). Primary prevention aims to prevent disease onset by risk factor control in individuals with healthy peri-implant tissues but exposed to known risk factors, for example, applying adequate and personalized oral hygiene for optimal plaque control also around implant-supported restoration(s). Secondary prevention aims at preventing disease recurrence once peri-implant disease (PID) has been diagnosed and treated. Thus, it targets populations of individuals who already have experienced an event of the disease: for example, regular peri-implant supportive care after successful active treatment of PID represents secondary prevention. Finally, tertiary prevention is represented by the prevention of disease complications in individuals who have a chronic disease, for example, promoting interventions to slow down the progression of the PIDs to avoid implant loss.

refer to “primordial prevention” as the earliest prevention modality
targeting the underlying risk factors and conditions that promote dis-
ease onset (Kisling & Das, 2022) (Figure 1). An example includes pro-
moting healthy behaviours including no tobacco smoking or increased
physical activity to prevent non-communicable diseases, such as
type-2 diabetes, or harmful behaviours that may increase the risk
of PIDs.

Once the dental implant is placed and loaded, the health of the peri-
implant tissues must be maintained over time. This is the driver of pri-
mary prevention strategies, which target the population of individuals
with healthy peri-implant tissues and comprises all interventions that
promote risk factor control to prevent the disease from manifesting
(Kisling & Das, 2022), for example, educating and motivating the patient
in a personalized manner to practice adequate oral hygiene behaviours
to effectively control biofilm accumulation around dental implants and
their superstructures/restorations. The management of peri-implant
mucositis is a preventive measure for the onset of peri-implantitis, but in
this situation it represents a form of secondary prevention that is beyond
the scope of the present review (Figure 1).

The present study aimed to systematically review the current lit-
erature to answer the following focused research question: "What is
the efficacy of preventive interventions, involving risk factor control,
in patients (i) awaiting dental implant rehabilitation (primordial preven-
tion), or (ii) having dental implant(s) with healthy peri-implant tissues
(primary prevention) on the incidence of PIDs?"

2 | METHODS

## 2.1 | Protocol development and registration

The protocol of the present systematic review and meta-analysis was
developed following the PRISMA statement checklist (Moher et al., 2009) and registered in PROSPERO on 10 May 2022 (registration number: CRD42022324733).

2.2 | Eligibility criteria

The main research question was constructed using the PICOS format for interventional studies and the PECOS format for observational studies, as follows:

2.2.1 | PICOS

(P) Participants: Adult patients awaiting dental implant placement or having dental implants with peri-implant health.

(I) Intervention: Interventions to control risk factor(s) for PIDs.

(C) Comparison: Adult patients awaiting dental implant placement or having dental implants with peri-implant health and not receiving any preventive intervention.
(O) Outcomes: The primary outcome was the occurrence of PIDs, including mucositis and peri-implantitis. Any case definition of peri-implant mucositis and peri-implantitis was considered. Because a preventive intervention aims to prevent the occurrence of a disease (i.e., PIDs) but also to maintain health (i.e., peri-implant health), clinical parameters essential to define peri-implant health and diagnose PIDs according to the 2017 World Workshop on the Classification of Periodontal and Peri-Implant Diseases and Conditions (Berglundh et al., 2018; Caton et al., 2018) were also considered as primary outcome measures, such as bleeding on probing (BOP) (or other indices for peri-implant tissue inflammation), peri-implant probing depth (PPD), suppuration, and radiographic marginal bone level (MBL). Eligible studies must report at least one of the aforementioned primary outcomes to be selected. Biomarkers in saliva or peri-implant fluid and dental implant survival rate were considered as secondary outcomes (Derks et al., 2022).

(S) Study design: Randomized (RCTs) and non-randomized controlled trails (NRCTs), with a minimum of 6 months follow-up from implant loading.

### 2.2.2 | PECOS

(P) Participants: Adult patients awaiting dental implant placement or having dental implants with peri-implant health.

(E) Exposure: Exposure to a risk factor for PIDs.

(C) Comparison: Adult patients awaiting dental implant placement or having dental implants with peri-implant health no more exposed to the risk factor.

(O) Outcomes: Same as in the PICOS format described above.

(S) Study design: Prospective and retrospective cohort studies and case-control studies (matched or not) with a minimum of 6 months follow-up from implant loading.

Based on the above-mentioned criteria, separate research questions were constructed for each PID risk factor explored.

The efficacy of primordial and primary preventive interventions for PIDs should be ideally assessed in longitudinal and interventional studies. However, because of the difficulties and ethical issues in conducting certain types of RCTs/NRCTs and the expected paucity of literature on PID prevention, prospective and retrospective observational studies were also considered. To assess the efficacy of risk factor control, the target population must be exposed to the risk factor at some point in time. Therefore, studies assessing the association between a risk factor and PID occurrence were not considered. For instance, comparisons between diabetes and non-diabetes patients with dental implants, or smokers versus non-smokers, were not considered. Indeed, the aim of the present study was designed to assess the efficacy of risk factor control on PID prevention, but not to identify the risk factors.

A set of potentially modifiable risk factors were predetermined and searched. We made the pragmatic decision not to include prosthesis-related risk factors because time and resources made them beyond the scope of this review. Therefore, the present systematic

review was limited to the following risk factors and their corresponding preventive interventions:

* Poor glycaemic control (as measured by HbA1c [in percentage]) in diabetic and pre-diabetic patients. No threshold was set for HbA1c because of country-related differences and comorbidity-related impact in defining good and poor glycaemic control. The preventive intervention was improving or obtaining glycaemic control.

* Smoking status (as defined by current smoking) and smoking habit (as measured by the quantity [number of cigarettes] or type of smoking habit [e.g., cigarette, e-cigarette, water pipe]). The preventive intervention was the promotion of smoking cessation by any guideline-based strategy.

* Type of and adherence to supportive periodontal/peri-implant care (SPC) protocols. The preventive intervention was promoting and obtaining adequate/regular patient adherence to the SPC employed. Studies comparing the efficacy of different SPC protocols were also considered.

* Width of the PIKM and thickness of the peri-implant soft tissue. A deficiency of PIKM or a thin peri-implant mucosa was considered as a risk factor. The preventive intervention was a surgical procedure for soft tissue augmentation, including PIKM augmentation. To be included, studies had to report the surgical indication, which should clearly be to augment the peri-implant keratinized tissue width or the peri-implant soft tissue thickness.

* Oral hygiene behaviours (including frequency and methods of brushing). The preventive intervention was promoting and achieving optimal/improved patient's oral hygiene behaviour.

* Bruxism/oral parafunction. The preventive intervention was controlling bruxism and oral parafunction with any appropriate therapy.

## 2.3 | Literature sources and search

The literature search and selection were carried out by two independent reviewers (NBS, AC). The following electronic databases were searched during April 2022 and updated during August 2022: MEDLINE (through PubMed), EMBASE, Cochrane Central Library, BaseSearch, Open Access Thesis and Dissertation (openthesis.org), and ClinicalTrials.gov. A specific research equation was formulated in each database, using appropriate keywords and MeSH terms for exposure and outcomes, as detailed in Table S1. In addition, reference lists from eligible studies and previously published review articles were crosschecked to identify additional pertinent studies. Only articles in English were considered but no publication date limit was applied.

## 2.4 | Study selection and data extraction

Records from the literature searches were merged into a single list imported into an EndNote library (EndNote software, Clarivate,CLEverbridge GmbH, Gereonstr., Cologne, Germany), in which duplicates
(O) Outcomes: The primary outcome was the occurrence of PIDs, including mucositis and peri-implantitis. Any case definition of peri-implant mucositis and peri-implantitis was considered. Because a preventive intervention aims to prevent the occurrence of a disease (i.e., PIDs) but also to maintain health (i.e., peri-implant health), clinical parameters essential to define peri-implant health and diagnose PIDs according to the 2017 World Workshop on the Classification of Periodontal and Peri-Implant Diseases and Conditions (Berglundh et al., 2018; Caton et al., 2018) were also considered as primary outcome measures, such as bleeding on probing (BOP) (or other indices for peri-implant tissue inflammation), peri-implant probing depth (PPD), suppuration, and radiographic marginal bone level (MBL). Eligible studies must report at least one of the aforementioned primary outcomes to be selected. Biomarkers in saliva or peri-implant fluid and dental implant survival rate were considered as secondary outcomes (Derks et al., 2022).

(S) Study design: Randomized (RCTs) and non-randomized controlled trials (NRCTs), with a minimum of 6 months follow-up from implant loading.

### 2.2.2 | PECOS

(P) Participants: Adult patients awaiting dental implant placement or having dental implants with peri-implant health.

(E) Exposure: Exposure to a risk factor for PIDs.

(C) Comparison: Adult patients awaiting dental implant placement or having dental implants with peri-implant health no more exposed to the risk factor.

(O) Outcomes: Same as in the PICOS format described above.

(S) Study design: Prospective and retrospective cohort studies and case-control studies (matched or not) with a minimum of 6 months follow-up from implant loading.

Based on the above-mentioned criteria, separate research questions were constructed for each PID risk factor explored.

The efficacy of primordial and primary preventive interventions for PIDs should be ideally assessed in longitudinal and interventional studies. However, because of the difficulties and ethical issues in conducting certain types of RCTs/NRCTs and the expected paucity of literature on PID prevention, prospective and retrospective observational studies were also considered. To assess the efficacy of risk factor control, the target population must be exposed to the risk factor at some point in time. Therefore, studies assessing the association between a risk factor and PID occurrence were not considered. For instance, comparisons between diabetes and non-diabetes patients with dental implants, or smokers versus non-smokers, were not considered. Indeed, the aim of the present study was designed to assess the efficacy of risk factor control on PID prevention, but not to identify the risk factors.

A set of potentially modifiable risk factors were predetermined and searched. We made the pragmatic decision not to include prosthesis-related risk factors because time and resources made them beyond the scope of this review. Therefore, the present systematic

review was limited to the following risk factors and their corresponding preventive interventions:

* Poor glycaemic control (as measured by HbA1c [in percentage]) in diabetic and pre-diabetic patients. No threshold was set for HbA1c because of country-related differences and comorbidity-related impact in defining good and poor glycaemic control. The preventive intervention was improving or obtaining glycaemic control.

* Smoking status (as defined by current smoking) and smoking habit (as measured by the quantity [number of cigarettes] or type of smoking habit [e.g., cigarette, e-cigarette, water pipe]). The preventive intervention was the promotion of smoking cessation by any guideline-based strategy.

* Type of and adherence to supportive periodontal/peri-implant care (SPC) protocols. The preventive intervention was promoting and obtaining adequate/regular patient adherence to the SPC employed. Studies comparing the efficacy of different SPC protocols were also considered.

* Width of the PIKM and thickness of the peri-implant soft tissue. A deficiency of PIKM or a thin peri-implant mucosa was considered as a risk factor. The preventive intervention was a surgical procedure for soft tissue augmentation, including PIKM augmentation. To be included, studies had to report the surgical indication, which should clearly be to augment the peri-implant keratinized tissue width or the peri-implant soft tissue thickness.

* Oral hygiene behaviours (including frequency and methods of brushing). The preventive intervention was promoting and achieving optimal/improved patient's oral hygiene behaviour.

* Bruxism/oral parafunction. The preventive intervention was controlling bruxism and oral parafunction with any appropriate therapy.

## 2.3 | Literature sources and search

The literature search and selection were carried out by two independent reviewers (NBS, AC). The following electronic databases were searched during April 2022 and updated during August 2022: MEDLINE (through PubMed), EMBASE, Cochrane Central Library, BaseSearch, Open Access Thesis and Dissertation (openthesis.org), and ClinicalTrials.gov. A specific research equation was formulated in each database, using appropriate keywords and MeSH terms for exposure and outcomes, as detailed in Table S1. In addition, reference lists from eligible studies and previously published review articles were crosschecked to identify additional pertinent studies. Only articles in English were considered but no publication date limit was applied.

## 2.4 | Study selection and data extraction

Records from the literature searches were merged into a single list imported into an EndNote library (EndNote software, Clarivate,CLEverbridge GmbH, Gereonstr., Cologne, Germany), in which duplicates
were automatically removed. Two independent reviewers (NBS, AC) undertook the study screening process by using Rayyan software (Intelligent Systematic Review, 2022) to support the reviewers at all different stages of the systematic review. Records were first screened at the title and abstract level. Each record had to be screened and voted upon (to be included or excluded) by the two reviewers, and blinded to the other reviewer's assessment. Any disagreement was resolved by a third author (MCC or PhB) acting as a moderator. Subsequently, reviewers performed a full-text evaluation of the pre-selected articles. Similarly, this evaluation was performed independently, and disagreements were resolved by the moderator to reach the final selection of the articles. Agreement between the reviewers was assessed by calculating Cohen's Kappa.

A dedicated Microsoft EXCEL spreadsheet was created to facilitate the data extraction process, which was conducted by three reviewers (MCC, NBS, AC). Study characteristics and principal findings were collated, analysed, and then summarized into tables to be processed for qualitative and quantitative analyses.

## 2.5 | Risk-of-bias assessment

Once the full-text article analysis was completed, the reviewers undertook evaluation of the risk of bias, which was assessed using appropriate tools according to the study design. Specifically, the revised Cochrane risk-of-bias tool for randomized trials (RoB-2) (Higgins et al., 2016), the ROBINS-I tool for NRCTs (Sterne et al., 2016), and the Newcastle-Ottawa Scale (NOS) (Stang, 2010) for cohort and case-control studies were employed as needed. Publication bias and sponsoring bias were also evaluated. The source of funding was classified as unknown if not reported in the original studies (Popelut et al., 2010).

## 2.6 | Data synthesis and analysis

Whenever information essential for inclusion (e.g., duration of follow-up, outcome measures) or potentially relevant data were missing in the published documents, the corresponding authors were contacted by email. When no answer was forthcoming, the record was excluded. The feasibility and appropriateness of meta-analyses was checked once data extraction was completed, and the selected studies were re-grouped by the type of exposure and outcome(s). Outcome measures were extracted as frequency or rate (in percentage), mean (standard deviation, SD), or median (interquartile range, IQR).

For the pooled data analysis, the odds ratio (OR) and 95% confidence intervals (95% CIs) between the compared groups were estimated using the Mantel-Haenszel method for binary outcomes. For continuous data, the mean difference (MD) or the standardized mean difference (SMD) with 95% CI between the groups were estimated using inverse variance weighting. Heterogeneity was assessed by the I² statistic, with values <40% considered as negligible, 40%-75% as moderate, and >75% as substantial heterogeneity (https://training.

cochrane.org/handbook/current). Random effect models were used as a more conservative approach, as a significant inter-study heterogeneity was expected. The pooled effect was considered significant if *p* < .05. The meta-analysis was performed by using RevMan software (Version 5.3; Cochrane Collaboration) and OpenMetaAnalyst.

# 3 | RESULTS

## 3.1 | Study selection and characteristics

By merging the searches of the two independent reviewers on the different databases, 7565 records were initially identified. Figure 2 shows the flow-chart of the study selection. The list of excluded articles after full-text evaluation is provided in Table S2. Finally, 48 articles were selected and distributed according to the type of risk factor. The kappa value was 0.612 (99.2% of agreement) for the selection upon title and abstract, and 0.466 (89.9% of agreement) for the selection after full-text evaluation.

## 3.2 | Synthesis of the results

### 3.2.1 | Glycaemic control

No interventional study assessing the efficacy of interventions to improve glycaemic control on peri-implant health and diseases was found. Evidence relies upon 11 observational cohort and case-control studies (Table 1). Seven studies compared well-controlled versus poorly controlled type-2 diabetes patients receiving dental implants (Aguilar-Salvatierra et al., 2016; Al Amri et al., 2016; Al Zahrani & Al Mutairi, 2019; Al-Sowygh et al., 2018; Ghiraldini et al., 2016; Gomez-Moreno et al., 2015; Tawil et al., 2008). Glycaemic control was assessed by measuring HbA1c levels and was defined as good if the value was between 6.1% and 8% in five studies, <7% in one study, and <6% in another study. Poor glycaemic control was defined as HbA1c level ranging between 8.1% and 10% in five studies, >8% in one study, and ranging between 7% and 9% in another study. Three studies also included a group of very poorly controlled type-2 diabetes patients (HbA1c >9 or >10%) (Al-Sowygh et al., 2018; Gomez-Moreno et al., 2015; Tawil et al., 2008). The remaining four studies compared pre-diabetes versus diabetes patients (Abduljabbar et al., 2017; Alrabiah et al., 2018; Alsahhaf et al., 2019; Mokeem et al., 2019), with significant similarities in the study design and methods and overlapping results. The authors were contacted by email to verify whether these studies investigated independent study populations or rather they analysed the same pool of patients. No reply was obtained and therefore these four studies were not included in the meta-analysis.

Pooled data analysis showed a significantly lower rate of peri-implantitis (OR = 0.16; 95% CI: 0.03-0.96; *p* = .004; I²: 0%) and significantly lower MBL changes over time (MD: -0.36 mm; 95% CI: -0.65 to -0.07; *p* < .0001; I²: 95%) in patients with good glycaemic control versus poor glycaemic control. The MD values in PPD and
were automatically removed. Two independent reviewers (NBS, AC) undertook the study screening process by using Rayyan software (Intelligent Systematic Review, 2022) to support the reviewers at all different stages of the systematic review. Records were first screened at the title and abstract level. Each record had to be screened and voted upon (to be included or excluded) by the two reviewers, and blinded to the other reviewer's assessment. Any disagreement was resolved by a third author (MCC or PhB) acting as a moderator. Subsequently, reviewers performed a full-text evaluation of the pre-selected articles. Similarly, this evaluation was performed independently, and disagreements were resolved by the moderator to reach the final selection of the articles. Agreement between the reviewers was assessed by calculating Cohen's Kappa.

A dedicated Microsoft EXCEL spreadsheet was created to facilitate the data extraction process, which was conducted by three reviewers (MCC, NBS, AC). Study characteristics and principal findings were collated, analysed, and then summarized into tables to be processed for qualitative and quantitative analyses.

## 2.5 | Risk-of-bias assessment

Once the full-text article analysis was completed, the reviewers undertook evaluation of the risk of bias, which was assessed using appropriate tools according to the study design. Specifically, the revised Cochrane risk-of-bias tool for randomized trials (RoB-2) (Higgins et al., 2016), the ROBINS-I tool for NRCTs (Sterne et al., 2016), and the Newcastle-Ottawa Scale (NOS) (Stang, 2010) for cohort and case-control studies were employed as needed. Publication bias and sponsoring bias were also evaluated. The source of funding was classified as unknown if not reported in the original studies (Popelut et al., 2010).

## 2.6 | Data synthesis and analysis

Whenever information essential for inclusion (e.g., duration of follow-up, outcome measures) or potentially relevant data were missing in the published documents, the corresponding authors were contacted by email. When no answer was forthcoming, the record was excluded. The feasibility and appropriateness of meta-analyses was checked once data extraction was completed, and the selected studies were re-grouped by the type of exposure and outcome(s). Outcome measures were extracted as frequency or rate (in percentage), mean (standard deviation, SD), or median (interquartile range, IQR).

For the pooled data analysis, the odds ratio (OR) and 95% confidence intervals (95% CIs) between the compared groups were estimated using the Mantel-Haenszel method for binary outcomes. For continuous data, the mean difference (MD) or the standardized mean difference (SMD) with 95% CI between the groups were estimated using inverse variance weighting. Heterogeneity was assessed by the I² statistic, with values <40% considered as negligible, 40%-75% as moderate, and >75% as substantial heterogeneity (https://training.

cochrane.org/handbook/current). Random effect models were used as a more conservative approach, as a significant inter-study heterogeneity was expected. The pooled effect was considered significant if *p* < .05. The meta-analysis was performed by using RevMan software (Version 5.3; Cochrane Collaboration) and OpenMetaAnalyst.

# 3 | RESULTS

## 3.1 | Study selection and characteristics

By merging the searches of the two independent reviewers on the different databases, 7565 records were initially identified. Figure 2 shows the flow-chart of the study selection. The list of excluded articles after full-text evaluation is provided in Table S2. Finally, 48 articles were selected and distributed according to the type of risk factor. The kappa value was 0.612 (99.2% of agreement) for the selection upon title and abstract, and 0.466 (89.9% of agreement) for the selection after full-text evaluation.

## 3.2 | Synthesis of the results

### 3.2.1 | Glycaemic control

No interventional study assessing the efficacy of interventions to improve glycaemic control on peri-implant health and diseases was found. Evidence relies upon 11 observational cohort and case-control studies (Table 1). Seven studies compared well-controlled versus poorly controlled type-2 diabetes patients receiving dental implants (Aguilar-Salvatierra et al., 2016; Al Amri et al., 2016; Al Zahrani & Al Mutairi, 2019; Al-Sowygh et al., 2018; Ghiraldini et al., 2016; Gomez-Moreno et al., 2015; Tawil et al., 2008). Glycaemic control was assessed by measuring HbA1c levels and was defined as good if the value was between 6.1% and 8% in five studies, <7% in one study, and <6% in another study. Poor glycaemic control was defined as HbA1c level ranging between 8.1% and 10% in five studies, >8% in one study, and ranging between 7% and 9% in another study. Three studies also included a group of very poorly controlled type-2 diabetes patients (HbA1c >9 or >10%) (Al-Sowygh et al., 2018; Gomez-Moreno et al., 2015; Tawil et al., 2008). The remaining four studies compared pre-diabetes versus diabetes patients (Abduljabbar et al., 2017; Alrabiah et al., 2018; Alsahhaf et al., 2019; Mokeem et al., 2019), with significant similarities in the study design and methods and overlapping results. The authors were contacted by email to verify whether these studies investigated independent study populations or rather they analysed the same pool of patients. No reply was obtained and therefore these four studies were not included in the meta-analysis.

Pooled data analysis showed a significantly lower rate of peri-implantitis (OR = 0.16; 95% CI: 0.03-0.96; *p* = .004; I²: 0%) and significantly lower MBL changes over time (MD: -0.36 mm; 95% CI: -0.65 to -0.07; *p* < .0001; I²: 95%) in patients with good glycaemic control versus poor glycaemic control. The MD values in PPD and
<figure><img src="image_3.png" /><figcaption>**FIGURE 2** Flow-chart of literature search and study selection.</figcaption></figure>

BOP were not significantly different between the groups (Figure 3). Dental implant survival was assessed in five studies (Aguilar-Salvatierra et al., 2016; Al Amri et al., 2016; Al Zahrani & Al Mutairi, 2019; Ghiraldini et al., 2016; Tawil et al., 2008). The estimated mean implant survival was 99% (95% CI: 97.8%-100% based on 253 dental implants) in patients with good glycaemic control and 95.6% (95% CI: 91.4%-99.8% based on 271 dental implants) in patients with poor glycaemic control. Three of these studies reported no implant loss (100% survival) over the study follow-up (ranging from 1 to 7 years) for both good and poor glycaemic control groups. Two studies (Aguilar-Salvatierra et al., 2016; Tawil et al., 2008), which included 309 implants, observed implant loss and were therefore used for meta-analysis; this showed that diabetes patients with poor glycaemic control have a 7.59 times increased risk of dental implant failure compared to patients with good glycaemic control (OR = 7.59; 95% CI: 1.63-35.3; *p* = .01; *I*²: 0%). Reasons for implant loss were not clearly specified; they included peri-implant and osseointegration problems occurring 1-3 years after implant placement (Aguilar-Salvatierra et al., 2016; Tawil et al., 2008).

Two studies evaluated biomarkers in the peri-implant sulcular fluid. One study assessed the levels of transforming growth factor-β (TGF-β), fibroblast growth factor (FGF), osteopontin (OPN), osteocalcin (OC), and osteoprotegerin (OPG) in the peri-implant fluid and compared them between patients with good (HbA1c: 6.1%-8%) and poor (HbA1c >8%) glycaemic control, as well as with non-diabetes patients (Ghiraldini et al., 2016). At 12 months, OPN levels were significantly lower in poorly controlled diabetes patients compared with non-diabetes patients, but no difference was observed among diabetes patients, irrespective of the HbA1c values. Another study evaluated the levels of advanced glycation end products (AGEs) in peri-implant sulcular fluid (via ELISA testing) and found a significant positive

correlation between AGEs and PPD and MBL in patients with poor glycaemic control (HbA1c >10%), supporting a compromised peri-implant state in these patients (Al-Sowygh et al., 2018).

Regarding pre-diabetes as a potential risk factor, selected studies not included in the meta-analysis showed a significantly worse peri-implant health in pre-diabetes compared to non-diabetes patients, but observed no significant differences between pre-diabetes (defined as HbA1c between 5.7% and 6.4%) and diabetes patients (HbA1c ≥6.5%) (Abduljabbar et al., 2017; Alrabiah et al., 2018; Alsahhaf et al., 2019; Mokeem et al., 2019) (Tables 1 and S3).

### 3.2.2 | Smoking habits

No interventional study was found. Overall, four studies met the selection criteria and were included (F. Alqahtani et al., 2019; M. A. AlQahtani et al., 2018; ArRejaie et al., 2019; Costa et al., 2022) (Tables 2 and S3). Significant similarities between three studies conducted by the same research team were noted (F. Alqahtani et al., 2019; M. A. AlQahtani et al., 2018; ArRejaie et al., 2019); the authors were contacted to know if they concerned independent patients samples but no answer was obtained. Because of doubts about overlapping data between the study populations, no pooled data analysis was performed.

Among the selected studies, only one described the occurrence of PIDs as a clinical diagnosis, reporting a lower rate of peri-implant mucositis (43.9% vs. 48.6%) and peri-implantitis (19.7% vs. 30.5%) in former smokers compared to current smokers (Costa et al., 2022). The authors observed a direct association between the cumulative smoking exposure and the risk for peri-implantitis as well as the time span since smoking cessation. All studies reported significant clinical
<figure><img src="image_3.png" /><figcaption>**FIGURE 2** Flow-chart of literature search and study selection.</figcaption></figure>

BOP were not significantly different between the groups (Figure 3). Dental implant survival was assessed in five studies (Aguilar-Salvatierra et al., 2016; Al Amri et al., 2016; Al Zahrani & Al Mutairi, 2019; Ghiraldini et al., 2016; Tawil et al., 2008). The estimated mean implant survival was 99% (95% CI: 97.8%-100% based on 253 dental implants) in patients with good glycaemic control and 95.6% (95% CI: 91.4%-99.8% based on 271 dental implants) in patients with poor glycaemic control. Three of these studies reported no implant loss (100% survival) over the study follow-up (ranging from 1 to 7 years) for both good and poor glycaemic control groups. Two studies (Aguilar-Salvatierra et al., 2016; Tawil et al., 2008), which included 309 implants, observed implant loss and were therefore used for meta-analysis; this showed that diabetes patients with poor glycaemic control have a 7.59 times increased risk of dental implant failure compared to patients with good glycaemic control (OR = 7.59; 95% CI: 1.63-35.3; *p* = .01; *I*²: 0%). Reasons for implant loss were not clearly specified; they included peri-implant and osseointegration problems occurring 1-3 years after implant placement (Aguilar-Salvatierra et al., 2016; Tawil et al., 2008).

Two studies evaluated biomarkers in the peri-implant sulcular fluid. One study assessed the levels of transforming growth factor-β (TGF-β), fibroblast growth factor (FGF), osteopontin (OPN), osteocalcin (OC), and osteoprotegerin (OPG) in the peri-implant fluid and compared them between patients with good (HbA1c: 6.1%-8%) and poor (HbA1c >8%) glycaemic control, as well as with non-diabetes patients (Ghiraldini et al., 2016). At 12 months, OPN levels were significantly lower in poorly controlled diabetes patients compared with non-diabetes patients, but no difference was observed among diabetes patients, irrespective of the HbA1c values. Another study evaluated the levels of advanced glycation end products (AGEs) in peri-implant sulcular fluid (via ELISA testing) and found a significant positive

correlation between AGEs and PPD and MBL in patients with poor glycaemic control (HbA1c >10%), supporting a compromised peri-implant state in these patients (Al-Sowygh et al., 2018).

Regarding pre-diabetes as a potential risk factor, selected studies not included in the meta-analysis showed a significantly worse peri-implant health in pre-diabetes compared to non-diabetes patients, but observed no significant differences between pre-diabetes (defined as HbA1c between 5.7% and 6.4%) and diabetes patients (HbA1c ≥6.5%) (Abduljabbar et al., 2017; Alrabiah et al., 2018; Alsahhaf et al., 2019; Mokeem et al., 2019) (Tables 1 and S3).

### 3.2.2 | Smoking habits

No interventional study was found. Overall, four studies met the selection criteria and were included (F. Alqahtani et al., 2019; M. A. AlQahtani et al., 2018; ArRejaie et al., 2019; Costa et al., 2022) (Tables 2 and S3). Significant similarities between three studies conducted by the same research team were noted (F. Alqahtani et al., 2019; M. A. AlQahtani et al., 2018; ArRejaie et al., 2019); the authors were contacted to know if they concerned independent patients samples but no answer was obtained. Because of doubts about overlapping data between the study populations, no pooled data analysis was performed.

Among the selected studies, only one described the occurrence of PIDs as a clinical diagnosis, reporting a lower rate of peri-implant mucositis (43.9% vs. 48.6%) and peri-implantitis (19.7% vs. 30.5%) in former smokers compared to current smokers (Costa et al., 2022). The authors observed a direct association between the cumulative smoking exposure and the risk for peri-implantitis as well as the time span since smoking cessation. All studies reported significant clinical
<table><caption>TABLE 1 Characteristics and outcomes of the selected studies analysing the impact of glycaemic control on the prevention of peri-implant diseases.</caption><thead><tr><th rowspan="2">Reference</th><th rowspan="2">Study design</th><th rowspan="2">Country</th><th rowspan="2">Setting</th><th rowspan="2">Study time frame</th><th rowspan="2">Follow-up duration</th><th rowspan="2">Study population</th><th rowspan="2">Type of intervention or exposure</th><th colspan="2">Diagnosis of peri-implant mucositis</th><th colspan="2">Diagnosis of peri-implantitis</th><th rowspan="2">Survival rate</th><th rowspan="2">Peri-implant mucosa inflammation (BOP)</th><th rowspan="2">Peri-implant probing pocket depth (mm)</th><th rowspan="2">Radiographic marginal bone level changes (mm)</th></tr><tr><th>No. of patients (no. of implants)</th><th>Patient level</th><th>Implant level</th><th>Patient level</th><th>Implant level</th></tr></thead><tbody><tr><td rowspan="10">Diabetes</td><td rowspan="10">Tawil et al. (2008)</td><td rowspan="10">Cohort study</td><td rowspan="10">Private periodontal practice Lebanon</td><td rowspan="10">NR</td><td rowspan="10">Mean F-UP: 42.4 months</td><td rowspan="10">Consecutive patients with T2DM receiving dental implants<br/>N = 45 (255)</td><td>HbA1c: &lt;7%<br/>N = 22 (103)</td><td>NR</td><td>NR</td><td>0/22 (0%)</td><td>0/103 (0%)</td><td>99.1%</td><td>NR</td><td>NR</td><td>0.24 ± 0.28</td></tr><tr><td>HbA1c: 7%–9%<br/>N = 22 (141)</td><td>NR</td><td>NR</td><td>NR</td><td>6/141 (4.2%)</td><td>96.5%</td><td>NR</td><td>NR</td><td>0.52 ± 0.75</td></tr><tr><td>HbA1c: &gt;9%<br/>N = 1 (11)</td><td>NR</td><td>NR</td><td>NR</td><td>1/11 (9.1%)</td><td>90.9%</td><td>NR</td><td>NR</td><td>1.62</td></tr><tr><td>HbA1c: ≤6%<br/>(no DM)<br/>N = 33 (33)</td><td>NR</td><td>NR</td><td>0/33 (0%)</td><td>0/33 (0%)</td><td>100% at 1 year<br/>100% at 2 year</td><td>0.39 ± 0.04 at 1 year<br/>0.44 ± 0.07 at 2 year</td><td>2.60 ± 0.18 at 1 year<br/>2.67 ± 0.14 at 2 year</td><td>0.64 ± 0.23 at 1 year<br/>0.72 ± 0.27 at 2 year</td></tr><tr><td>HbA1c:<br/>6.1%–8%<br/>N = 30 (30)</td><td>NR</td><td>NR</td><td>1/30 (3.4%)</td><td>1/30 (3.4%)</td><td>100% at 1 year<br/>96.6% at 2 year</td><td>0.45 ± 0.07 at 1 year<br/>0.51 ± 0.05 at 2 year</td><td>2.66 ± 0.27 at 1 year<br/>2.79 ± 0.24 at 2 year</td><td>0.86 ± 0.25 at 1 year<br/>0.98 ± 0.27 at 2 year</td></tr><tr><td>HbA1c:<br/>8.1%–10%<br/>N = 22 (22)</td><td>NR</td><td>NR</td><td>3/22 (13.7%)</td><td>3/22 (13.7%)</td><td>95.4% at 1 year<br/>86.3% at 2 year</td><td>0.65 ± 0.06 at 1 year<br/>0.05 at 2 year</td><td>3.57 ± 0.37 at 1 year<br/>3.68 ± 0.48 at 2 year</td><td>1.54 ± 0.43 at 1 year<br/>1.92 ± 0.38 at 2 year</td></tr><tr><td>HbA1c: ≤6%<br/>(no DM)<br/>N = 19 (19)</td><td>0%</td><td>0%</td><td>0%</td><td>0%</td><td>100%</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td>HbA1c:<br/>6.1%–8%<br/>N = 16 (16)</td><td>0%</td><td>0%</td><td>0%</td><td>0%</td><td>100%</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td>HbA1c: &gt;8%<br/>N = 16 (16)</td><td>0%</td><td>0%</td><td>0%</td><td>0%</td><td>100%</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td rowspan="3">Aguilar-Salvatierra et al. (2016)</td><td rowspan="3">Cohort study</td><td rowspan="3">University setting Spain</td><td rowspan="3">NR</td><td rowspan="3">F-UP: 24 months</td><td rowspan="3">Patients with T2DM receiving immediately loaded dental implants in the aesthetic zone of the upper maxilla<br/>N = 85 (85)</td><td>HbA1c: ≤6%<br/>(no DM)<br/>N = 33 (33)</td><td>NR</td><td>NR</td><td>0/33 (0%)</td><td>0/33 (0%)</td><td>100% at 1 year<br/>100% at 2 year</td><td>0.39 ± 0.04 at 1 year<br/>0.44 ± 0.07 at 2 year</td><td>2.60 ± 0.18 at 1 year<br/>2.67 ± 0.14 at 2 year</td><td>0.64 ± 0.23 at 1 year<br/>0.72 ± 0.27 at 2 year</td></tr><tr><td>HbA1c:<br/>6.1%–8%<br/>N = 30 (30)</td><td>NR</td><td>NR</td><td>1/30 (3.4%)</td><td>1/30 (3.4%)</td><td>100% at 1 year<br/>96.6% at 2 year</td><td>0.45 ± 0.07 at 1 year<br/>0.51 ± 0.05 at 2 year</td><td>2.66 ± 0.27 at 1 year<br/>2.79 ± 0.24 at 2 year</td><td>0.86 ± 0.25 at 1 year<br/>0.98 ± 0.27 at 2 year</td></tr><tr><td>HbA1c:<br/>8.1%–10%<br/>N = 22 (22)</td><td>NR</td><td>NR</td><td>3/22 (13.7%)</td><td>3/22 (13.7%)</td><td>95.4% at 1 year<br/>86.3% at 2 year</td><td>0.65 ± 0.06 at 1 year<br/>0.05 at 2 year</td><td>3.57 ± 0.37 at 1 year<br/>3.68 ± 0.48 at 2 year</td><td>1.54 ± 0.43 at 1 year<br/>1.92 ± 0.38 at 2 year</td></tr><tr><td rowspan="3">Ghiraaldini et al. (2016)</td><td rowspan="3">Case-control study</td><td rowspan="3">University setting Brazil</td><td rowspan="3">2012–2013 F-UP: 12 months</td><td rowspan="3">Patients with T2DM receiving one posterior dental implant<br/>N = 51 (51)</td><td>HbA1c: ≤6%<br/>(no DM)<br/>N = 19 (19)</td><td>0%</td><td>0%</td><td>0%</td><td>0%</td><td>100%</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td>HbA1c:<br/>6.1%–8%<br/>N = 16 (16)</td><td>0%</td><td>0%</td><td>0%</td><td>0%</td><td>100%</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td>HbA1c: &gt;8%<br/>N = 16 (16)</td><td>0%</td><td>0%</td><td>0%</td><td>0%</td><td>100%</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td rowspan="3">Gomez-Moreno et al. (2015)</td><td rowspan="3">Cohort study</td><td rowspan="3">University setting Spain</td><td rowspan="3">NR</td><td rowspan="3">F-UP: 36 months</td><td rowspan="3">Patients with T2DM receiving dental implants<br/>N = 67 (67)</td><td>HbA1c: ≤6%<br/>(no DM)<br/>N = 21 (21)</td><td>NR</td><td>NR</td><td>0%</td><td>0%</td><td>0%</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td>HbA1c:<br/>6.1%–8%<br/>N = 24 (24)</td><td>NR</td><td>NR</td><td>0%</td><td>0%</td><td>0%</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td>HbA1c:<br/>6.1%–8%<br/>N = 24 (24)</td><td>NR</td><td>NR</td><td>0%</td><td>0%</td><td>0%</td><td>NR</td><td>NR</td><td>NR</td></tr></tbody></table>

(Continues)
<table><caption>TABLE 1 Characteristics and outcomes of the selected studies analysing the impact of glycaemic control on the prevention of peri-implant diseases.</caption><thead><tr><th rowspan="2">Reference</th><th rowspan="2">Study design</th><th rowspan="2">Country</th><th rowspan="2">Setting</th><th rowspan="2">Study time frame</th><th rowspan="2">Follow-up duration</th><th rowspan="2">Study population</th><th rowspan="2">Type of intervention or exposure</th><th colspan="2">Diagnosis of peri-implant mucositis</th><th colspan="2">Diagnosis of peri-implantitis</th><th rowspan="2">Survival rate</th><th rowspan="2">Peri-implant mucosa inflammation (BOP)</th><th rowspan="2">Peri-implant probing pocket depth (mm)</th><th rowspan="2">Radiographic marginal bone level changes (mm)</th></tr><tr><th>No. of patients (no. of implants)</th><th>Patient level</th><th>Implant level</th><th>Patient level</th><th>Implant level</th></tr></thead><tbody><tr><td rowspan="10">Diabetes</td><td rowspan="10">Tawil et al. (2008)</td><td rowspan="10">Cohort study</td><td rowspan="10">Private periodontal practice Lebanon</td><td rowspan="10">NR</td><td rowspan="10">Mean F-UP: 42.4 months</td><td rowspan="10">Consecutive patients with T2DM receiving dental implants<br/>N = 45 (255)</td><td>HbA1c: &lt;7%<br/>N = 22 (103)</td><td>NR</td><td>NR</td><td>0/22 (0%)</td><td>0/103 (0%)</td><td>99.1%</td><td>NR</td><td>NR</td><td>0.24 ± 0.28</td></tr><tr><td>HbA1c: 7%–9%<br/>N = 22 (141)</td><td>NR</td><td>NR</td><td>NR</td><td>6/141 (4.2%)</td><td>96.5%</td><td>NR</td><td>NR</td><td>0.52 ± 0.75</td></tr><tr><td>HbA1c: &gt;9%<br/>N = 1 (11)</td><td>NR</td><td>NR</td><td>NR</td><td>1/11 (9.1%)</td><td>90.9%</td><td>NR</td><td>NR</td><td>1.62</td></tr><tr><td>HbA1c: ≤6%<br/>(no DM)<br/>N = 33 (33)</td><td>NR</td><td>NR</td><td>0/33 (0%)</td><td>0/33 (0%)</td><td>100% at<br/>1 year<br/>100% at<br/>2 year</td><td>0.39 ± 0.04 at<br/>1 year<br/>0.44 ± 0.07 at<br/>2 year</td><td>2.60 ± 0.18 at<br/>1 year<br/>2.67 ± 0.14 at<br/>2 year</td><td>0.64 ± 0.23 at<br/>1 year<br/>0.72 ± 0.27 at<br/>2 year</td></tr><tr><td>HbA1c:<br/>6.1%–8%<br/>N = 30 (30)</td><td>NR</td><td>NR</td><td>1/30 (3.4%)</td><td>1/30 (3.4%)</td><td>100% at<br/>1 year<br/>96.6% at<br/>2 year</td><td>0.45 ± 0.07 at<br/>1 year<br/>0.51 ± 0.05 at<br/>2 year</td><td>2.66 ± 0.27 at<br/>1 year<br/>2.79 ± 0.24 at<br/>2 year</td><td>0.86 ± 0.25 at<br/>1 year<br/>0.98 ± 0.27 at<br/>2 year</td></tr><tr><td>HbA1c:<br/>8.1%–10%<br/>N = 22 (22)</td><td>NR</td><td>NR</td><td>3/22 (13.7%)</td><td>3/22 (13.7%)</td><td>95.4% at<br/>1 year<br/>86.3% at<br/>2 year</td><td>0.65 ± 0.06 at<br/>1 year<br/>0.05 at<br/>2 year</td><td>3.57 ± 0.37 at<br/>1 year<br/>3.68 ± 0.48 at<br/>2 year</td><td>1.54 ± 0.43 at<br/>1 year<br/>1.92 ± 0.38 at<br/>2 year</td></tr><tr><td>HbA1c: ≤6%<br/>(no DM)<br/>N = 19 (19)</td><td>0%</td><td>0%</td><td>0%</td><td>0%</td><td>100%</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td>HbA1c:<br/>6.1%–8%<br/>N = 16 (16)</td><td>0%</td><td>0%</td><td>0%</td><td>0%</td><td>100%</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td>HbA1c: &gt;8%<br/>N = 16 (16)</td><td>0%</td><td>0%</td><td>0%</td><td>0%</td><td>100%</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td rowspan="3">Aguilar-Salvatierra et al. (2016)</td><td rowspan="3">Cohort study</td><td rowspan="3">University setting Spain</td><td rowspan="3">NR</td><td rowspan="3">F-UP: 24 months</td><td rowspan="3">Patients with T2DM receiving immediately loaded dental implants in the aesthetic zone of the upper maxilla<br/>N = 85 (85)</td><td>HbA1c: ≤6%<br/>(no DM)<br/>N = 33 (33)</td><td>NR</td><td>NR</td><td>0/33 (0%)</td><td>0/33 (0%)</td><td>100% at<br/>1 year<br/>100% at<br/>2 year</td><td>0.39 ± 0.04 at<br/>1 year<br/>0.44 ± 0.07 at<br/>2 year</td><td>2.60 ± 0.18 at<br/>1 year<br/>2.67 ± 0.14 at<br/>2 year</td><td>0.64 ± 0.23 at<br/>1 year<br/>0.72 ± 0.27 at<br/>2 year</td></tr><tr><td>HbA1c:<br/>6.1%–8%<br/>N = 30 (30)</td><td>NR</td><td>NR</td><td>1/30 (3.4%)</td><td>1/30 (3.4%)</td><td>100% at<br/>1 year<br/>96.6% at<br/>2 year</td><td>0.45 ± 0.07 at<br/>1 year<br/>0.51 ± 0.05 at<br/>2 year</td><td>2.66 ± 0.27 at<br/>1 year<br/>2.79 ± 0.24 at<br/>2 year</td><td>0.86 ± 0.25 at<br/>1 year<br/>0.98 ± 0.27 at<br/>2 year</td></tr><tr><td>HbA1c:<br/>8.1%–10%<br/>N = 22 (22)</td><td>NR</td><td>NR</td><td>3/22 (13.7%)</td><td>3/22 (13.7%)</td><td>95.4% at<br/>1 year<br/>86.3% at<br/>2 year</td><td>0.65 ± 0.06 at<br/>1 year<br/>0.05 at<br/>2 year</td><td>3.57 ± 0.37 at<br/>1 year<br/>3.68 ± 0.48 at<br/>2 year</td><td>1.54 ± 0.43 at<br/>1 year<br/>1.92 ± 0.38 at<br/>2 year</td></tr><tr><td rowspan="3">Ghiraaldini et al. (2016)</td><td rowspan="3">Case-control study</td><td rowspan="3">University setting Brazil</td><td rowspan="3">2012–2013<br/>F-UP: 12 months</td><td rowspan="3">Patients with T2DM receiving one posterior dental implant<br/>N = 51 (51)</td><td>HbA1c: ≤6%<br/>(no DM)<br/>N = 19 (19)</td><td>0%</td><td>0%</td><td>0%</td><td>0%</td><td>100%</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td>HbA1c:<br/>6.1%–8%<br/>N = 16 (16)</td><td>0%</td><td>0%</td><td>0%</td><td>0%</td><td>100%</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td>HbA1c: &gt;8%<br/>N = 16 (16)</td><td>0%</td><td>0%</td><td>0%</td><td>0%</td><td>100%</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td rowspan="3">Gomez-Moreno et al. (2015)</td><td rowspan="3">Cohort study</td><td rowspan="3">University setting Spain</td><td rowspan="3">NR</td><td rowspan="3">F-UP: 36 months</td><td rowspan="3">Patients with T2DM receiving dental implants<br/>N = 67 (67)</td><td>HbA1c: ≤6%<br/>(no DM)<br/>N = 21 (21)</td><td>NR</td><td>NR</td><td>0%</td><td>0%</td><td>0%</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td>HbA1c:<br/>6.1%–8%<br/>N = 24 (24)</td><td>NR</td><td>NR</td><td>0%</td><td>0%</td><td>0%</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td>HbA1c:<br/>6.1%–8%<br/>N = 24 (24)</td><td>NR</td><td>NR</td><td>0%</td><td>0%</td><td>0%</td><td>NR</td><td>NR</td><td>NR</td></tr></tbody></table>

(Continues)
<table><caption>TABLE 1 (Continued)</caption><thead><tr><th rowspan="2">Reference</th><th rowspan="2">Study design</th><th rowspan="2">Setting</th><th rowspan="2">Study time frame</th><th rowspan="2">Follow-up duration</th><th rowspan="2">Total no. patients (no. of implants)</th><th rowspan="2">Type of intervention or exposure</th><th colspan="2">Diagnosis of peri-implant mucositis</th><th colspan="2">Diagnosis of peri-implantitis</th><th rowspan="2">Survival rate</th><th rowspan="2">Peri-implant mucosa inflammation (BOP)</th><th rowspan="2">Peri-implant probing pocket depth (mm)</th><th rowspan="2">Radiographic marginal bone level changes (mm)</th></tr><tr><th>Patient level</th><th>Implant level</th><th>Patient level</th><th>Implant level</th></tr></thead><tbody><tr><td rowspan="10">Al Amri et al. (2016)</td><td rowspan="10">Cohort study</td><td rowspan="10">Hospital setting Saudi Arabia</td><td rowspan="10">NR</td><td rowspan="10">F-UP: 24 months</td><td rowspan="10">Partially edentulous T2DM patients receiving immediately loaded dental implants N = 91 (91)</td><td>HbA1c: 8.1%-10%</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>100%</td><td>0.60 ± 0.05 at 2 year<br>0.62 ± 0.06 at 3 year</td><td>2.31 ± 0.21 at 2 year<br>2.34 ± 0.20 at 3 year</td><td>0.59 ± 0.16 at 2 year<br>0.64 ± 0.17 at 3 year</td></tr><tr><td>HbA1c: &gt;10.1%</td><td>NR</td><td>NR</td><td>0%</td><td>0%</td><td>NR</td><td>0.62 ± 0.06 at 1 year<br>0.63 ± 0.07 at 2 year<br>0.72 ± 0.06 at 3 year</td><td>2.33 ± 0.28 at 1 year<br>2.37 ± 0.26 at 2 year<br>2.40 ± 0.25 at 3 year</td><td>0.54 ± 0.12 at 1 year<br>0.63 ± 0.16 at 2 year<br>0.70 ± 0.19 at 3 year</td></tr><tr><td>HbA1c: ≤6% (no DM)</td><td>N = 30 (30)</td><td>NR</td><td>NR</td><td>NR</td><td>100%</td><td>0.4 ± 0.02 at 1 year<br>0.4 ± 0.06 at 2 year<br>0.6 ± 0.04 at 1 year<br>0.62 ± 0.07 at 2 year<br>0.62 ± 0.05 at 2 year</td><td>1.9 ± 0.04 at 1 year<br>1.6 ± 0.05 at 2 year<br>2.3 ± 0.18 at 1 year<br>2.3 ± 0.15 at 2 year</td><td>0.45 ± 0.06 at 1 year<br>0.46 ± 0.16 at 2 year<br>0.54 ± 0.12 at 1 year<br>0.58 ± 0.15 at 2 year</td></tr><tr><td>HbA1c: 6.1%-8%</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>100%</td><td>0.6 ± 0.04 at 1 year<br>0.62 ± 0.07 at 2 year<br>0.62 ± 0.05 at 2 year</td><td>2.4 ± 0.35 at 1 year<br>2.3 ± 0.62 at 2 year</td><td>0.57 ± 0.07 at 1 year<br>0.59 ± 0.2 at 2 year</td></tr><tr><td>HbA1c: 8.1%-10%</td><td>N = 30 (30)</td><td>NR</td><td>NR</td><td>NR</td><td>100%</td><td>0.63 ± 0.02 at 1 year<br>0.62 ± 0.05 at 2 year</td><td>NR</td><td>0.25 ± 0.35 at 1 year<br>0.31 ± 0.22 at 2 year<br>0.44 ± 0.31 at 3 year<br>0.6 ± 0.18 at 7 year</td></tr><tr><td>HbA1c: &gt;8% (no DM)</td><td>N = 31 (31)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>0.48 ± 0.66 at 1 year<br>0.64 ± 0.72 at 2 year<br>0.83 ± 0.92 at 3 year<br>1.12 ± 0.87 at 7 year</td></tr><tr><td>HbA1c: ≤6% (no DM)</td><td>N = 35 (74)</td><td>NR</td><td>NR</td><td>NR</td><td>100%</td><td>NR</td><td>NR</td><td>0.48 ± 0.66 at 1 year<br>0.64 ± 0.72 at 2 year<br>0.83 ± 0.92 at 3 year<br>1.12 ± 0.87 at 7 year</td></tr><tr><td>HbA1c: &gt;8% (no DM)</td><td>N = 32 (50)</td><td>NR</td><td>NR</td><td>NR</td><td>100%</td><td>NR</td><td>NR</td><td>0.48 ± 0.66 at 1 year<br>0.64 ± 0.72 at 2 year<br>0.83 ± 0.92 at 3 year<br>1.12 ± 0.87 at 7 year</td></tr><tr><td>HbA1c: ≤6% (no DM)</td><td>N = 26 (42)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>0.48 ± 0.66 at 1 year<br>0.64 ± 0.72 at 2 year<br>0.83 ± 0.92 at 3 year<br>1.12 ± 0.87 at 7 year</td></tr><tr><td>HbA1c: 6.1%-8%</td><td>N = 93 (148)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>0.48 ± 0.66 at 1 year<br>0.64 ± 0.72 at 2 year<br>0.83 ± 0.92 at 3 year<br>1.12 ± 0.87 at 7 year</td></tr><tr><td>Al Sowygh et al. (2018)</td><td>Case-control study</td><td>Private referral dental clinic Greece/ Saudi Arabia</td><td>NR</td><td>F-UP: at least 36 months (Mean: &gt;62 months)</td><td>T2DM patients receiving dental implants N = 93 (148)</td><td>HbA1c: 8.1%-10%</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>10.8 (6-13.1)</td><td>1.4 (0.7-2.1)</td><td>0.8 (0-1.1)</td></tr></tbody></table>
<table><caption>TABLE 1 (Continued)</caption><thead><tr><th rowspan="2">Reference</th><th rowspan="2">Study design</th><th rowspan="2">Setting</th><th rowspan="2">Study time frame</th><th rowspan="2">Follow-up duration</th><th rowspan="2">Total no. patients (no. of implants)</th><th rowspan="2">Type of intervention or exposure</th><th colspan="2">Diagnosis of peri-implant mucositis</th><th colspan="2">Diagnosis of peri-implantitis</th><th rowspan="2">Survival rate</th><th rowspan="2">Peri-implant mucosa inflammation (BOP)</th><th rowspan="2">Peri-implant probing pocket depth (mm)</th><th rowspan="2">Radiographic marginal bone level changes (mm)</th></tr><tr><th>Patient level</th><th>Implant level</th><th>Patient level</th><th>Implant level</th></tr></thead><tbody><tr><td rowspan="10">Al Amri et al. (2016)</td><td rowspan="10">Cohort study</td><td rowspan="10">Hospital setting Saudi Arabia</td><td rowspan="10">NR</td><td rowspan="10">F-UP: 24 months</td><td rowspan="10">Partially edentulous T2DM patients receiving immediately loaded dental implants N = 91 (91)</td><td>HbA1c: 8.1%-10%</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>100%</td><td>0.60 ± 0.05 at 2 year<br>0.62 ± 0.06 at 3 year</td><td>2.31 ± 0.21 at 2 year<br>2.34 ± 0.20 at 3 year</td><td>0.59 ± 0.16 at 2 year<br>0.64 ± 0.17 at 3 year</td></tr><tr><td>HbA1c: &gt;10.1%</td><td>NR</td><td>NR</td><td>0%</td><td>0%</td><td>NR</td><td>0.62 ± 0.06 at 1 year<br>0.63 ± 0.07 at 2 year<br>0.72 ± 0.06 at 3 year</td><td>2.33 ± 0.28 at 1 year<br>2.37 ± 0.26 at 2 year<br>2.40 ± 0.25 at 3 year</td><td>0.54 ± 0.12 at 1 year<br>0.63 ± 0.16 at 2 year<br>0.70 ± 0.19 at 3 year</td></tr><tr><td>HbA1c: ≤6% (no DM)</td><td>N = 30 (30)</td><td>NR</td><td>NR</td><td>NR</td><td>100%</td><td>0.4 ± 0.02 at 1 year<br>0.4 ± 0.06 at 2 year<br>0.6 ± 0.04 at 1 year<br>0.62 ± 0.07 at 2 year<br>0.62 ± 0.05 at 2 year</td><td>1.9 ± 0.04 at 1 year<br>1.6 ± 0.05 at 2 year<br>2.3 ± 0.18 at 1 year<br>2.3 ± 0.15 at 2 year</td><td>0.45 ± 0.06 at 1 year<br>0.46 ± 0.16 at 2 year<br>0.54 ± 0.12 at 1 year<br>0.58 ± 0.15 at 2 year</td></tr><tr><td>HbA1c: 6.1%-8%</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>100%</td><td>0.6 ± 0.04 at 1 year<br>0.62 ± 0.07 at 2 year<br>0.62 ± 0.05 at 2 year</td><td>2.4 ± 0.35 at 1 year<br>2.3 ± 0.62 at 2 year</td><td>0.57 ± 0.07 at 1 year<br>0.59 ± 0.2 at 2 year</td></tr><tr><td>HbA1c: 8.1%-10%</td><td>N = 30 (30)</td><td>NR</td><td>NR</td><td>NR</td><td>100%</td><td>0.63 ± 0.02 at 1 year<br>0.62 ± 0.05 at 2 year</td><td>NR</td><td>0.25 ± 0.35 at 1 year<br>0.31 ± 0.22 at 2 year<br>0.44 ± 0.31 at 3 year<br>0.6 ± 0.18 at 7 year</td></tr><tr><td>HbA1c: &gt;8% (no DM)</td><td>N = 31 (31)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>0.48 ± 0.66 at 1 year<br>0.64 ± 0.72 at 2 year<br>0.83 ± 0.92 at 3 year<br>1.12 ± 0.87 at 7 year</td></tr><tr><td>HbA1c: ≤6% (no DM)</td><td>N = 35 (74)</td><td>NR</td><td>NR</td><td>NR</td><td>100%</td><td>NR</td><td>NR</td><td>0.8 (0-1.1)</td></tr><tr><td>HbA1c: 6.1%-8%</td><td>N = 32 (50)</td><td>NR</td><td>NR</td><td>NR</td><td>100%</td><td>NR</td><td>NR</td><td>1.4 (0.7-2.1)</td></tr><tr><td>HbA1c: 2009-2011</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>10.8 (6-13.1)</td></tr><tr><td>HbA1c: &gt;8%</td><td>N = 67 (124)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>18.2 (11.4-26.7)</td></tr><tr><td>Al Zahrani and Al Mutairi (2019)</td><td>Cohort study</td><td>Hospital setting Saudi Arabia</td><td>NR</td><td>F-UP: 7 years</td><td>T2DM patients requiring dental implant N = 93 (148)</td><td>T2DM patients receiving dental implants N = 93 (148)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td>Al-Sowygh et al. (2018)</td><td>Case-control study</td><td>Private referral dental clinic Greece/ Saudi Arabia</td><td>NR</td><td>F-UP: at least 36 months (Mean: &gt;62 months)</td><td>T2DM patients receiving dental implants N = 93 (148)</td><td>HbA1c: ≤6% (no DM)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td></tr></tbody></table>
<table><caption>TABLE 1 (Continued)</caption><thead><tr><th rowspan="2">Reference</th><th rowspan="2">Study design</th><th rowspan="2">Setting</th><th rowspan="2">Study time frame</th><th rowspan="2">Follow-up duration</th><th rowspan="2">Study population</th><th rowspan="2">Type of intervention or exposure</th><th colspan="2">Diagnosis of peri-implant mucositis</th><th colspan="2">Diagnosis of peri-implantitis</th><th rowspan="2">Survival rate</th><th rowspan="2">Peri-implant mucosa inflammation (BOP)</th><th rowspan="2">Peri-implant probing pocket depth (mm)</th><th rowspan="2">Radiographic marginal bone level changes (mm)</th></tr><tr><th>Patient level</th><th>Implant level</th><th>Patient level</th><th>Implant level</th></tr></thead><tbody><tr><td rowspan="10">Pre-diabetes</td><td rowspan="10">Abduljabbar et al. (2017)</td><td rowspan="10">Case-control study</td><td rowspan="10">University setting Saudi Arabia</td><td rowspan="10">NR Mean F-UP: &gt;6 years</td><td rowspan="10">Patients with pre-diabetes or T2DM having received dental implants<br/>N = 130 (130)</td><td>N = 25 (36)</td><td>HbA1c: 4%-<br/>5% (no DM)<br/>N = 42 (42)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>15.2 ± 0.8</td><td>2.1 ± 0.1</td><td>1.6 ± 0.2</td></tr><tr><td>HbA1c: 8.1%-<br/>10%</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>28.5 (18.9-36)</td><td>3.1 (2.6-3.9)</td><td>2.4 (2.1-4.3)</td></tr><tr><td>N = 25 (39)</td><td>HbA1c: 5.7%-<br/>6.4%</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>36.4 ± 4.1</td><td>4 ± 0.4</td><td>3.4 ± 0.6</td></tr><tr><td>N = 45 (45)</td><td>HbA1c: 6.4%-<br/>≥6.5%</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>33.3 ± 3.5</td><td>4.2 ± 0.2</td><td>3.5 ± 0.4</td></tr><tr><td>N = 43 (43)</td><td>HbA1c: 4%-<br/>5%</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>13.6 (5.5-15.2)</td><td>1.3 (0.8-1.9)</td><td>0.7 (0-1.2)</td></tr><tr><td>N = 30 (39)</td><td>HbA1c: 5.7%-<br/>6.4%</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>24.7 (16.1-29.8)</td><td>2.7 (2.1-3.5)</td><td>2.1 (1.3-3)</td></tr><tr><td>N = 30 (42)</td><td>HbA1c: 6.4%-<br/>≥6.5%</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>31.4 (21.6-38.2)</td><td>3.2 (2.4-3.8)</td><td>2.5 (2-4.2)</td></tr><tr><td>N = 30 (46)</td><td>HbA1c: 4%-<br/>5%</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>0.22 ± 0.04 at 1 year</td><td>2.04 ± 0.21 at 1 year</td><td>0.43 ± 0.20 at 1 year</td></tr><tr><td>N = 40 (52)</td><td>HbA1c: 4%-<br/>5%</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>0.25 ± 0.05 at 2 year</td><td>2.11 ± 0.20 at 2 year</td><td>0.49 ± 0.18 at 2 year</td></tr><tr><td rowspan="3">Alrabiha et al. (2018)</td><td rowspan="3">Case-control study</td><td rowspan="3">Private referral dental clinic Saudi Arabia</td><td rowspan="3">NR F-UP: at least 36 months (Mean: &gt;63 months)</td><td rowspan="3">Patients with pre-diabetes or T2DM having received dental implants<br/>N = 90 (127)</td><td>N = 40 (52)</td><td>HbA1c: 4%-<br/>5%</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>0.21 ± 0.06 at 3 year</td><td>2.18 ± 0.18 at 3 year</td><td>0.51 ± 0.18 at 3 year</td></tr><tr><td>N = 41 (78)</td><td>HbA1c: 5.7%-<br/>6.4%</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>0.38 ± 0.07 at 1 year</td><td>2.13 ± 0.20 at 1 year</td><td>0.51 ± 0.14 at 1 year</td></tr><tr><td>N = 41 (78)</td><td>HbA1c: 5.7%-<br/>6.4%</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>0.39 ± 0.07 at 2 year</td><td>2.19 ± 0.21 at 2 year</td><td>0.54 ± 0.17 at 2 year</td></tr><tr><td>Alsahraf et al. (2019)</td><td>Case-control study</td><td>NR Saudi Arabia</td><td>2010-2016 F-UP: at least 36 months (Mean: &gt;63 s months)</td><td>Patients with pre-diabetes or T2DM having received narrow dental implants<br/>N = 119 (195)</td><td>N = 41 (78)</td><td>HbA1c: 4%-<br/>5%</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>0.42 ± 0.08 at 3 year</td><td>2.23 ± 0.21 at 3 year</td><td>0.59 ± 0.16 at 3 year</td></tr></tbody></table>

(Continues)
<table><caption>TABLE 1 (Continued)</caption><thead><tr><th rowspan="2">Reference</th><th rowspan="2">Study design</th><th rowspan="2">Setting</th><th rowspan="2">Study time frame</th><th rowspan="2">Study population</th><th rowspan="2">Type of intervention or exposure</th><th colspan="2">Diagnosis of peri-implant mucositis</th><th colspan="2">Diagnosis of peri-implantitis</th><th rowspan="2">Survival rate</th><th rowspan="2">Peri-implant mucosa inflammation (BOP)</th><th rowspan="2">Peri-implant probing pocket depth (mm)</th><th rowspan="2">Radiographic marginal bone level changes (mm)</th></tr><tr><th>Patient level</th><th>Implant level</th><th>Patient level</th><th>Implant level</th></tr></thead><tbody><tr><td rowspan="2">Mokeem et al. (2019)</td><td rowspan="2">Case-control study</td><td rowspan="2">NR<br/>Saudi Arabia</td><td rowspan="2">2016–2017<br/>Mean F-UP:<br/>&gt; 59 months</td><td rowspan="2">Patients with pre-diabetes or T2DM having received short dental implants<br/>N = 71 (111)</td><td>HbA1c:<br/>≥6.5%<br/>N = 38 (65)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>0.46 ± 0.06 at<br/>1 year<br/>0.49 ± 0.05 at<br/>2 year<br/>0.53 ± 0.07 at<br/>3 year</td><td>2.32 ± 0.18 at<br/>1 year<br/>2.35 ± 0.22 at<br/>2 year<br/>2.39 ± 0.18 at<br/>3 year</td><td>0.58 ± 0.15 at<br/>1 year<br/>0.62 ± 0.17 at<br/>2 year<br/>0.69 ± 0.17 at<br/>3 year</td></tr><tr><td>HbA1c: 4%–5%<br/>N = 25 (32)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>13.6 (5.5–15.2)</td><td>1.8 (0.7–2.1)</td><td>0.8 (0–1.3)</td></tr><tr><td rowspan="2"></td><td rowspan="2"></td><td rowspan="2"></td><td rowspan="2"></td><td rowspan="2"></td><td>HbA1c:<br/>5.7%–6.4%<br/>N = 22 (35)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>24.7 (16.1–29.8)</td><td>2.2 (2–3.1)</td><td>1.9 (1.1–2.8)</td></tr><tr><td>HbA1c: ≥6.5%<br/>N = 24 (44)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>32.9 (24.7–39.1)</td><td>3.3 (2.5–3.9)</td><td>2.7 (2.2–4.1)</td></tr></tbody></table>

Note: Significant differences between groups in the outcome measures are indicated in bold.

Abbreviations: BOP, bleeding on probing; DM, diabetes mellitus; F-UP, follow-up; HbA1c, glycated haemoglobin; NR, not reported; PPD, periodontal probing depth; T2DM, type-2 diabetes mellitus.
<table><caption>TABLE 1 (Continued)</caption><thead><tr><th rowspan="2">Reference</th><th rowspan="2">Study design</th><th rowspan="2">Setting</th><th rowspan="2">Study time frame</th><th rowspan="2">Study population</th><th rowspan="2">Type of intervention or exposure</th><th colspan="2">Diagnosis of peri-implant mucositis</th><th colspan="2">Diagnosis of peri-implantitis</th><th rowspan="2">Survival rate</th><th rowspan="2">Peri-implant mucosa inflammation (BOP)</th><th rowspan="2">Peri-implant probing pocket depth (mm)</th><th rowspan="2">Radiographic marginal bone level changes (mm)</th></tr><tr><th>Patient level</th><th>Implant level</th><th>Patient level</th><th>Implant level</th></tr></thead><tbody><tr><td rowspan="2">Mokeem et al. (2019)</td><td rowspan="2">Case-control study</td><td rowspan="2">NR<br/>Saudi Arabia</td><td rowspan="2">2016–2017<br/>Mean F-UP:<br/>&gt; 59 months</td><td rowspan="2">Patients with pre-diabetes or T2DM having received short dental implants<br/>N = 71 (111)</td><td>HbA1c:<br/>≥6.5%<br/>N = 38 (65)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>0.46 ± 0.06 at<br/>1 year<br/>0.49 ± 0.05 at<br/>2 year<br/>0.53 ± 0.07 at<br/>3 year</td><td>2.32 ± 0.18 at<br/>1 year<br/>2.35 ± 0.22 at<br/>2 year<br/>2.39 ± 0.18 at<br/>3 year</td><td>0.58 ± 0.15 at<br/>1 year<br/>0.62 ± 0.17 at<br/>2 year<br/>0.69 ± 0.17 at<br/>3 year</td></tr><tr><td>HbA1c: 4%–5%<br/>N = 25 (32)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>13.6 (5.5–15.2)</td><td>1.8 (0.7–2.1)</td><td>0.8 (0–1.3)</td></tr><tr><td rowspan="2"></td><td rowspan="2"></td><td rowspan="2"></td><td rowspan="2"></td><td rowspan="2"></td><td>HbA1c:<br/>5.7%–6.4%<br/>N = 22 (35)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>24.7 (16.1–29.8)</td><td>2.2 (2–3.1)</td><td>1.9 (1.1–2.8)</td></tr><tr><td>HbA1c:<br/>≥6.5%<br/>N = 24 (44)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>32.9 (24.7–39.1)</td><td>3.3 (2.5–3.9)</td><td>2.7 (2.2–4.1)</td></tr></tbody></table>

Note: Significant differences between groups in the outcome measures are indicated in bold.

Abbreviations: BOP, bleeding on probing; DM, diabetes mellitus; F-UP, follow-up; HbA1c, glycated haemoglobin; NR, not reported; PPD, periodontal probing depth; T2DM, type-2 diabetes mellitus.
(a) **Diagnosis of peri-implantitis:** comparison between good and poor glycemic control (GC) in type-2 diabetes patients (analysis at the implant level)

<figure><img src="image_4.png" /></figure>

(b) **Probing pocket depth (PPD):** Mean difference between good and poor glycemic control (GC) in type-2 diabetes (analysis at the implant level)

<figure><img src="image_5.png" /></figure>

(c) **Bleeding on probing (BOP):** Mean difference between good and poor glycemic control (GC) in type-2 diabetes patients (analysis at the implant level)

<figure><img src="image_6.png" /></figure>

(d) **Marginal bone level (MBL):** Mean difference between good and poor glycemic control (GC) in type-2 diabetes patients (analysis at the implant level)

<figure><img src="image_7.png" /><figcaption>**FIGURE 3** Forest plots for the impact of glycemic control on peri-implant diseases, peri-implant probing depth, bleeding on probing, and marginal bone level.</figcaption></figure>

differences between former smokers, e-cigarette users, waterpipe smokers, and current smokers. The former smoker category showed less peri-implant mucosal inflammation, lower PPD, and lower MBL changes compared to the other categories. Pro-inflammatory marker

levels, including MMP-9 (ArRejaie et al., 2019), IL-1β (M. A. AlQahtani et al., 2018; ArRejaie et al., 2019), IL-6 (M. A. AlQahtani et al., 2018), and TNF-α (M. A. AlQahtani et al., 2018), were found to be higher in the peri-implant sulcular fluid of current smokers than in that of e-cigarette users.
(a) **Diagnosis of peri-implantitis:** comparison between good and poor glycemic control (GC) in type-2 diabetes patients (analysis at the implant level)

<figure><img src="image_4.png" /></figure>

(b) **Probing pocket depth (PPD):** Mean difference between good and poor glycemic control (GC) in type-2 diabetes (analysis at the implant level)

<figure><img src="image_5.png" /></figure>

(c) **Bleeding on probing (BOP):** Mean difference between good and poor glycemic control (GC) in type-2 diabetes patients (analysis at the implant level)

<figure><img src="image_6.png" /></figure>

(d) **Marginal bone level (MBL):** Mean difference between good and poor glycemic control (GC) in type-2 diabetes patients (analysis at the implant level)

<figure><img src="image_7.png" /><figcaption>**FIGURE 3** Forest plots for the impact of glycemic control on peri-implant diseases, peri-implant probing depth, bleeding on probing, and marginal bone level.</figcaption></figure>

differences between former smokers, e-cigarette users, waterpipe smokers, and current smokers. The former smoker category showed less peri-implant mucosal inflammation, lower PPD, and lower MBL changes compared to the other categories. Pro-inflammatory marker

levels, including MMP-9 (ArRejaie et al., 2019), IL-1β (M. A. AlQahtani et al., 2018; ArRejaie et al., 2019), IL-6 (M. A. AlQahtani et al., 2018), and TNF-α (M. A. AlQahtani et al., 2018), were found to be higher in the peri-implant sulcular fluid of current smokers than in that of e-cigarette users.
<table><caption>TABLE 2 Characteristics and outcomes of the selected studies analysing the impact of smoking cessation strategies on the prevention of peri-implant diseases.</caption><thead><tr><th rowspan="2">Reference</th><th rowspan="2">Study design</th><th rowspan="2">Country</th><th rowspan="2">Setting</th><th rowspan="2">Study time frame</th><th rowspan="2">Follow-up duration</th><th rowspan="2">Total no. patients (no. of implants)</th><th rowspan="2">Type of intervention or exposure</th><th colspan="2">Diagnosis of peri-implant mucositis</th><th colspan="2">Diagnosis of peri-implantitis</th><th rowspan="2">Peri-implant probing pocket depth (mm)</th><th rowspan="2">Radiographic marginal bone level changes (mm)</th></tr><tr><th>No. of patients (no. of implants)</th><th>Patient level</th><th>Implant level</th><th>Patient level</th><th>Implant level</th><th>Survival rate</th></tr></thead><tbody><tr><td rowspan="10">AlQahtani et al. (2018)</td><td rowspan="10">Case-control study</td><td rowspan="10">NR</td><td rowspan="10">NR</td><td rowspan="10">NR</td><td rowspan="10">NR</td><td rowspan="10">Otherwise systemically healthy adult patients requiring at least 1 dental implant</td><td rowspan="10">Current smokers<br/>N = 40 (71)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>16.7 ± 3.9</td><td>PPD ≥ 4 mm<br/>7.8% ± 1.2</td><td>3.6 ± 0.5</td></tr><tr><td>Waterpipe smokers</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>18.4 ± 2.5</td><td>PPD ≥ 4 mm<br/>7% ± 1.1</td><td>3.2 ± 0.6</td></tr><tr><td>e-cigarette users</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>23.3 ± 5.1</td><td>PPD ≥ 4 mm<br/>5.3% ± 1.5</td><td>1.9 ± 0.9</td></tr><tr><td>Never smokers</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>38.9 ± 19.6</td><td>PPD ≥ 4 mm<br/>4.4% ± 0.6</td><td>0.9 ± 0.3</td></tr><tr><td>N = 40 (55)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Current smokers</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>18.4 ± 4.8</td><td>PPD ≥ 4 mm<br/>23.8% ± 2.7</td><td>2.3 ± 1.2</td></tr><tr><td>N = 32 (59)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>e-cigarette users</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>14.7 ± 5.3</td><td>PPD ≥ 4 mm<br/>15.9% ± 1.4</td><td>1.4 ± 0.9</td></tr><tr><td>N = 31 (49)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Never smokers</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>39.8 ± 18.1</td><td>PPD ≥ 4 mm<br/>4.5% ± 0.7</td><td>0.9 ± 0.3</td></tr><tr><td>N = 32 (51)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="10">AlQahtani et al. (2019)</td><td rowspan="10">Case-control study</td><td rowspan="10">NR</td><td rowspan="10">NR</td><td rowspan="10">NR</td><td rowspan="10">Young smoker patients requiring dental implants</td><td rowspan="10">Current smokers<br/>N = 35 (35)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>6.8 ± 1.2</td><td>4.3 ± 0.2</td><td>NR</td></tr><tr><td>Waterpipe smokers</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>7.9 ± 1.8</td><td>4.4 ± 0.5</td><td>NR</td></tr><tr><td>N = 33 (33)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>e-cigarette users</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>6.6 ± 1.3</td><td>3.2 ± 0.3</td><td>NR</td></tr><tr><td>N = 34 (34)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Never smokers</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>19.8 ± 1.3</td><td>0.8 ± 0.1</td><td>NR</td></tr><tr><td>N = 35 (35)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Current smokers</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>42.8 ± 23.4</td><td>PPD ≥ 5 mm<br/>33.2 ± 15.9</td><td>NR</td></tr><tr><td>N = 72 (149)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Former smokers</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>53.5 ± 30.2</td><td>PPD ≥ 5 mm<br/>28.5 ± 11.8</td><td>NR</td></tr><tr><td>N = 66 (140)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>
<table><caption>TABLE 2 Characteristics and outcomes of the selected studies analysing the impact of smoking cessation strategies on the prevention of peri-implant diseases.</caption><thead><tr><th rowspan="2">Reference</th><th rowspan="2">Study design</th><th rowspan="2">Country</th><th rowspan="2">Setting</th><th rowspan="2">Study time frame</th><th rowspan="2">Follow-up duration</th><th rowspan="2">Total no. patients (no. of implants)</th><th rowspan="2">Type of intervention or exposure</th><th colspan="2">Diagnosis of peri-implant mucositis</th><th colspan="2">Diagnosis of peri-implantitis</th><th rowspan="2">Peri-implant probing pocket depth (mm)</th><th rowspan="2">Radiographic marginal bone level changes (mm)</th></tr><tr><th>No. of patients (no. of implants)</th><th>Patient level</th><th>Implant level</th><th>Patient level</th><th>Implant level</th><th>Survival rate</th></tr></thead><tbody><tr><td rowspan="10">AlQahtani et al. (2018)</td><td rowspan="10">Case-control study</td><td rowspan="10">NR</td><td rowspan="10">NR</td><td rowspan="10">NR</td><td rowspan="10">NR</td><td rowspan="10">NR</td><td>Current smokers</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>16.7 ± 3.9</td><td>PPD ≥ 4 mm 7.8% ± 1.2</td><td>3.6 ± 0.5</td></tr><tr><td>N = 40 (71)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Waterpipe smokers</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>18.4 ± 2.5</td><td>PPD ≥ 4 mm 7% ± 1.1</td><td>3.2 ± 0.6</td></tr><tr><td>N = 40 (65)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>e-cigarette users</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>23.3 ± 5.1</td><td>PPD ≥ 4 mm 5.3% ± 1.5</td><td>1.9 ± 0.9</td></tr><tr><td>N = 40 (62)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Never smokers</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>38.9 ± 19.6</td><td>PPD ≥ 4 mm 4.4% ± 0.6</td><td>0.9 ± 0.3</td></tr><tr><td>N = 40 (55)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="10">ArRejaie et al. (2019)</td><td rowspan="10">Case-control study</td><td rowspan="10">University Setting Saudi Arabia</td><td rowspan="10">2016–2017 F-UP: at least 36 months (Mean F-UP &gt;47.2 months)</td><td rowspan="10">Otherwise systemically healthy adult patients requiring dental implants</td><td rowspan="10">N = 95 (159)</td><td>Current smokers</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>18.4 ± 4.8</td><td>PPD ≥ 4 mm 23.8% ± 2.7</td><td>2.3 ± 1.2</td></tr><tr><td>N = 32 (59)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>e-cigarette users</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>14.7 ± 5.3</td><td>PPD ≥ 4 mm 15.9% ± 1.4</td><td>1.4 ± 0.9</td></tr><tr><td>N = 31 (49)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Never smokers</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>39.8 ± 18.1</td><td>PPD ≥ 4 mm 4.5% ± 0.7</td><td>0.9 ± 0.3</td></tr><tr><td>N = 32 (51)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="10">AlQahtani et al. (2019)</td><td rowspan="10">Case-control study</td><td rowspan="10">NR</td><td rowspan="10">NR</td><td rowspan="10">NR</td><td rowspan="10">NR</td><td rowspan="10">NR</td><td>Current smokers</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>6.8 ± 1.2</td><td>4.3 ± 0.2</td><td>NR</td></tr><tr><td>N = 35 (35)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Waterpipe smokers</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>7.9 ± 1.8</td><td>4.4 ± 0.5</td><td>NR</td></tr><tr><td>N = 33 (33)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>e-cigarette users</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>6.6 ± 1.3</td><td>3.2 ± 0.3</td><td>NR</td></tr><tr><td>N = 34 (34)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Never smokers</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>19.8 ± 1.3</td><td>0.8 ± 0.1</td><td>NR</td></tr><tr><td>N = 35 (35)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="10">Costa et al. (2022)</td><td rowspan="10">Cohort study</td><td rowspan="10">University setting (3 Public Health Centres) Brazil</td><td rowspan="10">2008–2019 F-UP: at least 5 years</td><td rowspan="10">Patients receiving dental implants</td><td rowspan="10">N = 350 (769)</td><td>Current smokers</td><td>35/72 (48.6%)</td><td>NR</td><td>22/72 (30.5%)</td><td>NR</td><td>NR</td><td>42.8 ± 23.4</td><td>PPD ≥ 5 mm 33.2 ± 15.9</td><td>NR</td></tr><tr><td>N = 72 (149)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Former smokers</td><td>29/66 (43.9%)</td><td>NR</td><td>13/66 (19.7%)</td><td>NR</td><td>NR</td><td>53.5 ± 30.2</td><td>PPD ≥ 5 mm 28.5 ± 11.8</td><td>NR</td></tr><tr><td>N = 66 (140)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>
<table><caption>TABLE 2 (Continued)</caption><thead><tr><th rowspan="2">Reference</th><th rowspan="2">Study design</th><th rowspan="2">Setting</th><th rowspan="2">Study time frame</th><th rowspan="2">Study population</th><th rowspan="2">Type of intervention or exposure</th><th rowspan="2">No. of patients (no. of implants)</th><th rowspan="2">Diagnosis of peri-implant mucositis</th><th colspan="3">Diagnosis of peri-implantitis</th><th rowspan="2">Peri-implant mucosa inflammation/ BOP</th><th rowspan="2">Peri-implant probing pocket depth (mm)</th><th rowspan="2">Radiographic marginal bone level changes (mm)</th></tr><tr><th>Patient level</th><th>Implant level</th><th>Patient level</th><th>Implant level</th><th>Survival rate</th></tr></thead><tbody><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>39/212 (18.4%)</td><td>NR</td><td>NR</td><td>56.4 ± 35.6</td><td>PPD ≥ 5 mm<br>26.3 ± 12.9</td><td></td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>90/212 (42.4%)</td><td>NR</td><td>NR</td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>Never smokers<br>N = 212 (480)</td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>

Note: Significant differences between groups in the outcome measures are indicated in bold.

Abbreviations: BOP, bleeding on probing; F-UP, follow-up; NR, not reported; PPD, periodontal probing depth.

### 3.2.3 | Supportive periodontal/peri-implant care

To assess the efficacy of SPC and different protocols of SPC, 13 observational studies and 1 RCT were found. Overall, nine studies (64.2%) were conducted in private practice settings, most of the time in specialist centres in periodontology or implant dentistry (Tables 3 and S3). Two articles reported different outcomes on the same study population (M. Roccuzzo et al., 2010, 2012), and another two articles reported outcomes of the same study population at different follow-up intervals, at 10 (M. Roccuzzo et al., 2014) and 20 years (A. Roccuzzo et al., 2022). Twelve studies compared patients regularly attending the recommended SPC versus not attending or attending SPC visits irregularly (Aguirre-Zorzano et al., 2013; Alhakeem et al., 2022; Ferreira et al., 2006; Frisch et al., 2020; Hu et al., 2020; Monje et al., 2017; Rinke et al., 2011; A. Roccuzzo et al., 2022; M. Roccuzzo et al., 2010, 2012, 2014; Roman-Torres et al., 2019); one RCT compared four different SPC protocols over a 1-year study period (Ziebolz et al., 2017), and one study compared patients with or without deep residual periodontal pockets during the SPC (Cho-Yan Lee et al., 2012).

Pooled data analyses showed that patients attending SPC regularly were at significantly lower risk of presenting with PIDs (including both peri-implant mucositis and peri-implantitis) (OR = 0.42; 95% CI: 0.24-0.75; *p* = .003; *I*²: 57%) during study follow-ups. This was also observed for the specific diagnosis of peri-implantitis, both at the patient level (OR = 0.45; 95% CI: 0.30-0.68; *p* = .0002; *I*²: 51%) and at the implant level (OR = 0.26; 95% CI: 0.15-0.46; *p* < .0001; *I*²: 21%). No significant between-group difference was observed for the diagnosis of peri-implant mucositis (Figures 4 and S1). In a sensitivity analysis performed excluding those studies that included patients with a history of periodontitis, dental implants under regular SPC showed an OR = 0.23 (95% CI: 0.08-0.64; *p* = .005; *I*²: 0%) of developing peri-implantitis compared to dental implants with no SPC (based on two studies; Frisch et al., 2020; Roman-Torres et al., 2019).

Regarding dental implants as the statistical unit, those submitted to regular SPC showed lower PPD (MD: -0.48 mm; 95% CI: -0.67 to -0.29; *p* < .0001; *I*²: 32%) and a reduced risk of presenting with an MBL >2 mm (OR: 0.4; 95% CI: 0.25-0.66; *p* = .0003; *I*²: 73%) (Figure 5). Irregular SPC was associated with a 3.76 times increased risk of implant failure (95% CI: 1.50-9.45; *p* = .005; *I*²: 0%) compared to regular SPC. All studies reporting dental implant survival evaluated study samples that included a proportion of patients with a history of periodontitis. Globally, the estimated mean implant survival was 99.3% (95% CI: 98.6%-100%) in the regular SPC group (based on 564 implants) and 97.8% (95% CI: 95.6%-99.9%) in the irregular SPC group (based on 454 implants). Reasons for implant loss were not specified in the selected studies, but they occurred after implant loading (Frisch et al., 2020; Hu et al., 2020; A. Roccuzzo et al., 2022; M. Roccuzzo et al., 2014).

Only one study evaluated the impact of residual deep periodontal pockets at the remaining natural teeth on the occurrence of PIDs (Cho-Yan Lee et al., 2012). When comparing patients with a history of generalized moderate to severe periodontitis presenting with deep
<table><caption>TABLE 3 Characteristics and outcomes of the selected studies analysing the impact professional periodontal/peri-implant supportive care protocols/compliance on the prevention of peri-implant diseases.</caption><thead><tr><th rowspan="2">Variable</th><th rowspan="2">Study design</th><th rowspan="2">Setting</th><th rowspan="2">Study time frame</th><th rowspan="2">Follow-up duration</th><th rowspan="2">Study population</th><th rowspan="2">Type of intervention or exposure</th><th colspan="3">Diagnosis of peri-implant mucositis</th><th colspan="3">Diagnosis of peri-implantitis</th><th rowspan="2">Peri-implant mucosa inflammation/ BOP</th><th rowspan="2">Peri-implant probing pocket depth (mm)</th><th rowspan="2">Radiographic marginal bone level changes (mm)</th></tr><tr><th>No. of patients (no. of implants)</th><th>Patient level</th><th>Implant level</th><th>Patient level</th><th>Implant level</th><th>Survival rate</th></tr></thead><tbody><tr><td rowspan="3">Ferreira et al. (2006)</td><td rowspan="3">Cross-sectional study</td><td rowspan="3">University setting Brazil</td><td rowspan="3">NR</td><td rowspan="3">F-UP: at least 6 months- 5 years</td><td rowspan="3">Consecutive partially edentulous patients treated with dental implants (including 30 patients with periodontitis)<br/>N = 212 (578)</td><td>Regular supportive peri-implant therapy (≤6-month interval)<br/>N = 94 (NR)</td><td>58/94<br/>NR</td><td>8/94<br/>(61.7%)</td><td>NR</td><td>8/94<br/>(8.5%)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td>Irregular supportive peri-implant therapy (&gt;6-month interval)<br/>N = 118 (NR)</td><td>79/118<br/>NR</td><td>11/118<br/>(66.9%)</td><td>NR</td><td>11/118<br/>(9.3%)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td>Regular individually tailored supportive periodontal and peri-implant therapy<br/>N = 79 (NR)</td><td>NR</td><td>NR</td><td>21/79<br/>(26.6%)</td><td>NR</td><td>NR</td><td>NE</td><td>PHP: 12.5 ± 2.4<br/>mPCP: 23 ± 2.7<br/>sPCP: 27.2 ± 2.7</td><td>PHP: 3.1 ± 0.5 mPCP: 3.2 ± 0.6<br/>sPCP: 3.9 ± 0.8</td><td>MBL &gt; 3 mm: 12 patients (16.4%)</td></tr><tr><td rowspan="3">M. Rocuzzo et al. (2010, 2012)</td><td rowspan="3">Cohort study</td><td rowspan="3">Private specialist periodontics/ implantology practice Italy</td><td rowspan="3">1996-1998</td><td rowspan="3">F-UP: 10 years</td><td rowspan="3">Consecutive patients referred for dental implant therapy (including 80 patients with history of periodontitis)<br/>N = 112 (NR)</td><td>No supportive periodontal and peri-implant therapy<br/>N = 22 (NR)</td><td>NR</td><td>NR</td><td>9/22<br/>(40.9%)</td><td>NR</td><td>NR</td><td>NE</td><td>PHP: 11.4 ± 4.8<br/>mPCP: 50 ± 4.9<br/>sPCP: 52.1 ± 7.2</td><td>PHP: 3.0 ± 0.4 mPCP: 4.3 ± 1.2<br/>sPCP: 3.9 ± 0.7</td><td>MBL &gt; 3 mm: 11 patients (50%)</td></tr><tr><td>Regular supportive periodontal and peri-implant therapy (3 to 6-month interval)<br/>N = 58 (NR)</td><td>25/58<br/>NR</td><td>2/58<br/>(43.1%)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td>Irregular supportive periodontal and peri-implant therapy<br/>N = 31 (NR)</td><td>15/31<br/>NR</td><td>8/31<br/>(48.4%)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td rowspan="3">Rinke et al. (2011)</td><td rowspan="3">Case-control study</td><td rowspan="3">Private practice Germany</td><td rowspan="3">1999-2006</td><td rowspan="3">Mean F-UP: 68.2 months ±24.8</td><td rowspan="3">Consecutive patients referred for dental implant therapy (including patients with history of periodontitis)<br/>N = 89 (NR)</td><td>Residual deep (≥6 mm) periodontal pocket(s) assessed during an individually tailored supportive periodontal therapy<br/>N = 13 (23)</td><td>NR</td><td>NR</td><td>7/13<br/>(53.8%)</td><td>10/23 (43.5%)</td><td>NR</td><td>NR</td><td>3.18 ± 0.63</td><td>0.68 ± 1.08 MBL &gt; 2 mm: 26.1%</td></tr><tr><td>No residual pocket during an individually tailored supportive periodontal therapy<br/>N = 17 (33)</td><td>NR</td><td>NR</td><td>4/17<br/>(23.5%)</td><td>5/33 (15.2%)</td><td>NR</td><td>NR</td><td>2.67 ± 0.44</td><td>0.23 ± 0.84 MBL &gt; 2 mm: 6.1%</td></tr><tr><td>4-monthly supportive periodontal therapy<br/>N = 27 (123)</td><td>1/27<br/>(3.7%)</td><td>NR</td><td>5/27<br/>(18.5%)</td><td>NR</td><td>100%</td><td>NR</td><td>NR</td><td>0.16 ± 0.15</td></tr><tr><td rowspan="3">Aguirre-Zorzano et al. (2013)</td><td rowspan="3">Case-control study</td><td rowspan="3">University setting Spain</td><td rowspan="3">NR</td><td rowspan="3">F-UP: 1 year</td><td rowspan="3">Patients with a history of treated chronic periodontitis<br/>N = 49 (246)</td><td>No supportive periodontal therapy<br/>N = 22 (123)</td><td>NR</td><td>NR</td><td>5/22<br/>(22.7%)</td><td>NR</td><td>11/22<br/>(50%)</td><td>NR</td><td>NR</td><td>NR</td><td>0.62 ± 0.94</td></tr><tr><td>4-monthly supportive periodontal therapy<br/>N = 27 (123)</td><td>1/27<br/>(3.7%)</td><td>NR</td><td>5/27<br/>(18.5%)</td><td>NR</td><td>100%</td><td>NR</td><td>NR</td><td>0.16 ± 0.15</td></tr><tr><td>No supportive periodontal therapy<br/>N = 22 (123)</td><td>5/22<br/>(22.7%)</td><td>NR</td><td>11/22<br/>(50%)</td><td>NR</td><td>99.2%</td><td>NR</td><td>NR</td><td>0.62 ± 0.94</td></tr></tbody></table>
<table><caption>TABLE 3 Characteristics and outcomes of the selected studies analysing the impact professional periodontal/peri-implant supportive care protocols/compliance on the prevention of peri-implant diseases.</caption><thead><tr><th rowspan="2">Variable</th><th rowspan="2">Study design</th><th rowspan="2">Setting</th><th rowspan="2">Study time frame</th><th rowspan="2">Follow-up duration</th><th rowspan="2">Study population</th><th rowspan="2">Type of intervention or exposure</th><th colspan="3">Diagnosis of peri-implant mucositis</th><th colspan="3">Diagnosis of peri-implantitis</th><th rowspan="2">Peri-implant mucosa inflammation/ BOP</th><th rowspan="2">Peri-implant probing pocket depth (mm)</th><th rowspan="2">Radiographic marginal bone level changes (mm)</th></tr><tr><th>No. of patients (no. of implants)</th><th>Patient level</th><th>Implant level</th><th>Patient level</th><th>Implant level</th><th>Survival rate</th></tr></thead><tbody><tr><td rowspan="3">Ferreira et al. (2006)</td><td rowspan="3">Cross-sectional study</td><td rowspan="3">University setting Brazil</td><td rowspan="3">NR</td><td rowspan="3">F-UP: at least 6 months- 5 years</td><td rowspan="3">Consecutive partially edentulous patients treated with dental implants (including 30 patients with periodontitis)<br/>N = 212 (578)</td><td>Regular supportive peri-implant therapy (≤6-month interval)<br/>N = 94 (NR)</td><td>58/94<br/>NR</td><td>8/94<br/>(61.7%)</td><td>NR</td><td>8/94<br/>(8.5%)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td>Irregular supportive peri-implant therapy (&gt;6-month interval)<br/>N = 118 (NR)</td><td>79/118<br/>NR</td><td>11/118<br/>(66.9%)</td><td>NR</td><td>11/118<br/>(9.3%)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td>Regular individually tailored supportive periodontal and peri-implant therapy<br/>N = 79 (NR)</td><td>NR</td><td>21/79<br/>(26.6%)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>PHP: 12.5 ± 2.4<br/>mPCP: 23 ± 2.7<br/>sPCP: 27.2 ± 2.7</td><td>PHP: 3.1 ± 0.5 mPCP: 3.2 ± 0.6<br/>sPCP: 3.9 ± 0.8</td><td>MBL &gt; 3 mm: 12 patients (16.4%)</td></tr><tr><td rowspan="3">M. Rocuzzo et al. (2010, 2012)</td><td rowspan="3">Cohort study</td><td rowspan="3">Private specialist periodontics/ implantology practice Italy</td><td rowspan="3">1996-1998<br/>F-UP: 10 years</td><td rowspan="3">Consecutive patients referred for dental implant therapy (including 80 patients with history of periodontitis)<br/>N = 112 (NR)</td><td>No supportive periodontal and peri-implant therapy<br/>N = 22 (NR)</td><td>NR</td><td>NR</td><td>9/22<br/>(40.9%)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>PHP: 11.4 ± 4.8<br/>mPCP: 50 ± 4.9<br/>sPCP: 52.1 ± 7.2</td><td>PHP: 3.0 ± 0.4 mPCP: 4.3 ± 1.2<br/>sPCP: 3.9 ± 0.7</td><td>MBL &gt; 3 mm: 11 patients (50%)</td></tr><tr><td>Regular supportive periodontal and peri-implant therapy (3 to 6-month interval)<br/>N = 58 (NR)</td><td>25/58<br/>NR</td><td>2/58<br/>(3.5%)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td>Irregular supportive periodontal and peri-implant therapy<br/>N = 31 (NR)</td><td>15/31<br/>NR</td><td>8/31<br/>(48.4%)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td rowspan="3">Rinke et al. (2011)</td><td rowspan="3">Case-control study</td><td rowspan="3">Private practice Germany</td><td rowspan="3">1999-2006<br/>Mean F-UP: 68.2 months ±24.8</td><td rowspan="3">Consecutive patients referred for dental implant therapy (including patients with history of periodontitis)<br/>N = 89 (NR)</td><td>Residual deep (≥6 mm) periodontal pocket(s) assessed during an individually tailored supportive periodontal therapy<br/>N = 13 (23)</td><td>NR</td><td>NR</td><td>7/13<br/>(53.8%)</td><td>10/23 (43.5%)</td><td>NR</td><td>NR</td><td>NR</td><td>3.18 ± 0.63</td><td>0.68 ± 1.08 MBL &gt; 2 mm: 26.1%</td></tr><tr><td>No residual pocket during an individually tailored supportive periodontal therapy<br/>N = 17 (33)</td><td>NR</td><td>NR</td><td>4/17<br/>(23.5%)</td><td>5/33 (15.2%)</td><td>NR</td><td>NR</td><td>NR</td><td>2.67 ± 0.44</td><td>0.23 ± 0.84 MBL &gt; 2 mm: 6.1%</td></tr><tr><td>4-monthly supportive periodontal therapy<br/>N = 27 (123)</td><td>1/27<br/>(3.7%)</td><td>NR</td><td>5/27<br/>(18.5%)</td><td>NR</td><td>NR</td><td>100%</td><td>NR</td><td>NR</td><td>0.16 ± 0.15</td></tr><tr><td rowspan="3">Aguirre-Zorzano et al. (2013)</td><td rowspan="3">Case-control study</td><td rowspan="3">University setting Spain</td><td rowspan="3">NR<br/>F-UP: 1 year</td><td rowspan="3">Patients with a history of treated chronic periodontitis<br/>N = 49 (246)</td><td>No supportive periodontal therapy<br/>N = 22 (123)</td><td>NR</td><td>NR</td><td>5/22<br/>(22.7%)</td><td>NR</td><td>11/22<br/>(50%)</td><td>NR</td><td>NR</td><td>NR</td><td>0.62 ± 0.94</td></tr><tr><td>4-monthly supportive periodontal therapy<br/>N = 27 (123)</td><td>1/27<br/>(3.7%)</td><td>NR</td><td>5/27<br/>(18.5%)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td>No supportive periodontal therapy<br/>N = 22 (123)</td><td>5/22<br/>(22.7%)</td><td>NR</td><td>11/22<br/>(50%)</td><td>NR</td><td>NR</td><td>99.2%</td><td>NR</td><td>NR</td></tr></tbody></table>
<table><caption>TABLE 3 (Continued)</caption><thead><tr><th rowspan="2">Variable</th><th rowspan="2">Study design</th><th rowspan="2">Setting</th><th rowspan="2">Country</th><th rowspan="2">Study time frame</th><th rowspan="2">Follow-up duration</th><th rowspan="2">Total no. of patients (no. of implants)</th><th rowspan="2">Study population</th><th rowspan="2">Type of intervention or exposure</th><th colspan="2">Diagnosis of peri-implant mucositis</th><th colspan="3">Diagnosis of peri-implantitis</th><th rowspan="2">Survival rate</th><th rowspan="2">Peri-implant mucosa inflammation/ BOP</th><th rowspan="2">Peri-implant probing pocket depth (mm)</th><th rowspan="2">Radiographic marginal bone level</th><th rowspan="2">Radiographic changes (mm)</th></tr><tr><th>No. of patients (no. of implants)</th><th>Patient level</th><th>Implant level</th><th>Patient level</th><th>Implant level</th></tr></thead><tbody><tr><td rowspan="4">Monje et al. (2017)</td><td rowspan="4">Cross-sectional study</td><td rowspan="4">Private specialist periodontal practice Spain</td><td rowspan="4">2016-2017</td><td rowspan="4">Mean F-UP: 46.85 months ±5.8</td><td rowspan="4">Consecutive patients treated with dental implants for fixed prosthetic rehabilitation</td><td rowspan="4">N = 115 (206)</td><td>Regular</td><td>22.8%</td><td>19.3%</td><td>4.5%</td><td>2.4%</td><td>NE</td><td>NE</td><td>NE</td><td>NE</td><td>NE</td><td>NE</td></tr><tr><td>supportive peri-implant therapy</td><td>N = NR</td><td>NE</td><td>NE</td><td>26.3%</td><td>19%</td><td>NE</td><td>NE</td><td>NE</td><td>NE</td><td>NE</td></tr><tr><td>Erratic supportive peri-implant therapy</td><td>N = NR</td><td>NE</td><td>NE</td><td>14.3%</td><td>8.7%</td><td>NE</td><td>NE</td><td>NE</td><td>NE</td><td>NE</td></tr><tr><td>No supportive peri-implant therapy</td><td>N = NR</td><td>NE</td><td>NE</td><td>14.3%</td><td>8.7%</td><td>NE</td><td>NE</td><td>NE</td><td>NE</td><td>NE</td></tr><tr><td rowspan="10">Ziebolz et al. (2017)</td><td rowspan="10">Multicentre RCT</td><td rowspan="10">Private dental hygiene practice (12 centres) Germany</td><td rowspan="10">F-UP: 1 year</td><td rowspan="10"></td><td rowspan="10"></td><td rowspan="10">Partially and fully edentulous patients with at least one dental implant-supported restoration (including 49 patients with a history of moderate or severe periodontitis)</td><td rowspan="10">N = 62 (101)</td><td>3-monthly supportive peri-implant therapy with curette, sonic scaler, polishing with prophylaxis brush</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>100%</td><td>5.9%</td><td>2.21 ± 1.32</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td>N = 17 (24)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>100%</td><td>13.3%</td><td>2.31 ± 1.54</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td>3-monthly supportive peri-implant therapy with curette, air polishing, polishing with prophylaxis brush</td><td>N = 15 (26)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>100%</td><td>6.3%</td><td>2.23 ± 1.28</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td>3-monthly supportive peri-implant therapy with curette, sonic scaler, polishing with prophylaxis brush, CHX varnish</td><td>N = 16 (30)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>100%</td><td>7.1%</td><td>2.05 ± 1.32</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td>3-monthly supportive peri-implant therapy with curette, air polishing, polishing with prophylaxis brush, CHX varnish</td><td>N = 14 (21)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>1/264 (0.4%)</td><td>NR</td><td>81/264 (31%)</td><td>2.72 ± 0.69</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td>Regular supportive peri-implant therapy (at least once/year for 7 years)</td><td>N = 44 (264)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>1/264 (0.4%)</td><td>NR</td><td>81/264 (31%)</td><td>2.72 ± 0.69</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td>No supportive peri-implant therapy (over the 7-year study period)</td><td>N = 22 (132)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>1/132 (0.75%)</td><td>NR</td><td>121/132 (92%)</td><td>3.10 ± 0.83</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td>Roman-Torres et al. (2019)</td><td>Case-control study</td><td>University setting Brazil</td><td>Dental implant placement in 2007</td><td>Consecutive patients rehabilitated with dental implant-supported overdentures</td><td>N = 66 (396)</td><td>F-UP: 7 years</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>
<table><caption>TABLE 3 (Continued)</caption><thead><tr><th>Variable</th><th>Study design</th><th>Setting</th><th>Study time frame</th><th>Follow-up duration</th><th>Study population</th><th>Type of intervention or exposure</th><th colspan="2">Diagnosis of peri-implant mucositis</th><th colspan="2">Diagnosis of peri-implantitis</th><th colspan="2">Survival rate</th><th colspan="2">Peri-implant mucosa inflammation/ BOP</th><th colspan="2">Peri-implant probing pocket depth (mm)</th><th>Radiographic marginal bone level</th><th>Radiographic changes (mm)</th></tr><tr><th>Reference</th><th></th><th>Country</th><th></th><th></th><th></th><th>No. of patients (no. of implants)</th><th>Patient level</th><th>Implant level</th><th>Patient level</th><th>Implant level</th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th></tr></thead><tbody><tr><td>Monje et al. (2017)</td><td>Cross-sectional study</td><td>Private specialist periodontal practice Spain</td><td>2016-2017<br>Mean F-UP: 46.85 months ±5.8</td><td>Consecutive patients treated with dental implants for fixed prosthetic rehabilitation<br>N = 115 (206)</td><td>Regular<br>supportive peri-implant therapy<br>N = NR</td><td></td><td>22.8%</td><td>19.3%</td><td>4.5%</td><td>2.4%</td><td>NE</td><td>NE</td><td>NE</td><td>NE</td><td>NE</td><td>NE</td><td>NE</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>Erratic supportive peri-implant therapy<br>N = NR</td><td>NE</td><td>NE</td><td>26.3%</td><td>19%</td><td>NE</td><td>NE</td><td>NE</td><td>NE</td><td>NE</td><td>NE</td><td>NE</td><td>NE</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>No supportive peri-implant therapy<br>N = NR</td><td>NE</td><td>NE</td><td>14.3%</td><td>8.7%</td><td>NE</td><td>NE</td><td>NE</td><td>NE</td><td>NE</td><td>NE</td><td>NE</td><td>NE</td></tr><tr><td>Ziebolz et al. (2017)</td><td>Multicentre RCT</td><td>Private dental hygiene practice (12 centres)<br>Germany</td><td>F-UP: 1 year</td><td></td><td>Partially and fully edentulous patients with at least one dental implant-supported restoration (including 49 patients with a history of moderate or severe periodontitis)<br>N = 62 (101)</td><td>3-monthly supportive peri-implant therapy with curette, sonic scaler, polishing with prophylaxis brush<br>N = 17 (24)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>100%</td><td>5.9%</td><td>2.21 ± 1.32</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>3-monthly supportive peri-implant therapy with curette, air polishing, polishing with prophylaxis brush<br>N = 15 (26)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>100%</td><td>13.3%</td><td>2.31 ± 1.54</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>3-monthly supportive peri-implant therapy with curette, sonic scaler, polishing with prophylaxis brush, CHX varnish<br>N = 16 (30)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>100%</td><td>6.3%</td><td>2.23 ± 1.28</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>3-monthly supportive peri-implant therapy with curette, air polishing, polishing with prophylaxis brush, CHX varnish<br>N = 14 (21)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>100%</td><td>7.1%</td><td>2.05 ± 1.32</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td>Roman-Torres et al. (2019)</td><td>Case-control study</td><td>University setting Brazil</td><td>Dental implant placement in 2007<br>F-UP: 7 years</td><td>Consecutive patients rehabilitated with dental implant-supported overdentures<br>N = 66 (396)</td><td>Regular supportive peri-implant therapy (at least once/year for 7 years)<br>N = 44 (264)</td><td>NR</td><td>NR</td><td>NR</td><td>1/264 (0.4%)</td><td>NR</td><td>81/264 (31%)</td><td>2.72 ± 0.69</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>No supportive peri-implant therapy (over the 7-year study period)<br>N = 22 (132)</td><td>NR</td><td>NR</td><td>NR</td><td>1/132 (0.75%)</td><td>NR</td><td>121/132 (92%)</td><td>3.10 ± 0.83</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td></tr></tbody></table>
<table><caption>TABLE 3 (Continued)</caption><thead><tr><th rowspan="2">Variable</th><th rowspan="2">Study design</th><th rowspan="2">Setting</th><th rowspan="2">Country</th><th rowspan="2">Study time frame</th><th rowspan="2">Follow-up duration</th><th rowspan="2">Total no. of patients (no. of implants)</th><th rowspan="2">Study population</th><th rowspan="2">Type of intervention or exposure</th><th colspan="2">Diagnosis of peri-implant mucositis</th><th colspan="2">Diagnosis of peri-implantitis</th><th rowspan="2">Survival rate</th><th rowspan="2">Peri-implant mucosa inflammation/ BOP</th><th rowspan="2">Peri-implant probing pocket depth (mm)</th><th rowspan="2">Radiographic marginal bone level changes (mm)</th></tr><tr><th>Patient level</th><th>Implant level</th><th>Patient level</th><th>Implant level</th></tr></thead><tbody><tr><td>Frisch et al. (2020)</td><td>Case-control study</td><td>Private practice</td><td>Germany</td><td>2006–2007 form implant placement</td><td>2012–2014 for outcomes assessment</td><td>Mean F-UP: 7.76 years ±3.07</td><td>Patients who were provided with implant-supported prostheses of all types included in a supportive implant therapy program</td><td>Regular supportive peri-implant care (at least once/year)<br/>N = 48 (98)</td><td>NR</td><td>30/98 (30.6%)</td><td>NR</td><td>4/98 (4.1%)</td><td>100%</td><td>NR</td><td>3.76 ± 0.86</td><td>1.02 ± 0.85<br/>MBL > 2 mm: 21.4%</td></tr><tr><td>Hu et al. (2020)</td><td>Case-control study</td><td>Hospital setting</td><td>Singapore</td><td>2005–2012<br/>Mean F-UP: 6.8 years (range: 4.5 11 years)</td><td>Consecutive patients receiving dental implants (including 77 patients with a history of treated periodontitis)</td><td>N = 200 (284)</td><td>Regular supportive peri-implant care (at least once/year)<br/>N = 100 (150)</td><td>NR</td><td>NR</td><td>6/100 (6%)</td><td>6/150 (4%)</td><td>98.7%</td><td>NR</td><td>NR</td><td>0.19<br/>MBL ≥ 2 mm: 0.7%</td></tr><tr><td>Alhakeem et al. (2022)</td><td>Case-control study</td><td>University setting</td><td>Iran</td><td>2010–2012<br/>Mean F-UP: 7.3 ± 1.4 years</td><td>Consecutive patients receiving dental implants (including 47 patients with a history of severe periodontitis)</td><td>N = 88 (186)</td><td>No supportive peri-implant care<br/>N = 100 (134)</td><td>NR</td><td>NR</td><td>20/100 (20%)</td><td>23/134 (17.2%)</td><td>97.8%</td><td>NR</td><td>NR</td><td>0.63<br/>MBL ≥ 2 mm: 9.7%</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>Regular supportive care<br/>N = 76 (165)</td><td>NR</td><td>NR</td><td>NR</td><td>17/165 (26.1%)</td><td>100%</td><td>137/165</td><td>PPD ≥ 4 mm<br/>24/165 (14.5%)</td><td>MBL ≥ 3 mm: 25/165</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>Irregular supportive care<br/>N = 12 (21)</td><td>NR</td><td>NR</td><td>NR</td><td>1/21 (4.8%)</td><td>100%</td><td>4/21</td><td>PPD ≥ 4 mm<br/>1/21 (4.8%)</td><td>MBL ≥ 3 mm: 1/21</td></tr></tbody></table>

Note: Significant differences between groups in the outcome measures are indicated in bold.

Abbreviations: BOP, bleeding on probing; F-UP, follow-up; MBL, marginal bone level; mPCP, moderately periodontally compromised patients; NE, not estimable; NR, not reported; PHP, periodontally healthy patients; PPD, pocket probing depth; sPCP, severely periodontally compromised patients.
<table><caption>TABLE 3 (Continued)</caption><thead><tr><th rowspan="2">Variable</th><th rowspan="2">Study design</th><th rowspan="2">Setting</th><th rowspan="2">Country</th><th rowspan="2">Study time frame</th><th rowspan="2">Follow-up duration</th><th rowspan="2">Total no. of patients (no. of implants)</th><th rowspan="2">Study population</th><th rowspan="2">Type of intervention or exposure</th><th colspan="2">Diagnosis of peri-implant mucositis</th><th colspan="2">Diagnosis of peri-implantitis</th><th rowspan="2">Survival rate</th><th rowspan="2">Peri-implant mucosa inflammation/ BOP</th><th rowspan="2">Peri-implant probing pocket depth (mm)</th><th rowspan="2">Radiographic marginal bone level changes (mm)</th></tr><tr><th>Patient level</th><th>Implant level</th><th>Patient level</th><th>Implant level</th></tr></thead><tbody><tr><td>Frisch et al. (2020)</td><td>Case-control study</td><td>Private practice</td><td>Germany</td><td>2006–2007 form implant placement</td><td>2012–2014 for outcomes assessment</td><td>Mean F-UP: 7.76 years ±3.07</td><td>Patients who were provided with implant-supported prostheses of all types included in a supportive implant therapy program</td><td>Regular supportive peri-implant care (at least once/year)<br/>N = 48 (98)</td><td>NR</td><td>30/98 (30.6%)</td><td>NR</td><td>4/98 (4.1%)</td><td>100%</td><td>NR</td><td>3.76 ± 0.86</td><td>1.02 ± 0.85<br/>MBL > 2 mm: 21.4%</td></tr><tr><td>Hu et al. (2020)</td><td>Case-control study</td><td>Hospital setting</td><td>Singapore</td><td>2005–2012<br/>Mean F-UP: 6.8 years (range: 4.5–11 years)</td><td>Consecutive patients receiving dental implants (including 77 patients with a history of treated periodontitis)</td><td>N = 200 (284)</td><td>Regular supportive peri-implant care (at least once/year)<br/>N = 100 (150)</td><td>NR</td><td>NR</td><td>6/100 (6%)</td><td>6/150 (4%)</td><td>98.7%</td><td>NR</td><td>NR</td><td>0.19<br/>MBL ≥ 2 mm: 0.7%</td></tr><tr><td>Alhakeem et al. (2022)</td><td>Case-control study</td><td>University setting</td><td>Iran</td><td>2010–2012<br/>Mean F-UP: 7.3 ± 1.4 years</td><td>Consecutive patients receiving dental implants (including 47 patients with a history of severe periodontitis)</td><td>N = 88 (186)</td><td>No supportive peri-implant care<br/>N = 100 (134)</td><td>NR</td><td>NR</td><td>20/100 (20%)</td><td>23/134 (17.2%)</td><td>97.8%</td><td>NR</td><td>NR</td><td>0.63<br/>MBL ≥ 2 mm: 9.7%</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>Regular supportive care<br/>N = 76 (165)</td><td>NR</td><td>NR</td><td>NR</td><td>17/165 (26.1%)</td><td>100%</td><td>137/165</td><td>PPD ≥ 4 mm<br/>24/165 (14.5%)</td><td>MBL ≥ 3 mm: 25/165</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>Irregular supportive care<br/>N = 12 (21)</td><td>NR</td><td>NR</td><td>NR</td><td>1/21 (4.8%)</td><td>100%</td><td>4/21</td><td>PPD ≥ 4 mm<br/>1/21 (4.8%)</td><td>MBL ≥ 3 mm: 1/21</td></tr></tbody></table>

Note: Significant differences between groups in the outcome measures are indicated in bold.

Abbreviations: BOP, bleeding on probing; F-UP, follow-up; MBL, marginal bone level; mPCP, moderately periodontally compromised patients; NE, not estimable; NR, not reported; PHP, periodontally healthy patients; PPD, pocket probing depth; sPCP, severely periodontally compromised patients.
(a) Diagnosis of peri-implant disease (including both peri-implant mucositis and peri-implantitis): comparison between regular and irregular SPC (analysis at the patient level)

<figure><img src="image_8.png" /></figure>

(b) Diagnosis of peri-implant mucositis: comparison between regular and irregular SPC (analysis at the patient level)

<figure><img src="image_9.png" /></figure>

(c) Diagnosis of peri-implantitis: comparison between regular and irregular SPC (analysis at the patient level)

<figure><img src="image_10.png" /><figcaption>**FIGURE 4** Forest plots for the impact of regular versus irregular supportive periodontal/peri-implant care on peri-implant diseases.</figcaption></figure>

residual pockets (≥6 mm) during the SPC with patients with a history of generalized moderate to severe periodontitis but without residual deep pockets, a significantly higher occurrence of peri-implantitis (3.5% vs. 15.2%, implant-level analysis) was observed when deep residual pockets were present.

The only RCT included in this subsection about SPC (Ziebolz et al., 2017) compared four different SPC protocols, including a 3-monthly SPC with curette, with sonic scaler or air polishing, and with or without chlorhexidine varnish application. No significant differences were noted between the groups in term of PPD, BOP, and survival at 1 year.

### 3.2.4 | Peri-implant soft tissue width and thickness

Overall, 17 studies were selected, including 9 RCTs, 4 NRCTs, 3 case-control studies, and 1 cohort study (Tables 4 and S3). Six studies (Buyukozdemir Askin et al., 2015; Kikuchi et al., 2022; Oh et al., 2017, 2020; M. Roccuzzo et al., 2016; Zheng et al., 2021) compared peri-implant tissue health parameters between sites with PIKM deficiency receiving a free gingival graft (FGG) to increase PIKM width versus no intervention. When pooling all studies together, meta-analyses showed a non-significant difference in PPD between the PIKM-augmented and non-augmented sites but a significantly lower clinical
(a) Diagnosis of peri-implant disease (including both peri-implant mucositis and peri-implantitis): comparison between regular and irregular SPC (analysis at the patient level)

<figure><img src="image_8.png" /></figure>

(b) Diagnosis of peri-implant mucositis: comparison between regular and irregular SPC (analysis at the patient level)

<figure><img src="image_9.png" /></figure>

(c) Diagnosis of peri-implantitis: comparison between regular and irregular SPC (analysis at the patient level)

<figure><img src="image_10.png" /><figcaption>**FIGURE 4** Forest plots for the impact of regular versus irregular supportive periodontal/peri-implant care on peri-implant diseases.</figcaption></figure>

residual pockets (≥6 mm) during the SPC with patients with a history of generalized moderate to severe periodontitis but without residual deep pockets, a significantly higher occurrence of peri-implantitis (3.5% vs. 15.2%, implant-level analysis) was observed when deep residual pockets were present.

The only RCT included in this subsection about SPC (Ziebolz et al., 2017) compared four different SPC protocols, including a 3-monthly SPC with curette, with sonic scaler or air polishing, and with or without chlorhexidine varnish application. No significant differences were noted between the groups in term of PPD, BOP, and survival at 1 year.

### 3.2.4 | Peri-implant soft tissue width and thickness

Overall, 17 studies were selected, including 9 RCTs, 4 NRCTs, 3 case-control studies, and 1 cohort study (Tables 4 and S3). Six studies (Buyukozdemir Askin et al., 2015; Kikuchi et al., 2022; Oh et al., 2017, 2020; M. Roccuzzo et al., 2016; Zheng et al., 2021) compared peri-implant tissue health parameters between sites with PIKM deficiency receiving a free gingival graft (FGG) to increase PIKM width versus no intervention. When pooling all studies together, meta-analyses showed a non-significant difference in PPD between the PIKM-augmented and non-augmented sites but a significantly lower clinical
(a) Probing pocket depth (PPD): comparison between regular and irregular SPC (analysis at the implant level)

<figure><img src="image_11.png" /></figure>

(b) Marginal bone level (MBL) > 2 mm: comparison between regular and irregular SPC (analysis at the implant level)

<figure><img src="image_12.png" /></figure>

(c) Implant survival: comparison between regular and irregular SPC (analysis at the implant level)

<figure><img src="image_13.png" /><figcaption>**FIGURE 5** Forest plots for the impact of regular versus irregular supportive periodontal/peri-implant care on peri-implant probing depth, bleeding on probing, and marginal bone level.</figcaption></figure>

soft tissue inflammation index (BOP/GI) (SMD = -1.18; 95% CI: -1.85 to -0.51; *p* = .0006; *I*²: 69%) around the dental implants receiving FGG to augment PIKM (Figure 6). Concerning the mean MBL, based on data from four studies, a significant difference in favour of PIKM-augmented sites (SMD: -0.25; 95% CI: -0.45 to -0.05; *p* = .01; *I*²: 62%) was also noted. When excluding from pooled data analysis cohort and case-control studies, the results were consistent with no statistical heterogeneity. No difference in PPD (SMD: -0.25; 95% CI: -0.63 to -0.13; *p* = .20; *I*²: 0%; based on 107 implants) but a significant difference in peri-implant mucosa inflammation (SMD: -1.5; 95% CI: -1.93 to -1.06; *p* < .0001; *I*²: 0%; based on 107 implants) and MBL changes (SMD: -0.33; 95% CI: -0.55 to -0.11; *p* = .003; *I*²: 0%; based on two studies, 66 implants) was noted between PIKM-augmented sites versus non-augmented sites. Only one study (Buyukozdemir Askin et al., 2015) evaluated inflammatory biomarkers in peri-implant sulcular fluid, namely the IL-1β

concentration, which was not different between PIKM-augmented and non-augmented sites.

Three studies compared peri-implant tissue health parameters between sites with thin peri-implant soft tissues receiving and not receiving a soft tissue augmentation procedure (by connective tissue graft [CTG] or allogenic membrane) to increase tissue thickness (Bienz et al., 2017; Hosseini et al., 2020; Linkevicius et al., 2015). Concerning the clinical parameters defining peri-implant health, no significant differences were reported for peri-implant mucosa inflammation (BOP or mBI), PPD, and MBL. For this latter parameter, pooled data analysis based on two studies including 107 implants (Hosseini et al., 2020; Linkevicius et al., 2015) showed a non-significant difference between CTG-augmented sites versus non-augmented sites (MD: -0.75 [-2.18 to 0.68], *p* = .32; *I*²: 99%). They all reported a survival rate of 100% (follow-up duration 1-5 years).
(a) Probing pocket depth (PPD): comparison between regular and irregular SPC (analysis at the implant level)

<figure><img src="image_11.png" /></figure>

(b) Marginal bone level (MBL) > 2 mm: comparison between regular and irregular SPC (analysis at the implant level)

<figure><img src="image_12.png" /></figure>

(c) Implant survival: comparison between regular and irregular SPC (analysis at the implant level)

<figure><img src="image_13.png" /><figcaption>**FIGURE 5** Forest plots for the impact of regular versus irregular supportive periodontal/peri-implant care on peri-implant probing depth, bleeding on probing, and marginal bone level.</figcaption></figure>

soft tissue inflammation index (BOP/GI) (SMD = -1.18; 95% CI: -1.85 to -0.51; *p* = .0006; *I*²: 69%) around the dental implants receiving FGG to augment PIKM (Figure 6). Concerning the mean MBL, based on data from four studies, a significant difference in favour of PIKM-augmented sites (SMD: -0.25; 95% CI: -0.45 to -0.05; *p* = .01; *I*²: 62%) was also noted. When excluding from pooled data analysis cohort and case-control studies, the results were consistent with no statistical heterogeneity. No difference in PPD (SMD: -0.25; 95% CI: -0.63 to -0.13; *p* = .20; *I*²: 0%; based on 107 implants) but a significant difference in peri-implant mucosa inflammation (SMD: -1.5; 95% CI: -1.93 to -1.06; *p* < .0001; *I*²: 0%; based on 107 implants) and MBL changes (SMD: -0.33; 95% CI: -0.55 to -0.11; *p* = .003; *I*²: 0%; based on two studies, 66 implants) was noted between PIKM-augmented sites versus non-augmented sites. Only one study (Buyukozdemir Askin et al., 2015) evaluated inflammatory biomarkers in peri-implant sulcular fluid, namely the IL-1β

concentration, which was not different between PIKM-augmented and non-augmented sites.

Three studies compared peri-implant tissue health parameters between sites with thin peri-implant soft tissues receiving and not receiving a soft tissue augmentation procedure (by connective tissue graft [CTG] or allogenic membrane) to increase tissue thickness (Bienz et al., 2017; Hosseini et al., 2020; Linkevicius et al., 2015). Concerning the clinical parameters defining peri-implant health, no significant differences were reported for peri-implant mucosa inflammation (BOP or mBI), PPD, and MBL. For this latter parameter, pooled data analysis based on two studies including 107 implants (Hosseini et al., 2020; Linkevicius et al., 2015) showed a non-significant difference between CTG-augmented sites versus non-augmented sites (MD: -0.75 [-2.18 to 0.68], *p* = .32; *I*²: 99%). They all reported a survival rate of 100% (follow-up duration 1-5 years).
<table><caption>TABLE 4 Characteristics and outcomes of the selected studies analysing the impact of peri-implant soft tissue augmentation on peri-implant health and diseases.</caption><thead><tr><th rowspan="2">Reference</th><th rowspan="2">Study design</th><th rowspan="2">Country</th><th rowspan="2">Study time frame</th><th rowspan="2">Follow-up duration</th><th rowspan="2">Study population</th><th rowspan="2">Type of intervention or exposure</th><th rowspan="2">No. patients (no. of implants)</th><th rowspan="2">Surgical procedure</th><th colspan="2">Diagnosis of peri-implant mucositis</th><th colspan="2">Diagnosis of peri-implantitis</th><th rowspan="2">Survival rate</th><th rowspan="2">Peri-implant mucosal inflammation/ BOP</th><th rowspan="2">Peri-implant probing depth (mm)</th><th rowspan="2">Radiographic marginal bone level changes (mm)</th></tr><tr><th>Patient level</th><th>Implant level</th><th>Patient level</th><th>Implant level</th></tr></thead><tbody><tr><td>Peri-implant keratinized mucosa (PIKM) augmentation: Comparison between augmented and non-augmented sites</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Buyukozdemir<br/>Askin et al.<br/>(2015)</td><td>NRCT</td><td>University setting<br/>Turkey</td><td>NR<br/>F-UP:<br/>6 months</td><td>Systemically and periodontally healthy patients requiring dental implants<br/>N = 18 (60)</td><td></td><td>Inadequate PIKM width<br/>(≤2 mm) treated with FGG<br/>N = NR (20)</td><td></td><td>Surgery performed at least 1 year after implant loading</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>0.65 ± 0.42<br/>(GI)<br/>30% (BOP)</td><td>2.29 ± 0.5</td><td>0.55 ± 0.39</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td>Inadequate PIKM width<br/>(≤2 mm) treated with SPC only<br/>N = NR (20)</td><td></td><td></td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>1.31 ± 0.33<br/>(GI)<br/>95% (BOP)</td><td>2.29 ± 0.65</td><td>0.81 ± 0.61</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td>Adequate PIKM width<br/>(>2 mm)<br/>N = NR (20)</td><td></td><td></td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>0.56 ± 0.44<br/>(GI)<br/>25% (BOP)</td><td>2.43 ± 0.81</td><td>0.72 ± 0.49</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td>Implants surrounded by PIKM<br/>N = 63 (63)</td><td></td><td></td><td>NR</td><td>NR</td><td>8/63<br/>(12.7%)</td><td>8/63<br/>(12.7%)</td><td>NR</td><td>23.4 ± 18.4</td><td>3.13 ± 0.59</td><td>0.34 ± 0.38</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td>Implants surrounded by alveolar mucosa without additional FGG<br/>N = 24 (24)</td><td></td><td>FGG was performed during the SPC whenever the patient reported soreness and insufficient plaque control</td><td>NR</td><td>NR</td><td>18/35<br/>(51.4%)<br/>NR</td><td>18/35<br/>(51.4%)</td><td>NR</td><td>33.3 ± 25.2</td><td>2.77 ± 0.70</td><td>0.50 ± 0.38</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td>Implants placed in alveolar mucosa with additional FGG<br/>N = 11 (11)</td><td></td><td></td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>27.3 ± 26.1</td><td>2.95 ± 0.80</td><td>0.56 ± 0.39</td></tr><tr><td>Rocuzzo et al. Cohort study<br/>(2016)</td><td>Specialized private practice<br/>Italy</td><td>1998-2002<br/>F-UP: 10 years</td><td>NR<br/>F-UP:<br/>6 months</td><td>Consecutive patients requiring dental implant in the posterior mandible (including 74 patients with history of moderate periodontitis)<br/>N = 98 (98)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td>FGG</td><td></td><td>Surgery performed at least 6 months after implant loading</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>100%</td><td>0.8 ± 1.1</td><td>3 ± 1<br/>(mesial)<br/>2.9 ± 1.1<br/>(distal)</td><td>At 18-month F-UP:<br/>0 ± 0.2 (mesial)<br/>0.06 ± 0.3 (distal)<br/>At 48-month F-UP:<br/>0 ± 0.5 (mesial)<br/>0 ± 0.5 (distal)</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td>At 48 months<br/>N = 28 (41)<br/>At 48 months:<br/>N = 23 (32)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Oh<br/>et al. (2017, 2020)</td><td>RCT</td><td>University setting<br/>USA</td><td>2012-2014<br/>F-UP:<br/>18 months<br/>(2017)<br/>And<br/>48 months<br/>(2020)</td><td>Patients with history of moderate periodontitis and with PIKM <2 mm on the facial side of a dental implant<br/>N = 14 (21)<br/>At 48 months<br/>N = 11 (18)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td>Oral prophylaxis only<br/>N = 14 (20)<br/>At 48 months<br/>N = 7 (8)</td><td></td><td></td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>100%</td><td>2.1 ± 0.9</td><td>3.7 ± 1.5<br/>(mesial)<br/>3.5 ± 1.4<br/>(distal)<br/>0.38 ± 0.3<br/>(mesial)<br/>0.25 ± 0.3 (distal)<br/>At 48-month F-UP:<br/>0.3 ± 0.4 (mesial)</td><td>At 18-month F-UP:<br/>0 ± 0.2 (mesial)<br/>0.06 ± 0.3 (distal)<br/>At 48-month F-UP:<br/>0 ± 0.5 (mesial)<br/>0 ± 0.5 (distal)</td></tr></tbody></table>
<table><caption>TABLE 4 Characteristics and outcomes of the selected studies analysing the impact of peri-implant soft tissue augmentation on peri-implant health and diseases.</caption><thead><tr><th rowspan="2">Reference</th><th rowspan="2">Study design</th><th rowspan="2">Country</th><th rowspan="2">Study time frame</th><th rowspan="2">Follow-up duration</th><th rowspan="2">Study population</th><th rowspan="2">Type of intervention or exposure</th><th rowspan="2">No. patients (no. of implants)</th><th rowspan="2">Surgical procedure</th><th colspan="2">Diagnosis of peri-implant mucositis</th><th colspan="2">Diagnosis of peri-implantitis</th><th rowspan="2">Survival rate</th><th rowspan="2">Peri-implant mucosal inflammation/ BOP</th><th rowspan="2">Peri-implant probing depth (mm)</th><th rowspan="2">Radiographic marginal bone level changes (mm)</th></tr><tr><th>Patient level</th><th>Implant level</th><th>Patient level</th><th>Implant level</th></tr></thead><tbody><tr><td>Peri-implant keratinized mucosa (PIKM) augmentation: Comparison between augmented and non-augmented sites</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Buyukozdemir<br/>Askin et al.<br/>(2015)</td><td>NRCT</td><td>University setting<br/>Turkey</td><td>NR<br/>F-UP:<br/>6 months</td><td>Systemically and periodontally healthy patients requiring dental implants<br/>N = 18 (60)</td><td></td><td>Inadequate PIKM width<br/>(≤2 mm) treated with FGG<br/>N = NR (20)</td><td></td><td>Surgery performed at least 1 year after implant loading</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>0.65 ± 0.42<br/>(GI)<br/>30% (BOP)</td><td>2.29 ± 0.5</td><td>0.55 ± 0.39</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td>Inadequate PIKM width<br/>(≤2 mm) treated with SPC only<br/>N = NR (20)</td><td></td><td></td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>1.31 ± 0.33<br/>(GI)<br/>95% (BOP)</td><td>2.29 ± 0.65</td><td>0.81 ± 0.61</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td>Adequate PIKM width<br/>(>2 mm)<br/>N = NR (20)</td><td></td><td></td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>0.56 ± 0.44<br/>(GI)<br/>25% (BOP)</td><td>2.43 ± 0.81</td><td>0.72 ± 0.49</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td>Implants surrounded by PIKM<br/>N = 63 (63)</td><td></td><td></td><td>NR</td><td>NR</td><td>8/63<br/>(12.7%)</td><td>8/63<br/>(12.7%)</td><td>NR</td><td>23.4 ± 18.4</td><td>3.13 ± 0.59</td><td>0.34 ± 0.38</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td>Implants surrounded by alveolar mucosa without additional FGG<br/>N = 24 (24)</td><td></td><td>FGG was performed during the SPC whenever the patient reported soreness and insufficient plaque control</td><td>NR</td><td>NR</td><td>18/35<br/>(51.4%)<br/>NR</td><td>18/35<br/>(51.4%)</td><td>NR</td><td>33.3 ± 25.2</td><td>2.77 ± 0.70</td><td>0.50 ± 0.38</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td>Implants placed in alveolar mucosa with additional FGG<br/>N = 11 (11)</td><td></td><td></td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>27.3 ± 26.1</td><td>2.95 ± 0.80</td><td>0.56 ± 0.39</td></tr><tr><td>Rocuzzo et al. Cohort study<br/>(2016)</td><td>Specialized private practice<br/>Italy</td><td>1998-2002<br/>F-UP: 10 years</td><td>NR<br/>F-UP:<br/>6 months</td><td>Consecutive patients requiring dental implant in the posterior mandible (including 74 patients with history of moderate periodontitis)<br/>N = 98 (98)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td>FGG</td><td></td><td>Surgery performed at least 6 months after implant loading</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>100%</td><td>0.8 ± 1.1</td><td>3 ± 1<br/>(mesial)<br/>2.9 ± 1.1<br/>(distal)</td><td>At 18-month F-UP:<br/>0 ± 0.2 (mesial)<br/>0.06 ± 0.3 (distal)<br/>At 48-month F-UP:<br/>0 ± 0.5 (mesial)<br/>0 ± 0.5 (distal)</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td>At 48 months<br/>N = 28 (41)<br/>At 48 months:<br/>N = 23 (32)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Oh<br/>et al. (2017, 2020)</td><td>RCT</td><td>University setting<br/>USA</td><td>2012-2014<br/>F-UP:<br/>18 months<br/>(2017)<br/>And<br/>48 months<br/>(2020)</td><td>Patients with history of moderate periodontitis and with PIKM <2 mm on the facial side of a dental implant<br/>N = 14 (21)<br/>At 48 months<br/>N = 11 (18)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td>Oral prophylaxis only<br/>N = 14 (20)<br/>At 48 months<br/>N = 7 (8)</td><td></td><td></td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>100%</td><td>2.1 ± 0.9</td><td>3.7 ± 1.5<br/>(mesial)<br/>3.5 ± 1.4<br/>(distal)<br/>0.38 ± 0.3<br/>(mesial)<br/>0.25 ± 0.3 (distal)<br/>At 48-month F-UP:<br/>0.3 ± 0.4 (mesial)</td><td>At 18-month F-UP:<br/>0 ± 0.2 (mesial)<br/>0.06 ± 0.3 (distal)<br/>At 48-month F-UP:<br/>0 ± 0.5 (mesial)<br/>0 ± 0.5 (distal)</td></tr></tbody></table>
<table><caption>TABLE 4 (Continued)</caption><thead><tr><th rowspan="2">Study design</th><th rowspan="2">Setting</th><th rowspan="2">Study time frame</th><th rowspan="2">Study population</th><th rowspan="2">Type of intervention or exposure</th><th rowspan="2">No. of patients (no. of implants)</th><th rowspan="2">Surgical procedure</th><th colspan="2">Diagnosis of peri-implant mucositis</th><th colspan="2">Diagnosis of peri-implantitis</th><th colspan="2">Peri-implant mucosal</th><th colspan="2">Peri-implant probing depth</th><th rowspan="2">Radiographic marginal bone level changes (mm)</th></tr><tr><th>Patient level</th><th>Implant level</th><th>Patient level</th><th>Implant level</th><th>Survival rate</th><th>BOP</th><th>Peri-implant mucosal inflammation/ BOP</th><th>Peri-implant probing depth</th></tr></thead><tbody><tr><td>Reference</td><td>Country</td><td>Follow-up duration</td><td>Total no. patients (no. of implants)</td><td></td><td>N = 10<sup>°</sup> (10)</td><td>Surgery performed 2-3 months after immediately placed implants if thin phenotype</td><td>NR</td><td>0%</td><td>NR</td><td>1/23 (4.3%)</td><td>100%</td><td>mBI 0.55% mBI 1.12.5% mBI 2.0%</td><td>NR</td><td>0.12 ± 0.33</td><td></td></tr><tr><td>Reference</td><td>Study design</td><td>Setting</td><td>Study time frame</td><td>Study population</td><td>No. of patients (no. of implants)</td><td>Type of intervention or exposure</td><td>No. of patients (no. of implants)</td><td>Surgical procedure</td><td>Diagnosis of peri-implant mucositis</td><td>Diagnosis of peri-implantitis</td><td>Patient level</td><td>Patient level</td><td>Survival rate</td><td>Peri-implant mucosal inflammation/ BOP</td><td>Radiographic marginal bone level changes (mm)</td></tr><tr><td rowspan="2">Peri-implant soft tissue augmentation: Comparison between different techniques</td><td>Lorenzo et al. (2012)</td><td>RCT</td><td>University setting and private practice (2 centres) Spain</td><td>2008-2009 F-UP: 6 months</td><td>Systemically healthy patients with at least 1 dental implant with minimal or no PIKM (&lt;1 mm) N = 24 (24)</td><td></td><td>Xenogenic collagen matrix N = 12 (12)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>0.2 ± 0.63 (GI) 1.6 ± 0.52</td><td></td><td></td><td></td></tr><tr><td>Frisch et al. (2015)</td><td>Case-control study</td><td>Specialized private practice Germany</td><td>1993-2011 Mean F-UP: 12.1 years ±4.9</td><td>Patients with a width &lt;1 mm of PIKM at a minimum of one dental implant N = 60 (105)</td><td></td><td>Free CTG N = 12 (12)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>0.33 ± 0.65 (GI) 2.08 ± 1.08</td><td></td><td></td><td></td></tr><tr><td rowspan="2">Reference</td><td>Study design</td><td>Setting</td><td>Study time frame</td><td>Follow-up duration</td><td>Total no. patients (no. of implants)</td><td></td><td>FGG N = NR (32)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>96.61% NR</td><td>3.84 ± 1.10</td><td></td><td></td><td></td></tr><tr><td>Reference</td><td>Study design</td><td>Setting</td><td>Study time frame</td><td>Study population</td><td>No. of patients (no. of implants)</td><td>CTG N = NR (27)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>1/32 (3.1%) 1/27 (3.7%)</td><td>3.78 ± 0.88</td><td></td><td></td><td></td></tr><tr><td rowspan="2">Reference</td><td>Study design</td><td>Setting</td><td>Study time frame</td><td>Follow-up duration</td><td>Total no. patients (no. of implants)</td><td></td><td>No intervention N = 30 (46)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>0 (0%) 100%</td><td>3.86 ± 0.89</td><td></td><td></td><td></td></tr><tr><td>Reference</td><td>Study design</td><td>Setting</td><td>Study time frame</td><td>Study population</td><td>No. of patients (no. of implants)</td><td>Acellular Dermal Matrix Allografts N = 18 (36)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>0.29 ± 0.33</td><td>3.22 ± 0.15</td><td></td><td></td><td></td></tr><tr><td rowspan="2">Reference</td><td>Study design</td><td>Setting</td><td>Study time frame</td><td>Follow-up duration</td><td>Total no. patients (no. of implants)</td><td></td><td>FGG N = 18 (36)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>0.19 ± 0.17</td><td>3.33 ± 0.27</td><td></td><td></td><td></td></tr><tr><td>Reference</td><td>Study design</td><td>Setting</td><td>Study time frame</td><td>Study population</td><td>No. of patients (no. of implants)</td><td>Xenogeneic collagen matrix N = 28 (28)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>100%</td><td>2.8 ± 0.2</td><td>0.2 ± 0.4</td><td></td><td></td><td></td></tr><tr><td>Reference</td><td>Study design</td><td>Setting</td><td>Study time frame</td><td>Follow-up duration</td><td>Total no. patients (no. of implants)</td><td></td><td>CTG N = 30 (30)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>100%</td><td>2.9 ± 0.3</td><td>0.2 ± 0.4</td><td></td><td></td><td></td></tr></tbody></table>
<table><caption>TABLE 4 (Continued)</caption><thead><tr><th rowspan="2">Reference</th><th rowspan="2">Study design</th><th rowspan="2">Country</th><th rowspan="2">Setting</th><th rowspan="2">Study time frame</th><th rowspan="2">Follow-up duration</th><th rowspan="2">Study population</th><th rowspan="2">Type of intervention or exposure</th><th colspan="2">Diagnosis of peri-implantitis</th><th colspan="2">Diagnosis of peri-implantitis mucositis</th><th colspan="2">Diagnosis of peri-implantitis</th><th colspan="2">Radiographic marginal bone level changes (mm)</th></tr><tr><th>No. of patients (no. of implants)</th><th>Surgical procedure</th><th>Patient level</th><th>Implant level</th><th>Patient level</th><th>Implant level</th><th>Survival rate</th><th>Peri-implant mucosal inflammation/ BOP</th><th>Peri-implant probing depth (mm)</th></tr></thead><tbody><tr><td rowspan="2">Vellis et al. (2019)</td><td rowspan="2">NRCT (split mouth)</td><td rowspan="2">University setting USA</td><td rowspan="2">NR</td><td rowspan="2">F-UP; 6 months</td><td rowspan="2">Patients with controlateral dental implants with &lt;1 mm of PIKM at the facial site N = 30 (60)</td><td rowspan="2">Xenogenic collagen matrix N = 30 (30)</td><td rowspan="2">Performed on loaded implants on the same day for both sides</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td>FGG N = 30 (30)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td rowspan="2">Thoma et al. (2020, 2022)</td><td rowspan="2">RCT</td><td rowspan="2">University setting Switzerland</td><td rowspan="2">2012-2018 F-UP; 3 (2020) and 5 years (2022)</td><td rowspan="2">Patients in the need of soft tissue augmentation around dental implants N = 17 (17)</td><td rowspan="2">Xenogenic collagen matrix N = 8 (8)</td><td rowspan="2">Performed after implant placement</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td>CTG N = 9 (9)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td rowspan="2">Huang et al. (2021)</td><td rowspan="2">RCT</td><td rowspan="2">University setting China</td><td rowspan="2">2017-2020 F-UP; 6 months</td><td rowspan="2">Patients presenting with at least 1 site with PIKM ≤2 mm in the edentulous region after dental implant surgery N = 26 (38)</td><td rowspan="2">Xenogenic collagen matrix N = 12 (18)</td><td rowspan="2">NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td>FGG N = 13 (19)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td></tr></tbody></table>

Note: Significant differences between groups in the outcome measures are indicated in bold.

Abbreviations: APF, apically positioned flap; BOP, bleeding on probing; CTG, connective tissue graft; FGG, free gingival graft; F-UP, follow-up; GI, gingival index; KT, keratinized tissue; mBI, modified bleeding index; NR, not reported; NRCT, non-randomized controlled trial; PPD, pocket probing depth; PSM, propensity score matching; RCT, randomized controlled trial; SPC, supportive periodontal/peri-implant care.

<footnote>*6 split-mouth.</footnote>
<table><caption>TABLE 4 (Continued)</caption><thead><tr><th rowspan="2">Reference</th><th rowspan="2">Study design</th><th rowspan="2">Country</th><th rowspan="2">Setting</th><th rowspan="2">Study time frame</th><th rowspan="2">Follow-up duration</th><th rowspan="2">Study population</th><th rowspan="2">Type of intervention or exposure</th><th colspan="2">Diagnosis of peri-implantitis</th><th colspan="2">Diagnosis of peri-implantitis mucositis</th><th colspan="2">Diagnosis of peri-implantitis</th><th colspan="2">Radiographic marginal bone level changes (mm)</th></tr><tr><th>No. of patients (no. of implants)</th><th>Surgical procedure</th><th>Patient level</th><th>Implant level</th><th>Patient level</th><th>Implant level</th><th>Survival rate</th><th>Peri-implant mucosal inflammation/ BOP</th><th>Peri-implant probing depth (mm)</th></tr></thead><tbody><tr><td rowspan="2">Vellis et al. (2019)</td><td rowspan="2">NRCT (split mouth)</td><td rowspan="2">University setting</td><td rowspan="2">USA</td><td rowspan="2">NR</td><td rowspan="2">F-UP; 6 months</td><td rowspan="2">Patients with controlateral dental implants with &lt;1 mm of PIKM at the facial site</td><td rowspan="2">Xenogenic collagen matrix</td><td rowspan="2">Performed on loaded implants on the same day for both sides</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>100%</td><td>0.23 ± 0.72</td><td>1.56 ± 0.67</td><td>NR</td></tr><tr><td>N = 30 (30)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>100%</td><td>0.13 ± 0.57</td><td>1.56 ± 0.62</td><td>NR</td></tr><tr><td rowspan="4">Thoma et al. (2020, 2022)</td><td rowspan="4">RCT</td><td rowspan="4">University setting Switzerland</td><td rowspan="4">NR</td><td rowspan="4">NR</td><td rowspan="4">NR</td><td rowspan="4">NR</td><td rowspan="4">NR</td><td rowspan="4">NR</td><td rowspan="4">NR</td><td rowspan="4">NR</td><td rowspan="4">NR</td><td rowspan="4">NR</td><td rowspan="4">NR</td><td rowspan="4">NR</td><td rowspan="4">NR</td></tr><tr><td rowspan="2">NR = 30 (30)</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td></tr><tr><td>At 3 years: 0.5 ± 1</td></tr><tr><td rowspan="2">NR = 30 (30)</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td></tr><tr><td>At 5 years: 0.4 ± 1.1</td></tr><tr><td rowspan="2">NR = 30 (30)</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td></tr><tr><td>At 5 years: 0.47 ± 0.6</td></tr><tr><td rowspan="4">Huang et al. (2021)</td><td rowspan="4">RCT</td><td rowspan="4">University setting China</td><td rowspan="4">NR</td><td rowspan="4">NR</td><td rowspan="4">NR</td><td rowspan="4">NR</td><td rowspan="4">NR</td><td rowspan="4">NR</td><td rowspan="4">NR</td><td rowspan="4">NR</td><td rowspan="4">NR</td><td rowspan="4">NR</td><td rowspan="4">NR</td><td rowspan="4">NR</td><td rowspan="4">NR</td><td rowspan="4">NR</td><td rowspan="4">NR</td></tr><tr><td rowspan="2">NR = 12 (18)</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td></tr><tr><td>At 3 years: 0.4 ± 0.3</td></tr><tr><td rowspan="2">NR = 12 (18)</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td></tr><tr><td>At 5 years: 0.47 ± 0.6</td></tr><tr><td rowspan="2">NR = 12 (18)</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td></tr><tr><td>At 3 years: 0.5 ± 1</td></tr><tr><td rowspan="2">NR = 12 (18)</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td></tr><tr><td>At 5 years: 0.4 ± 1.1</td></tr><tr><td rowspan="2">NR = 12 (18)</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td></tr><tr><td>At 3 years: 0.4 ± 0.3</td></tr><tr><td rowspan="2">NR = 12 (18)</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td></tr><tr><td>At 5 years: 0.47 ± 0.6</td></tr><tr><td rowspan="2">NR = 12 (18)</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td></tr><tr><td>At 3 years: 0.5 ± 1</td></tr><tr><td rowspan="2">NR = 12 (18)</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td></tr><tr><td>At 5 years: 0.4 ± 1.1</td></tr><tr><td rowspan="2">NR = 12 (18)</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td></tr><tr><td>At 3 years: 0.4 ± 0.3</td></tr><tr><td rowspan="2">NR = 12 (18)</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td></tr><tr><td>At 5 years: 0.47 ± 0.6</td></tr><tr><td rowspan="2">NR = 12 (18)</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td></tr><tr><td>At 3 years: 0.5 ± 1</td></tr><tr><td rowspan="2">NR = 12 (18)</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td></tr><tr><td>At 5 years: 0.4 ± 1.1</td></tr><tr><td rowspan="2">NR = 12 (18)</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td></tr><tr><td>At 3 years: 0.4 ± 0.3</td></tr><tr><td rowspan="2">NR = 12 (18)</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td></tr><tr><td>At 5 years: 0.47 ± 0.6</td></tr></tbody></table>

Note: Significant differences between groups in the outcome measures are indicated in bold.

Abbreviations: APF, apically positioned flap; BOP, bleeding on probing; CTG, connective tissue graft; FGG, free gingival graft; F-UP, follow-up; GI, gingival index; KT, keratinized tissue; mBI, modified bleeding index; NR, not reported; NRCT, non-randomized controlled trial; PPD, pocket probing depth; PSM, propensity score matching; RCT, randomized controlled trial; SPC, supportive periodontal/peri-implant care.

<footnote>*6 split-mouth.</footnote>
(a) Probing pocket depth (PPD): comparison between implant sites with augmented and non-augmented PIKM

<figure><img src="image_14.png" /></figure>

(b) Bleeding on probing: comparison between implant sites with augmented and non-augmented PIKM

<figure><img src="image_15.png" /></figure>

(c) Marginal bone level: comparison between implant sites with augmented and non-augmented PIKM

<figure><img src="image_16.png" /><figcaption>**FIGURE 6** Forest plots for impact of peri-implant keratinized mucosa augmentation versus no augmentation on peri-implant probing depth, bleeding on probing, and marginal bone level.</figcaption></figure>

Overall, only three studies reported the occurrence of PIDs (Frisch et al., 2015; Hosseini et al., 2020; M. Roccuzzo et al., 2016). The first study defined peri-implantitis as the presence of BOP, PPD ≥5 mm, and a radiographic bone loss ≥3.5 mm (Frisch et al., 2015). During a mean follow-up of 12 years, three groups receiving FGG or CTG or no intervention were compared. No statistical differences were found between groups. The second study, a 10-year prospective cohort, observed a significantly higher rate of PIDs for dental implants with PIKM deficiency compared to implants surrounded by PIKM (51.4% vs. 12.7%; *p* < .0001) (Roccuzzo et al., 2016). The authors also reported a significantly lower soreness for implants surrounded by PIKM or placed in the alveolar mucosa receiving FGG compared to implants surrounded by alveolar mucosa and not receiving FGG (M. Roccuzzo et al., 2016). The third study was a controlled clinical trial with a small sample size (19 patients) and observed a 4.3% rate of peri-implantitis in the control group compared to 0% in the test group receiving CTG (partial split-mouth design) (Hosseini et al., 2020). Meta-analysis was performed by pooling together two studies comparing CTG versus no intervention (Frisch et al., 2015; Hosseini et al., 2020), and including 37 implants in CTG-augmented sites versus

69 implants in non-augmented sites. It showed no significant difference between the two groups for the rate of incident peri-implantitis (OR = 1.97; 95% CI: 0.2–19.72; *p* = .56; *I*²: 0%).

Eight studies (Basemez et al., 2013; Cairo et al., 2017; Frisch et al., 2015; Huang et al., 2021; Lorenzo et al., 2012; Thoma et al., 2020, 2022; Vellis et al., 2019) assessed the efficacy of alternative techniques for peri-implant soft tissue augmentation, namely FGG, CTF, use of xenogenic collagen matrix (XCM), or acellular dermal matrix. Two articles reported the outcomes of the same RCT, at 3 and 5 years of post-trail follow-up (Thoma et al., 2020, 2022). Pooled data analyses found no difference between CTG/FGG versus XCM for mean PPD, MBL, and BOP (Figure 7).

3.2.5 | Oral hygiene behaviours

Three studies were selected (Alhakeem et al., 2022; Swierkot et al., 2013; Truhlar et al., 2000), including two RCTs and one case-control study (Table 5). No meta-analysis was possible. One multicentre RCT found a significant difference in favour of
(a) Probing pocket depth (PPD): comparison between implant sites with augmented and non-augmented PIKM

<figure><img src="image_14.png" /></figure>

(b) Bleeding on probing: comparison between implant sites with augmented and non-augmented PIKM

<figure><img src="image_15.png" /></figure>

(c) Marginal bone level: comparison between implant sites with augmented and non-augmented PIKM

<figure><img src="image_16.png" /><figcaption>**FIGURE 6** Forest plots for impact of peri-implant keratinized mucosa augmentation versus no augmentation on peri-implant probing depth, bleeding on probing, and marginal bone level.</figcaption></figure>

Overall, only three studies reported the occurrence of PIDs (Frisch et al., 2015; Hosseini et al., 2020; M. Roccuzzo et al., 2016). The first study defined peri-implantitis as the presence of BOP, PPD ≥5 mm, and a radiographic bone loss ≥3.5 mm (Frisch et al., 2015). During a mean follow-up of 12 years, three groups receiving FGG or CTG or no intervention were compared. No statistical differences were found between groups. The second study, a 10-year prospective cohort, observed a significantly higher rate of PIDs for dental implants with PIKM deficiency compared to implants surrounded by PIKM (51.4% vs. 12.7%; *p* < .0001) (Roccuzzo et al., 2016). The authors also reported a significantly lower soreness for implants surrounded by PIKM or placed in the alveolar mucosa receiving FGG compared to implants surrounded by alveolar mucosa and not receiving FGG (M. Roccuzzo et al., 2016). The third study was a controlled clinical trial with a small sample size (19 patients) and observed a 4.3% rate of peri-implantitis in the control group compared to 0% in the test group receiving CTG (partial split-mouth design) (Hosseini et al., 2020). Meta-analysis was performed by pooling together two studies comparing CTG versus no intervention (Frisch et al., 2015; Hosseini et al., 2020), and including 37 implants in CTG-augmented sites versus

69 implants in non-augmented sites. It showed no significant difference between the two groups for the rate of incident peri-implantitis (OR = 1.97; 95% CI: 0.2–19.72; *p* = .56; *I*²: 0%).

Eight studies (Basemez et al., 2013; Cairo et al., 2017; Frisch et al., 2015; Huang et al., 2021; Lorenzo et al., 2012; Thoma et al., 2020, 2022; Vellis et al., 2019) assessed the efficacy of alternative techniques for peri-implant soft tissue augmentation, namely FGG, CTF, use of xenogenic collagen matrix (XCM), or acellular dermal matrix. Two articles reported the outcomes of the same RCT, at 3 and 5 years of post-trail follow-up (Thoma et al., 2020, 2022). Pooled data analyses found no difference between CTG/FGG versus XCM for mean PPD, MBL, and BOP (Figure 7).

3.2.5 | Oral hygiene behaviours

Three studies were selected (Alhakeem et al., 2022; Swierkot et al., 2013; Truhlar et al., 2000), including two RCTs and one case-control study (Table 5). No meta-analysis was possible. One multicentre RCT found a significant difference in favour of
counter-rotational powered toothbrush in term of peri-implant mucosa inflammation and implant survival compared to manual tooth-brushing over a 2-year follow-up period (Truhlar et al., 2000). The other RCT, comparing sonic versus manual toothbrush over a 1-year trial, concluded that both toothbrushes maintain peri-implant tissue health over time (Swierkot et al., 2013). Finally, the case-control study indicated that the frequency of tooth brushing (at least twice a day vs. at most once a day) had no impact on peri-implant PPD, MBL, and BOP (Alhakeem et al., 2022).

### 3.2.6 | Other risk factors

No study was found concerning bruxism (or oral parafunction) control in patients awaiting or having received dental implants. Similarly, no study was found addressing the efficacy of behavioural strategies to improve lifestyle in order to maintain peri-implant health and prevent PIDs. Most of the interventions to control risk factors for PIDs remained unexplored.

### 3.3 | Primordial prevention of PIDs

No study investigated the impact of promoting healthy behaviours prior to implant placement to avoid risk factor development. To further explore this important topic, we revised the studies included in order to try to assess whether any preventive action was undertaken (and thus described) prior to implant placement. The results of this critical appraisal are reported in Table 6. Over the 48 articles included, high heterogeneity was noted; 15 of them (31.2%) clearly stated that periodontal diseases were assessed and treated prior to implant placement. Nineteen studies (39.5%) promoted adherence to SPC and 20 of them (41.7%) considered smoking as an exclusion (or non-inclusion) criterion. Fourteen studies (29%) stated that oral hygiene instructions were given to the patient prior to implant placement, but only a few described the specific OH instructions given.

### 3.4 | Risk of bias

The ROB assessment for case-control and cohort studies is reported in Table S4. Overall, 32 studies were evaluated based on the NOS system; 14 studies were found to be at high risk (<6 stars) and 18 at low risk of bias (≥6 stars). Concerning the RCTs included, the ROB assessment (ROB-II) is reported in Table S5. Only 2 of 12 trials were judged at low risk of bias. Finally, the four NRCTs were judged to be at moderate risk based on ROBINS-I scale as detailed in Table S6. Only 16 of 48 (33.3%) studies did not declare the source of funding (thus classified as unknown). Similarly, in 12 studies (25%), no declaration about potential conflicts of interest was found. The studies included were published over a period of 22 years (2000–2022).

## 4 | DISCUSSION

The present systematic review and meta-analysis was designed to assess the efficacy of risk factor control in preventing PIDs. None of the available studies was designed to provide direct evidence for both primordial and primary preventive interventions for PIDs. The present results are therefore inferred from observational and interventional studies with various working hypotheses that were not originally developed to test the efficacy of a preventive measure on the occurrence of PIDs. However, comparing patients exposed and not exposed to risk factors or benefitting or not benefitting from interventions that may decrease the consequence of risk may be useful to elucidate the role of risk factor control in the prevention of PIDs.

### 4.1 | Main findings

Overall, risk factor control appeared to impact positively on preserving peri-implant health and preventing PIDs, with differences related to the specific risk factor considered.

#### 4.1.1 | Impact of glycaemic control

The present meta-analyses showed that diabetes patients with poor glycaemic control (HbA1c >8%) have an increased risk of peri-implantitis and MBL changes over time compared to diabetes patients with a good glycaemic control. Evidence is consistent among the studies but limited and with a mean implant survival rate that may be considered as acceptable in both groups (95.6% and 99%, respectively). The results were reported at the dental implant level only because it was not possible to collect data using the patient as the statistical unit, even though a patient-level analysis would be more appropriate since diabetes is a systemic disease. Pooled-data analyses failed to show differences in PPD and BOP. Since the risk of peri-implantitis is increased, this could be interpreted as conflicting with its case definition, which included increased PPD and BOP (Berglundh et al., 2018). However, a mean difference in MBL was determined. This supports the central role of peri-implant bone loss as a major clinical feature of peri-implantitis (Carral et al., 2021). Pre-diabetes patients may also be seen to be at risk for PIDs, but insufficient data exist to assess this risk compared to controlled or poorly controlled diabetes.

Overall, the present findings were based on 11 studies, of which 4 (36.4%) were judged at high risk of bias. The clinical and statistical heterogeneity was high, which indicates a need for caution in the interpretation of the results. Moreover, no data were available on the type of action taken to control diabetes mellitus (e.g., lifestyle modifications, medications) in patients with good or poor glycaemic control. Finally, 7 of 11 studies were performed in Saudi Arabia where the prevalence of diabetes was estimated at 18.7% in 2021 (https://www.worldbank.org/en/home), one of the highest in the world. This limits the external validity of the data when dealing with European countries. Nevertheless, taken together, the present findings provide
counter-rotational powered toothbrush in term of peri-implant mucosa inflammation and implant survival compared to manual toothbrushing over a 2-year follow-up period (Truhlar et al., 2000). The other RCT, comparing sonic versus manual toothbrush over a 1-year trial, concluded that both toothbrushes maintain peri-implant tissue health over time (Swierkot et al., 2013). Finally, the case-control study indicated that the frequency of tooth brushing (at least twice a day vs. at most once a day) had no impact on peri-implant PPD, MBL, and BOP (Alhakeem et al., 2022).

### 3.2.6 | Other risk factors

No study was found concerning bruxism (or oral parafunction) control in patients awaiting or having received dental implants. Similarly, no study was found addressing the efficacy of behavioural strategies to improve lifestyle in order to maintain peri-implant health and prevent PIDs. Most of the interventions to control risk factors for PIDs remained unexplored.

### 3.3 | Primordial prevention of PIDs

No study investigated the impact of promoting healthy behaviours prior to implant placement to avoid risk factor development. To further explore this important topic, we revised the studies included in order to try to assess whether any preventive action was undertaken (and thus described) prior to implant placement. The results of this critical appraisal are reported in Table 6. Over the 48 articles included, high heterogeneity was noted; 15 of them (31.2%) clearly stated that periodontal diseases were assessed and treated prior to implant placement. Nineteen studies (39.5%) promoted adherence to SPC and 20 of them (41.7%) considered smoking as an exclusion (or non-inclusion) criterion. Fourteen studies (29%) stated that oral hygiene instructions were given to the patient prior to implant placement, but only a few described the specific OH instructions given.

### 3.4 | Risk of bias

The ROB assessment for case-control and cohort studies is reported in Table S4. Overall, 32 studies were evaluated based on the NOS system; 14 studies were found to be at high risk (<6 stars) and 18 at low risk of bias (≥6 stars). Concerning the RCTs included, the ROB assessment (ROB-II) is reported in Table S5. Only 2 of 12 trials were judged at low risk of bias. Finally, the four NRCTs were judged to be at moderate risk based on ROBINS-I scale as detailed in Table S6. Only 16 of 48 (33.3%) studies did not declare the source of funding (thus classified as unknown). Similarly, in 12 studies (25%), no declaration about potential conflicts of interest was found. The studies included were published over a period of 22 years (2000–2022).

## 4 | DISCUSSION

The present systematic review and meta-analysis was designed to assess the efficacy of risk factor control in preventing PIDs. None of the available studies was designed to provide direct evidence for both primordial and primary preventive interventions for PIDs. The present results are therefore inferred from observational and interventional studies with various working hypotheses that were not originally developed to test the efficacy of a preventive measure on the occurrence of PIDs. However, comparing patients exposed and not exposed to risk factors or benefitting or not benefitting from interventions that may decrease the consequence of risk may be useful to elucidate the role of risk factor control in the prevention of PIDs.

### 4.1 | Main findings

Overall, risk factor control appeared to impact positively on preserving peri-implant health and preventing PIDs, with differences related to the specific risk factor considered.

#### 4.1.1 | Impact of glycaemic control

The present meta-analyses showed that diabetes patients with poor glycaemic control (HbA1c >8%) have an increased risk of peri-implantitis and MBL changes over time compared to diabetes patients with a good glycaemic control. Evidence is consistent among the studies but limited and with a mean implant survival rate that may be considered as acceptable in both groups (95.6% and 99%, respectively). The results were reported at the dental implant level only because it was not possible to collect data using the patient as the statistical unit, even though a patient-level analysis would be more appropriate since diabetes is a systemic disease. Pooled-data analyses failed to show differences in PPD and BOP. Since the risk of peri-implantitis is increased, this could be interpreted as conflicting with its case definition, which included increased PPD and BOP (Berglundh et al., 2018). However, a mean difference in MBL was determined. This supports the central role of peri-implant bone loss as a major clinical feature of peri-implantitis (Carral et al., 2021). Pre-diabetes patients may also be seen to be at risk for PIDs, but insufficient data exist to assess this risk compared to controlled or poorly controlled diabetes.

Overall, the present findings were based on 11 studies, of which 4 (36.4%) were judged at high risk of bias. The clinical and statistical heterogeneity was high, which indicates a need for caution in the interpretation of the results. Moreover, no data were available on the type of action taken to control diabetes mellitus (e.g., lifestyle modifications, medications) in patients with good or poor glycaemic control. Finally, 7 of 11 studies were performed in Saudi Arabia where the prevalence of diabetes was estimated at 18.7% in 2021 (https://www.worldbank.org/en/home), one of the highest in the world. This limits the external validity of the data when dealing with European countries. Nevertheless, taken together, the present findings provide
(a) **Probing pocket depth:** comparison between implant sites augmented with xenogenic collagen matrix (XCM) vs. connective tissue graft (CTG) or free gingival graft (FGG)

<figure><img src="image_17.png" /></figure>

(b) **Bleeding on probing:** comparison between implant sites augmented with xenogenic collagen matrix (XCM) vs. connective tissue graft (CTG) or free gingival graft (FGG)

<figure><img src="image_18.png" /></figure>

(c) **Marginal bone level:** comparison between implant sites augmented with xenogenic collagen matrix (XCM) vs. connective tissue graft (CTG) or free gingival graft (FGG)

<figure><img src="image_19.png" /><figcaption>**FIGURE 7** Forest plots for impact of different peri-implant soft tissue augmentation procedures on peri-implant probing depth, bleeding on probing, and marginal bone level.</figcaption></figure>

additional evidence-based support to promote optimal glycaemic control in patients with diabetes mellitus undergoing dental implant therapy.

### 4.1.2 | Impact of smoking cessation

Based on the four studies included in this systematic review, there is insufficient evidence to determine whether smoking cessation or the

use of e-cigarettes and other smoking habits are associated with a decreased risk for PIDs compared to current smoking (F. Alqahtani et al., 2019; M. A. AlQahtani et al., 2018; ArRejaie et al., 2019). The best evidence available was represented by the cohort study conducted by Costa et al. The authors showed that the longer the time since smoking cessation, the lower was the occurrence of peri-implantitis: former smokers who quit smoking 6–10 years earlier had a significantly lower OR for peri-implantitis (OR = 0.49; 0.20–0.72) compared to current smokers (Costa et al., 2022). Thus, efforts should
(a) **Probing pocket depth:** comparison between implant sites augmented with xenogenic collagen matrix (XCM) vs. connective tissue graft (CTG) or free gingival graft (FGG)

<figure><img src="image_17.png" /></figure>

(b) **Bleeding on probing:** comparison between implant sites augmented with xenogenic collagen matrix (XCM) vs. connective tissue graft (CTG) or free gingival graft (FGG)

<figure><img src="image_18.png" /></figure>

(c) **Marginal bone level:** comparison between implant sites augmented with xenogenic collagen matrix (XCM) vs. connective tissue graft (CTG) or free gingival graft (FGG)

<figure><img src="image_19.png" /><figcaption>**FIGURE 7** Forest plots for impact of different peri-implant soft tissue augmentation procedures on peri-implant probing depth, bleeding on probing, and marginal bone level.</figcaption></figure>

additional evidence-based support to promote optimal glycaemic control in patients with diabetes mellitus undergoing dental implant therapy.

4.1.2 | Impact of smoking cessation

Based on the four studies included in this systematic review, there is insufficient evidence to determine whether smoking cessation or the

use of e-cigarettes and other smoking habits are associated with a decreased risk for PIDs compared to current smoking (F. Alqahtani et al., 2019; M. A. AlQahtani et al., 2018; ArRejaie et al., 2019). The best evidence available was represented by the cohort study conducted by Costa et al. The authors showed that the longer the time since smoking cessation, the lower was the occurrence of peri-implantitis: former smokers who quit smoking 6–10 years earlier had a significantly lower OR for peri-implantitis (OR = 0.49; 0.20–0.72) compared to current smokers (Costa et al., 2022). Thus, efforts should
<table><caption>TABLE 5 Characteristics and outcomes of the selected studies analysing the impact of oral hygiene habits on the prevention of peri-implant diseases.</caption><thead><tr><th rowspan="2">Reference</th><th rowspan="2">Study design</th><th rowspan="2">Country</th><th rowspan="2">Setting</th><th rowspan="2">Time frame</th><th rowspan="2">Follow-up duration (months)</th><th rowspan="2">Total no. patients (no. of implants)</th><th rowspan="2">No. of patients (no. of implants)</th><th colspan="2">Diagnosis of peri-implant mucositis</th><th colspan="2">Diagnosis of peri-implantitis</th><th rowspan="2">Peri-implant probing pocket depth (mm)</th><th rowspan="2">Radiographic marginal bone level changes (mm)</th></tr><tr><th>Patient level</th><th>Implant level</th><th>Patient level</th><th>Implant level</th><th>Survival rate</th><th>Peri-implant mucosa inflammation/BOP</th></tr></thead><tbody><tr><td rowspan="4">Truhlar et al. (2000)</td><td rowspan="4">Multicentre RCT</td><td rowspan="4">Hospital setting USA</td><td rowspan="4">NR F-UP: 24 months</td><td rowspan="4">Dental implants placed in Veterans Administration Medical Centres N = NR (2966)</td><td>Counter-rotational powered toothbrush N = NR (1409)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>96.1%</td><td>NE-but significantly lower than manual care group</td><td>NR</td><td>NR</td></tr><tr><td>Manual home-care N = NR (1557)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>94.1%</td><td>NE</td><td>NR</td><td>NR</td></tr><tr><td>Sonic toothbrush N = 42 (NR)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>0.27 ± 0.26</td><td>3.37 ± 0.85</td><td>NR</td></tr><tr><td>Manual toothbrush N = 41 (NR)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>0.28 ± 0.38</td><td>3.19 ± 0.81</td><td>NR</td></tr><tr><td rowspan="4">Swierkot et al. (2013)</td><td rowspan="4">RCT</td><td rowspan="4">Hospital setting Germany</td><td rowspan="4">2008-2010 F-UP: 12 months</td><td rowspan="4">Patients treated for periodontitis with at least 1 posterior dental implant N = 83 (290)</td><td>Brushing at least twice/day N = 55 (119)</td><td>NR</td><td>NR</td><td>NR</td><td>14/119 (11.8%)</td><td>100% 13/119 (10.9%)</td><td>PPD ≥ 4 mm: 85/119</td><td>MBL ≥ 3 mm: 19/119</td></tr><tr><td>Brushing at most once/day N = 88 (186)</td><td>NR</td><td>NR</td><td>NR</td><td>4/67 (6%)</td><td>100% 12/67 (17.9%)</td><td>PPD ≥ 4 mm: 56/67</td><td>MBL ≥ 3 mm: 7/67</td></tr><tr><td>Alhakeem et al. (2022)</td><td>Case-control study</td><td>University setting Iran</td><td>2010-2012 Mean F-UP: 7.3 ± 1.4 years</td><td>Consecutive patients receiving dental implants (including 47 patients with a history of severe periodontitis) N = 88 (186)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td></tr></tbody></table>

Note: Significant differences between groups in the outcome measures are indicated in bold.

Abbreviations: BOP, bleeding on probing; F-UP, follow-up; NE, not estimable; NR, not reported; RCT, randomized controlled trial.
<table><caption>TABLE 5 Characteristics and outcomes of the selected studies analysing the impact of oral hygiene habits on the prevention of peri-implant diseases.</caption><thead><tr><th rowspan="2">Reference</th><th rowspan="2">Study design</th><th rowspan="2">Country</th><th rowspan="2">Setting</th><th rowspan="2">Time frame</th><th rowspan="2">Follow-up duration (months)</th><th rowspan="2">Total no. patients (no. of implants)</th><th rowspan="2">No. of patients (no. of implants)</th><th colspan="2">Diagnosis of peri-implant mucositis</th><th colspan="2">Diagnosis of peri-implantitis</th><th rowspan="2">Peri-implant probing pocket depth (mm)</th><th rowspan="2">Radiographic marginal bone level changes (mm)</th></tr><tr><th>Patient level</th><th>Implant level</th><th>Patient level</th><th>Implant level</th><th>Survival rate</th><th>Peri-implant mucosa inflammation/BOP</th></tr></thead><tbody><tr><td rowspan="4">Truhlar et al. (2000)</td><td rowspan="4">Multicentre RCT</td><td rowspan="4">Hospital setting USA</td><td rowspan="4">NR F-UP: 24 months</td><td rowspan="4">Dental implants placed in Veterans Administration Medical Centres<br/>N = NR (2966)</td><td>Counter-rotational powered toothbrush<br/>N = NR (1409)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>96.1%</td><td>NE-but significantly lower than manual care group</td><td>NR</td><td>NR</td></tr><tr><td>Manual home-care<br/>N = NR (1557)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>94.1%</td><td>NE</td><td>NR</td><td>NR</td></tr><tr><td>Sonic toothbrush<br/>N = 42 (NR)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>0.27 ± 0.26</td><td>3.37 ± 0.85</td><td>NR</td></tr><tr><td>Manual toothbrush<br/>N = 41 (NR)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>0.28 ± 0.38</td><td>3.19 ± 0.81</td><td>NR</td></tr><tr><td rowspan="4">Swierkot et al. (2013)</td><td rowspan="4">RCT</td><td rowspan="4">Hospital setting Germany</td><td rowspan="4">2008-2010 F-UP: 12 months</td><td rowspan="4">Patients treated for periodontitis with at least 1 posterior dental implant<br/>N = 83 (290)</td><td>Brushing at least twice/day<br/>N = 55 (119)</td><td>NR</td><td>NR</td><td>NR</td><td>14/119 (11.8%)</td><td>100% 13/119 (10.9%)</td><td>PPD ≥ 4 mm: 85/119</td><td>MBL ≥ 3 mm: 19/119</td></tr><tr><td>Brushing at most once/day<br/>N = 88 (186)</td><td>NR</td><td>NR</td><td>NR</td><td>4/67 (6%)</td><td>100% 12/67 (17.9%)</td><td>PPD ≥ 4 mm: 56/67</td><td>MBL ≥ 3 mm: 7/67</td></tr><tr><td>Consecutive patients receiving dental implants (including 47 patients with a history of severe periodontitis)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td>N = 88 (186)</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td>Alhakeem et al. (2022)</td><td>Case-control study</td><td>University setting Iran</td><td>2010-2012 Mean F-UP: 7.3 ± 1.4 years</td><td>Patients treated for periodontitis with at least 1 posterior dental implant<br/>N = 83 (290)</td><td>Brushing at least twice/day<br/>N = 55 (119)</td><td>NR</td><td>NR</td><td>NR</td><td>14/119 (11.8%)</td><td>100% 13/119 (10.9%)</td><td>PPD ≥ 4 mm: 85/119</td><td>MBL ≥ 3 mm: 19/119</td></tr></tbody></table>

Note: Significant differences between groups in the outcome measures are indicated in bold.

Abbreviations: BOP, bleeding on probing; F-UP, follow-up; NE, not estimable; NR, not reported; RCT, randomized controlled trial.
<table><caption>TABLE 6 Primordial prevention actions reported in the selected studies.</caption><thead><tr><th>Variable</th><th>Oral hygiene instructions given prior to implant placement</th><th>Achievement of optimal plaque control prior to implant placement</th><th>Achievement of low gingival inflammation prior to implant placement</th><th>Treatment(s) of periodontal disease prior to implant placement</th><th>Promoting smoking cessation</th><th>Promoting adherence to periodontal and peri-implant supportive care</th><th>Promoting/ monitoring glycaemic control</th></tr></thead><tbody><tr><td><strong>Reference</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Glycaemic control</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Tawil et al. (2008)</td><td>-</td><td>-</td><td>-</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Aguilar-Salvatierra et al. (2016)</td><td>✓</td><td>✓</td><td>-</td><td>✓</td><td>Smoking as exclusion criterion</td><td>-</td><td>✓</td></tr><tr><td>Ghiraldini et al. (2016)</td><td>-</td><td>-</td><td>-</td><td>✓</td><td>Smoking as exclusion criterion</td><td>✓</td><td>✓</td></tr><tr><td>Gomez-Moreno et al. (2015)</td><td>-</td><td>✓</td><td>-</td><td>-</td><td>Smoking as exclusion criterion</td><td>-</td><td>✓</td></tr><tr><td>Al Amri et al. (2016)</td><td>✓</td><td>-</td><td>-</td><td>-</td><td>Smoking as exclusion criterion</td><td>✓</td><td>✓</td></tr><tr><td>Abduljabbar et al. (2017)</td><td>-</td><td>-</td><td>-</td><td>-</td><td>Smoking as exclusion criterion</td><td>-</td><td>✓</td></tr><tr><td>Alrabiah et al. (2018)</td><td>-</td><td>-</td><td>-</td><td>-</td><td>Smoking as exclusion criterion</td><td>-</td><td>-</td></tr><tr><td>Al-Sowygh et al. (2018)</td><td>-</td><td>-</td><td>-</td><td>-</td><td>Smoking as exclusion criterion</td><td>-</td><td>-</td></tr><tr><td>Alsahhaf et al. (2019)</td><td>-</td><td>-</td><td>-</td><td>-</td><td>Smoking as exclusion criterion</td><td>✓</td><td>✓</td></tr><tr><td>Al Zahrani and Al Mutairi (2019)</td><td>-</td><td>-</td><td>-</td><td>-</td><td>Smoking as exclusion criterion</td><td>✓</td><td>✓</td></tr><tr><td>Mokeem et al. (2019)</td><td>-</td><td>-</td><td>-</td><td>-</td><td>Smoking as exclusion criterion</td><td>-</td><td>✓</td></tr><tr><td><strong>Smoking cessation strategies</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>AlQahtani et al. (2018)</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>ArRejaie et al. (2019)</td><td>-</td><td>-</td><td>-</td><td>-</td><td>✓</td><td>-</td><td>Diabetes as exclusion criterion</td></tr><tr><td>Alqahtani et al. (2019)</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>Diabetes as exclusion criterion</td></tr><tr><td>Costa et al. (2022)</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td><strong>Supportive care protocols/compliance</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Ferreira et al. (2006)</td><td>✓</td><td>-</td><td>-</td><td>-</td><td>Smoking as exclusion criterion</td><td>-</td><td>-</td></tr><tr><td>M. Rocuzzo et al. (2010, 2012)</td><td>✓</td><td>✓</td><td>✓</td><td>-</td><td>-</td><td>✓</td><td>-</td></tr></tbody></table>