Risk of Revision and Other Complications Following Knee Arthroplasty in Patients Previously Exposed to Bariatric Surgeries: A Nationwide, Register-based Study
Conditions: Arthritis Knee, Bariatric Surgery Candidate, Prosthesis Failure, Prosthesis Survival, Prosthesis-Related Infections
Sponsor: Bispebjerg Hospital

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Risk of revision and other complications following knee arthroplasty 
in patients previously exposed to bariatric surgeries: A nationwide, 
register-based study 
 
Authors/Collaborators: 
Saber M. Saber1,2,4, MD, PhD Fellow; Janne Petersen MSc, PhD, Associate Professor3,6; Robin 
Christensen2,5, MSc, PhD, Professor; Espen Solem, MD, PhD, Associate Professor3,4; Søren 
Overgaard, MD, DmSci, Professor1,4 
 
Affiliations: 
1. Department of Orthopaedic Surgery and Traumatology, Copenhagen University Hospital, Bispebjerg and 
Frederiksberg, Copenhagen, Denmark; 2. Section for Biostatistics and Evidence-Based Research, the Parker Institute, 
Copenhagen University Hospital, Bispebjerg and Frederiksberg, Copenhagen, Denmark; 3. Copenhagen Phase IV unit 
(Phase4CPH), Department of Clinical Pharmacology and Center of Clinical Research and Prevention at Copenhagen 
University Hospital, Bispebjerg and Frederiksberg; 4. University of Copenhagen, Department of Clinical Medicine, 
Faculty of Health and Medical Sciences; 5. Research Unit of Rheumatology, Department of Clinical Research, 
University of Southern Denmark, Odense University Hospital, Denmark & 6. Section of Biostatistics, Department of 
Public Health, University of Copenhagen, Copenhagen, Denmark. 
 
 

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Abstract 
Background: Previous studies have investigated the outcomes of Knee Arthroplasty (KA) following Bariatric 
Surgery (BAS), but with substantial limitations as not stratifying for Body Mass Index (BMI) at time of KA or 
not addressing the type of BAS (gastric bypass, banding or sleeve). Since BMI varies greatly in patients with 
previous BAS, it is likely that BMI affects outcomes after KA in BAS-operated patients. 
Objective: Based on the Danish national registers and databases. The objective of this study is to analyse 
the association between exposure to BAS prior to KA and the following outcomes: 1) the risk of revision, 2) 
use of antibiotics and 3) mortality. Furthermore, we want to test whether the association is modified by BMI 
status at the time KA surgery (i.e., non-obese, obese and morbidly obese patients). 
Methods/Design: The study is a nationwide, register-based cohort study. The study will follow the 
reporting of studies conducted using observational routinely-collected data statement for 
PharmacoEpidemiology (RECORD-PE) guidelines. We will compare the risk of revision after primary KA 
between patients with or without prior BAS. We will stratify the for BMI (non-obese: BMI < 30 kg/m2, obese: 
BMI 30-39 kg/m2, morbidly obese: BMI ≥ 40 kg/m2) at time of KA and the type of KA (i.e., Total Knee 
Arthroplasty (TKA) or Unicondylar Knee Arthroplasty (UKA)).  
Exposures and outcomes: Exposure will be defined as BAS prior to KA. Outcomes are 1) revision due to all 
causes; 2) revision due to infection; 3) Knee related use of antibiotics within 30- and 90 days after the index 
KA; 4) Antibiotic use due to other causes within 30- and 90 days after the index KA and 5) mortality rate 
within 2 years following the index KA. We will use BMI, year of KA, year of BAS, sex, household income, 
highest completed education, comedication, Elixhauser Comorbidity Measure (ECM) and the NOMESCO 
(Nordic Medico-Statistical Committee) Classification of Surgical Procedures for stratifying and matching.. 
Multiple sensitivity analyses will be performed to investigate the influence of time between BAS and KA; 
and the type of BAS on the outcomes.  
Perspectives: The purpose of this study is to estimate the risk of complications following KA in patients with 
previous exposure to BAS and it is anticipated that findings from this study would potentially help shared-
decision making between the surgeon and patient - weighing the risks and benefits and by that, optimise 
selection of the right patients. 
 
Keywords: Knee Arthroplasty, Bariatric Surgery, Risk of Revision, Register, Osteoarthritis 

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INTRODUCTION  
Knee Arthroplasty (KA) have been estimated to have a 15-years survival rate of around 93%.1 The main 
indications for revision after knee arthroplasty are aseptic loosening, infection and pain.2 Surgical risk 
factors for revision include uncemented components, implant malalignment and longer length of operation. 
Patient-related risk factors include obesity, male sex and younger age at time of KA.3-8 Obese patients 
(BMI>30 kg/m2) have a higher risk for revision, deep and superficial infection, wound dehiscence and 
readmission following KA.5 As obesity is a major risk factor much attention has been paid to weight loss 
before surgery. bariatric surgery (BAS) is an efficient weight-reducing intervention and can lead to a 
decrease in excess weight by up to 74% through all types of bariatric surgeries.9 The prevalence of BAS-
operated patients is increasing due to the increased obesity worldwide.10 Whether BAS previous to KA is 
advantageous is disputed, mainly because BAS carries possible long-term complications, which vary 
depending on the type of BAS.11,12 For example, late, non-surgical complications such as nutritional 
deficiencies of micronutrients and vitamins (including vitamin D) may impact bone metabolism and immune 
capacity and hence increase the risk of revision after KA, despite the weight loss achieved by BAS.13 
Previous studies have investigated the outcomes of KA after BAS, but with substantial limitations.14-24  A 
recent RCT concluded a reduced risk of complications after KA in patients exposed to BAS. The trial was 
underpowered (and prematurely terminated) for important outcomes and has limited external validity due 
to unclear exclusion criteria and a high number of excluded patients.16 Other limitation is the treatment of 
BAS as a homogenous group without stratifying for BMI at time of KA or type of BAS (gastric bypass, 
banding or sleeve).17-24 For instance, various studies have reported that the Body Mass Index (BMI) of the 
BAS-groups at the time of knee arthroscopy (KA) falls within a broad range of 23-57 kg/m2.21,22,24 This 
significant variance in BMI suggests considerable heterogeneity within this group. Furthermore, this wide 
range in BMI could potentially influence the outcomes reported in these studies. Moreover, some 
researchers did not report the registered body mass index (BMI) at the time of KA. Instead, they relied on 
ICD-9 codes for their data. 17-20,23 This approach results in a comparison between two groups that are 
fundamentally dissimilar. This is because ICD-9 codes do not accurately reflect overweight conditions, and 
in a US sample, only 15.1% of overweight patients were assigned relevant ICD-9 codes.25 
Objective 
The objective of this study is to analyse the association between exposure to BAS prior to KA and the 
following outcomes: 1) the risk of revision, 2) use of antibiotics and 3) mortality. Furthermore, we want to 
test whether the association is modified by BMI at the time KA surgery (i.e., non-obese, obese and morbidly 

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obese patients). This would help the surgeon in weighing the risks and benefits and by that, selecting the 
right patient for operation. 
METHODS 
Study design  
The study is a nationwide, register-based cohort study. The study will be reported following the REporting 
of studies Conducted using Observational Routinely-collected Data statement for PharmacoEpidemiology 
(RECORD-PE) guidelines. 26 We will compare the risk of revision after primary KA in the period from 2011 
and 2 years earlier to data-extraction date stratified for exposure to BAS prior to their KA. We will further 
stratify for BMI (non-obese: BMI < 30 kg/m2, obese: BMI 30-39 kg/m2, and morbidly obese: BMI ≥ 40 kg/m2) 
at time of KA and the type of KA (i.e., Total Knee Arthroplasty (TKA) or Unicondylar Knee Arthroplasty 
(UKA)). 
Setting  
There are approximately 5.8 million inhabitants in Denmark, and every citizen has a unique 10-digit Civil 
Personal Register (CPR) number in the Danish Civil Registration System (DCRS), and by this number citizens 
can be cross-linked across different databases and be traced until death or immigration. 
Data sources 
The Danish Civil Registration System (DCRS) contains information on the CPR number, vital and migrant 
status, cohabiting status, and municipality of residence.27 
The Danish Knee Arthroplasty Register (DKR) is nation-wide register that contains 
information on all primary knee arthroplasty procedures and revisions performed in Denmark, e.g., baseline 
characteristics as age, sex, BMI, at the time of KA operation. The registry started in 1997 and the reporting 
to the registry became mandatory since 2006. DKR is known for high degree of coverage and 
completeness.28,29  
The Danish Microbiology Database (MiBa) is a national database containing data from all 
samples received by the Danish clinical microbiology departments from both hospitals and general practices 
with complete coverage since 2010. 30 
The Danish National Patient Register (DNPR) is a valuable tool for epidemiological research, 
providing longitudinal registration of diagnoses, treatments, and examinations derived from every hospital 
contact in Denmark with complete nationwide coverage since 1978. 31 

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The Danish National Prescription Registry has kept information on all prescriptions for drugs 
dispensed by community pharmacies in Denmark since 1994 according to Anatomical Therapeutic Chemical 
(ATC) classification system (ATC codes). Data from the Danish National Prescription Registry does not 
include hospital dispensaries.32 
The Danish Registers on Personal Income and Transfer Payments contains more than 160 
variables including salaries, entrepreneurial income, taxes, public transfer payments, capital income, private 
pension contributions, and pay-outs. In addition, Statistics Denmark provide more detailed registers on 
specific income transfers, including sickness benefit, old age pension, disability pension, and cash and 
unemployment benefits.33 
The Danish Population Education Register provides information on education status on Danish 
population, and it carries high degree of validity and coverage.34 
Study population 
We will include patients with primary/idiopathic or secondary (due to meniscus or cruciate ligament lesion) 
osteoarthritis (OA) who received primary KA in the period from 2011 and 2021. Patients will be identified 
from the DKR. Patients are followed for 2 years, until first revision, death or migration, whichever comes 
first. 
Variables 
Outcomes:  
1. Revision due to any cause at two different observation periods within 1) 90 days and b) 2 years 
following KA. Revision surgery with debridement and/or exchange of at least one component will 
be based on a composite endpoint (34) 
2. Revision due to infection within 1) 90 days and b) 2 years following KA: our definition of infection is 
adapted from the European Bone and Joint Infection Society (EBJIS) criteria 35 as at least one of the 
following 
A. DKR-registered revision surgery due to infection. 
B. At least 2 deep-tissue samples of phenotypically indistinguishable bacteria isolated 
from at least 3 deep-tissue samples  
C. One or more positive intraoperative samples from a closed fluid aspirate AND a 
biopsy (fluid AND tissue) of phenotypically indistinguishable bacteria isolated.  
3. Antibiotic use within 30- and 90-days following KA as measure of knee related infection will be 
defined as the use of one of the following oral antibiotics: dicloxacillin, flucloxacillin, 

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phenoxymethylpenicillin, or amoxicillin as suggested by Milandt et al.36 Other antibiotics 
recommended by the international consensus for treating joint infections will also be considered 
knee-related: oral ciprofloxacin, roxithromycin, linezolid, cefuroxime and cefalexin. 37   
4. Antibiotic use within 30- and 90-days following KA due to other causes: any oral antibiotic other 
than the forementioned ones. 
5. Mortality registered in the DCRS by date up to 2 years following KA surgery. 
 
Covariates  
We will identify our cohort as patients, who had a BAS before the date of index arthroplasty based on the 
NOMESCO (Nordic Medico-Statistical Committee) Classification of Surgical Procedures from the DNPR 
(KJDF10 & KJDF11 [gastric bypass]; KJDF20 & KJDF21 [gastric banding]; KJDF40, KJDF41, KJDF96 & KJDF97 
[gastric sleeve]). The comparator (unexposed) group will be patients without BAS before KA. 
BMI category and the type of KA (TKA and UKA). will be used for stratifying into subgroups, 
differentiating individuals into appropriate baseline strata. For matching we will be using the following pre-
KA-exposure covariates: age (years) at the year of KA, sex (male/female), household income (at the year of 
KA, categorized into quartiles), highest completed education (at the year of KA, categorized into 3 
categories: <11, 11 to 15, and >15 years). 
Comedication (at least one redeemed prescription 365 days earlier to index KA - 60 days for 
antibiotics): 1) Glucose-lowering due to the association between DM and surgical complications.38,39 2) 
Antithrombotic medications and 3) NSAIDs because of the possible postoperative bleeding-related 
complications 40 and 4) Antiresorptives due to the possible increased risk of revision.41 The last covariate to 
be included in matching and adjustment is Elixhauser Comorbidity Measure (ECM) (at the year of KA, 
categorized into 3: 0, 1-2 and ≥ 3), ECM is validated comorbidity scoring measure that has shown highest 
discriminative ability for the occurrence of all categories of postoperative adverse outcomes following 
orthopedic surgeries.42-44 
For sensitivity analyses we will analyse the type of BAS and the calendar year of BAS and the calendar 
year of KA. 
 
Database construction and handling 
We will extract data from all patients receiving KA in period from 2011 and 2023 the DKR, the dataset will 
be enriched with the relevant variables by cross-linking the CPR numbers from the MiBa and will be sent to 

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Statistics Denmark, where the baseline socioeconomic data will be supplied. The database will be then 
enriche with baseline health-related data from the Danish Health Data Authority (DHDA). The final 
database will be kept and handled inside an encrypted server belonging to Statistics denmark. Data is 
handled in the most recent version of R (www.r-project.org). The primary author (SMS) will be responsible 
for data management. 
Data control and editing  
In case of bilateral KA, the first one will be treated as study unit. In case of simultaneous bilateral KA, 
patients will be excluded. 
We expect some missing values in our study and these values will be omitted, no data imputation will be 
used. 
Extreme values for continuous variables will be tested by using plots and histograms to identify the 
possible entry-errors. 
In case of abnormal data entries, e.g., wrong date format, it will be corrected if possible, otherwise the 
values will be omitted. 
 
Statistical Methods 
We will use descriptive statistics for the baseline characteristics of the two groups stratified for BMI and the 
type of KA. To address possible survival bias, number of deaths in the exposed and non-exposed groups will 
be reported.  
First, we will run a non-adjusted (crude) analysis comparing outcomes between patients 
exposed and unexposed to BAS. Then we will perform a propensity score matched analysis, where we do 
exact matching based on BMI (non-obese: BMI < 30 kg/m2, obese: BMI 30-39 kg/m2, morbidly obese: BMI ≥ 
40 kg/m2) and the type of KA (i.e., TKA or UKA). Propensity scores will be estimated using a logistic 
regression model and will be based the forementioned covariates. We will use  greedy match algorithm in a 
ratio of up to 1:5 of patients exposed to bariatric surgery and those who are not, in order to minimize the 
mean squared error of the estimated treatment effect in several scenarios, difference of maximum of 0.2 
logit will be used in propensity score matching 45. Following that, we will do a propensity score matched 
analysis with interaction term for BMI. 
For dichotomous outcomes, a cox regression will be performed to report hazards ratio with 
the corresponding two-sided 95% confidence intervals (Cis) and a p-value of <0.05 will be considered as 
statistically significant. 
To validate the propensity score matching, we will report the standardized differences of the means 
(or medians) of continuous variables or the prevalence of dichotomous baseline covariates between each 
set of groups by using the standardised differences. We will apply a standardized difference of ≥0.25 to 
indicate that there might be a meaningful imbalance in the baseline covariate. 

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Sensitivity analyses 
We will do a sensitivity analysis to test whether the gap between BAS and KA would influence the obtained 
result by limiting the gap ≤12 months, 13-24 months and >24 months. To investigate whether the type of 
Bariatric Surgery (BAS), such as gastric banding or gastric bypass, has an impact on the outcomes, we plan 
to conduct a sensitivity analysis. This will involve narrowing our focus to each specific type of BAS. This 
particular approach has not been previously applied, and the findings could prove to be significant.  
Patient and Public Involvement (PPI) 
This project follows the EULAR recommendations for the inclusion of patient representatives in the 
contemporary scientific process.46 This protocol was introduced to a Danish PPI. The research questions 
and the reported outcomes was discussed from the PPI perspectives.  
 
HEALTH RESEARCH ETHICS AND GENERAL CONSIDERATIONS  
Funding 
Section for Biostatistics and Evidence-Based Research, the Parker Institute, Bispebjerg and Frederiksberg 
Hospital is supported by a core grant from the Oak Foundation (OCAY-18-774-OFIL). Saber M. Saber is 
supported by a grant from Karen Elise Jensens Fond. The supporting institutions had no role in study design 
or writing of this protocol. 
Conflict of interest 
All will be disclosed. 
Disclaimers 
The views expressed in the submitted protocol are the authors’ own and not an official position of the 
institution or funder. 
Ethics 
In Denmark, the Act on Processing of Personal Data does not require ethical permission or obtained 
consent for anonymised retrospective register studies. The Danish Data Protection Agency has approved 
the study with nr p-2023-14433. 
 
 
 

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