(2022) 20:326
Romiti et al. BMC Medicine
https://doi.org/10.1186/s12916-022-02526-7

RESEARCH ARTICLE

Open Access

Clinical complexity and impact of the ABC(Atrial fibrillation Better Care) pathway
in patients with atrial fibrillation: a reportfrom the ESC‑EHRA EURObservational Research
Programme in AF General Long‑Term Registry
Giulio Francesco Romiti1,2†, Marco Proietti1,3,4†, Marco Vitolo1,5,6, Niccolò Bonini1,5, Ameenathul Mazaya Fawzy1,
Wern Yew Ding1, Laurent Fauchier7, Francisco Marin8, Michael Nabauer9, Gheorghe Andrei Dan10,
Tatjana S. Potpara11,12, Giuseppe Boriani5†, Gregory Y. H. Lip1,13*†   and on behalf of the ESC-EHRA EORP-AF
General Long-Term Registry Investigators

Abstract
Background: Clinical complexity is increasingly prevalent among patients with atrial fibrillation (AF). The ‘Atrial fibrillation Better Care’ (ABC) pathway approach has been proposed to streamline a more holistic and integrated approachto AF care; however, there are limited data on its usefulness among clinically complex patients. We aim to determine
the impact of ABC pathway in a contemporary cohort of clinically complex AF patients.
Methods: From the ESC-EHRA EORP-AF General Long-Term Registry, we analysed clinically complex AF patients,
defined as the presence of frailty, multimorbidity and/or polypharmacy. A K-medoids cluster analysis was performed
to identify different groups of clinical complexity. The impact of an ABC-adherent approach on major outcomes wasanalysed through Cox-regression analyses and delay of event (DoE) analyses.
Results: Among 9966 AF patients included, 8289 (83.1%) were clinically complex. Adherence to the ABC pathway
in the clinically complex group reduced the risk of all-cause death (adjusted HR [aHR]: 0.72, 95%CI 0.58–0.91), major
adverse cardiovascular events (MACEs; aHR: 0.68, 95%CI 0.52–0.87) and composite outcome (aHR: 0.70, 95%CI:
0.58–0.85). Adherence to the ABC pathway was associated with a significant reduction in the risk of death (aHR: 0.74,
95%CI 0.56–0.98) and composite outcome (aHR: 0.76, 95%CI 0.60–0.96) also in the high-complexity cluster; similar
trends were observed for MACEs. In DoE analyses, an ABC-adherent approach resulted in significant gains in eventfree survival for all the outcomes investigated in clinically complex patients. Based on absolute risk reduction at 1 year†

Giulio Francesco Romiti and Marco Proietti equally contributed to the paper.

†

Giuseppe Boriani and Gregory Y.H. Lip are joint senior authors.

*Correspondence: gregory.lip@liverpool.ac.uk
1
Liverpool Centre for Cardiovascular Science, University of Liverpool
and Liverpool Heart & Chest Hospital, William Henry Duncan Building, 6 West
Derby St, Liverpool L7 8TX, UK
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Romiti et al. BMC Medicine(2022) 20:326

Page 2 of 12

of follow-up, the number needed to treat for ABC pathway adherence was 24 for all-cause death, 31 for MACEs and 20
for the composite outcome.
Conclusions: An ABC-adherent approach reduces the risk of major outcomes in clinically complex AF patients.
Ensuring adherence to the ABC pathway is essential to improve clinical outcomes among clinically complex AF
patients.
Keywords: Atrial fibrillation, Integrated management, Outcomes, Clinical complexity

BackgroundIn recent years, increasing awareness of clinical complexity has contributed to significant changes in theapproach to the care of atrial fibrillation (AF) patients.
Multimorbidity, polypharmacy and frailty can be seenas three different expressions of clinical complexity,
and although these often coexist and overlap, eachof these phenomena has a specific role in influencing prognosis [1]. All of these have been repeatedly
described in AF patients, and several reports have outlined their detrimental effects in terms of quality ofcare and major outcomes [2–6].
Recent guidelines on AF [7, 8] have recommended
appropriate characterization and evaluation ofpatients [9], followed by a holistic or integrated careapproach to AF management, based on the ‘Atrial
fibrillation Better Care’ (ABC) pathway approach tostreamline a comprehensive and holistic management of AF patients [10]. The ABC pathway approachhas three pillars: ‘A’, Anticoagulation/avoid stroke; ‘B’,
Better symptom management; and ‘C’, Cardiovascular risk factors and Comorbidities optimization [10].
Adherence to the ABC pathway in patients with AF
is associated with a lower risk of major outcomes andhealth-related costs in real-world observational studies [11–15], confirmed by the prospective mAFA-II
randomized controlled trial [16] and highlighted in asystematic review and meta-analysis [17]. The latter
showed that adherence to an ABC pathway was associated with lower risk of all major outcomes (including
all-cause death, stroke, and major bleeding) among AF
patients.
To date, there are few contemporary data on theeffectiveness of the ABC pathway in specific highrisk subgroups of AF patients, particularly in clinically complex subjects. In this analysis from theEuropean Society of Cardiology (ESC) EURObservational Research Programme (EORP) Atrial Fibrillation
General Long-Term Registry, we explored whether
adherence to the ABC management strategy would
be associated with reduced risk of adverse outcomesin clinically complex patients, defined as those withfrailty, multimorbidity and/or polypharmacy.

Methods
For the purpose of this analysis, we used data from the
ESC-EHRA EURObservational Research Programme(EORP) Atrial Fibrillation General Long-Term Registry,
which is a prospective, observational, multicentre registry, held by the ESC and endorsed by the EHRA. The
study enrolled consecutive AF inpatients and outpatientsin 250 cardiology practices, across 27 countries. Details
on study design, baseline characteristics, outcomes adjudication and follow-up are reported elsewhere [18, 19].
Briefly, all patients enrolled had AF, documented in
the 12 months preceding enrolment. All patients wereaged ≥18 years and provided written informed consent.
Enrolment was undertaken from October 2013 to September 2016, with planned 1-year and 2-year follow-up.
Patient data were collected after the signing of a written informed consent by each patient, and following theapproval of the study protocol by an Institutional Review
Board/Ethic Committee. The study was first approvedby the National Coordinators’ main institutions (listed
in the Acknowledgements section) and subsequently
authorized by each site under the responsibility of thelead contact and study team (all listed in the Acknowledgements section), as per the specific national and local
regulation. Any details regarding approval numbers forthe study protocol regarding any specific site could beobtained from the corresponding authors, upon reasonable request. The study was performed according to
the European Union Note for Guidance on Good Clinical Practice CPMP/ECH/135/95 and the Declaration of
Helsinki.
Symptomatic status was defined according to EHRA
score [8], while thromboembolic and bleeding risk wereassessed according to ­CHA2DS2-VASc and HAS-BLED
scores, computed according to the original schemes[8]. We defined high thromboembolic risk when
­CHA2DS2-VASc was ≥2 in males and ≥3 in females, andhigh bleeding risk when HAS-BLED was ≥3. Frailty wasassessed according to a 40-item frailty index (FI) (Additional file 1: Table S1), built according to the cumulative
deficits model, as proposed by Rockwood and Mitnitski[20, 21]. Calculation of FI was performed as the ratio of
the total deficits found for each patient over the total
number of possible deficits examined. According to theRomiti et al. BMC Medicine(2022) 20:326

usual clinical use, a FI ranging from 0.10 to <0.25 defined
the presence of pre-frailty, while a FI ≥0.25 defined thepresence of frailty [22]. Multimorbidity was defined as
the presence of ≥2 comorbidities. Number of drugs
received at baseline was used to assess polypharmacy,
which was defined as the concomitant use of ≥5 drugs[23].
Adherence to the Atrial fibrillation Better Care (ABC)
pathway was evaluated at baseline and defined as per previously published study [14] according to three criteria[10]:– ‘A’ Criterion: Patients were considered ‘adherent’
to the ‘A’ criterion if properly prescribed with oral
anticoagulant (OAC) according to their thromboembolic risk. Specifically, we considered adherent
males with C­ HA2DS2-VASc≥1 and females with
­CHA2DS2-VASc≥2, treated with either vitamin K
antagonist (VKA) (with a time in therapeutic range≥70%) or a non-vitamin K antagonist oral anticoagulant (NOAC); patients not receiving OAC and with
low thromboembolic risk (i.e. C­ HA2DS2-VASc=0 in
males or =1 in females) were also considered adherent.
– ‘B’ Criterion: As this criterion refers to the actual
symptom control, rather than the attempt, we considered ‘adherent’ those patients with an EHRA scoreof I (no symptoms) or II (mild symptoms) at baseline.
– ‘C’ Criterion: For this criterion, we considered thecomorbidities most frequently found in AF patients:
hypertension, coronary artery disease (CAD),
peripheral artery disease (PAD), heart failure (HF),
previous stroke/transient ischaemic attack (TIA)
and diabetes mellitus. Any patient with ≥1 of these
conditions and treated according to ‘optimal medical
treatment’ (defined according to the current clinicalguidelines) was considered adherent to this criteria.
Optimal treatment was defined as follows: (i) hypertension: if blood pressure at baseline was ≤140/90
mmHg; (ii) CAD: treatment with angiotensin-converting enzyme (ACE) inhibitors, beta-blockers andstatins; (iii) PAD: treatment with statins; (iv) previous
stroke/TIA: treatment with statins; (v) HF: treatment
with ACE inhibitors or angiotensin receptor blockers, and beta-blockers; and (vi) diabetes mellitus:
treatment with insulin or oral antidiabetics. Patientswith 2 or more of the above conditions needed to be
optimally treated for all to be considered adherent tothe ‘C’ criterion.
Patients who met all three criteria were consideredadherent to the ABC pathway; otherwise, they were considered ABC-non adherent.

Page 3 of 12

Major adverse events

For this analysis, we considered the following major
adverse events: (i) all-cause death; (ii) major adverse cardiovascular events (MACEs), as the composite of any
thromboembolic events, any acute coronary syndromeand cardiovascular death; and (iii) a composite outcomeof all-cause death and MACE.
Statistical analysis

Continuous variables were expressed as mean (Standard
Deviation, SD) or median [interquartile range, IQR]; differences across groups were evaluated with appropriate
parametric and non-parametric tests, respectively. Categorical variables were expressed as counts and percentages; differences across groups were assessed throughchi-square test.
Cox regression models were fitted to evaluate theimpact of ABC pathway (in terms of full adherence,
number of criteria fulfilled and each additional criteria)
in clinically complex patients (defined as having at least
one complexity criteria among frailty, multimorbidity
and polypharmacy), and separately in those with frailty,
multimorbidity and polypharmacy, after adjustment forage, sex, type of atrial fibrillation and components of­CHA2DS2-VASc (previous thromboembolism, coronary
artery disease, congestive heart failure, hypertension, diabetes, peripheral artery disease).
To explore the interplay between the different domainsof clinical complexity (i.e. frailty, multimorbidity, polypharmacy), the ABC pathway and the risk of outcomes, we
performed a K-medoids cluster analysis with the use of
the partition around medoids cluster algorithm. Optimal
number of clusters was selected according to the averagesilhouette width. We included 4 pre-determined variables in the cluster-analysis (age, frailty index, numberof comorbidities and number of drugs taken), to reflect
the different domains of clinical complexity; each of thesevariables was scaled before clustering. For each cluster,
we reported baseline characteristics and compared categorical and continuous variables as already specified.
We also evaluated the impact of ABC pathway adherencein each cluster identified through Kaplan-Meier and Coxregression analyses.
To further analyse the impact of adherence to the ABC
pathway on the risk of outcomes, we performed a quantile regression to estimate the delay of event (DoE) [24–26] attained in the ABC-adherent group of patients at 6
months, 1 year and 2 years of follow-up. Finally, for theclinical complexity group and the high clinical complexity
cluster, we calculated the number needed to treat (NNT)
along with 95% confidence interval (CI) based on absolute risk reduction at 1 year of follow-up. A two-sided pRomiti et al. BMC Medicine(2022) 20:326

Page 4 of 12< 0.05 was considered statistically significant. All analyses were performed using R 4.1.2 (R Core Team, Vienna,
Austria) for Windows.

Results
Among the 11,096 patients enrolled in the ESC-EHRA
EORP-AF General Long-Term Registry, a total of 9966(89.8%) with complete data available on FI, numberof comorbidities and number of drugs received were
included in this analysis.
Overall, 8289 (83.1%) patients were defined as clinically complex (presenting with at least one of frailty,
multimorbidity and/or polypharmacy). Baseline characteristics of the overall cohort and of the clinically complex, frailty (n=2108), multimorbidity (n=7894) andpolypharmacy (n=5366) subgroups are shown in Additional file 1: Table S2. Overall, higher age and burden ofcomorbidities were associated with each of the complexity domains explored. Among patients with complete
data on ABC adherence (n=6091), less than one-third
clinically complex patients were treated as ABC-pathway
adherent, with frail individuals showing lowest figures
for each ABC criterion, across the clinically complexity
domains explored.

Outcomes in clinically complex and subgroups of frail,
multimorbid and polypharmacy AF patients

Outcomes according to clinical complexity status andin subgroups of frail, multimorbid and polypharmacy
patients during a median follow-up of 730 [IQR: 701–749] days are reported in Additional file 1: Table S3.
Clinically complex AF patients showed increased risk of
all-cause death (adjusted Hazard Ratio [aHR]: 1.97, 95%
CI: 1.40–2.76), MACEs (aHR: 1.49, 95% CI: 1.07–2.06)
and composite outcome (aHR: 1.76, 95% CI: 1.36–2.28),
after adjustment for age, sex, type of AF, anticoagulationand components of ­CHA2DS2-VASc score. Among theclinical complexity subgroups, the highest increase inrisk for all outcomes was observed for frail patients (compared to robust ones), with a 3-fold higher risk of deathand composite outcome, and more than double risk of
MACEs.
Multivariate Cox regression models are summarized inTable 1. Among clinically complex patients, full adherence to the ABC pathway reduced the risk of all-cause
death (aHR: 0.72, 95% CI: 0.58–0.91), MACE (aHR:
0.68, 95% CI: 0.52–0.87) and composite outcome (aHR:
0.70, 95% CI: 0.58–0.85). When compared to patients’adherent to 0 criteria, incremental risk reductions

Table 1 Risk of adverse clinical events and relationship with ABC pathway in clinically complex, frail, multimorbid and polypharmacy
patients (n=6091)
Clinically complex
N=4785Frailty
N=1175Multimorbidity
N=4535

Polypharmacy
N=2934All-cause death
ABC adherent, vs. non-adherent

0.72 [0.58–0.91]

0.63 [0.38–1.04]

0.71 [0.57–0.89]

0.86 [0.66–1.11]

1 ABC criteria, vs. 0

0.53 [0.35–0.78]

0.50 [0.32–0.79]

0.51 [0.34–0.76]

0.52 [0.29–0.95]

2 ABC criteria, vs. 0

0.34 [0.23–0.50]

0.37 [0.23–0.58]

0.32 [0.21–0.47]

0.39 [0.22–0.69]

3 ABC criteria, vs. 0

0.29 [0.19–0.44]

0.28 [0.15–0.53]

0.27 [0.18–0.42]

0.37 [0.20–0.68]

For each criteria

0.69 [0.62–0.78]

0.67 [0.56–0.80]

0.68 [0.60–0.76]

0.80 [0.68–0.93]

2–3 ABC criteria, vs. 0–1

0.56 [0.47–0.68]

0.61 [0.46–0.81]

0.55 [0.45–0.66]

0.68 [0.53–0.88]

MACE
ABC adherent, vs. non-adherent

0.68 [0.52–0.87]

0.88 [0.54–1.42]

0.69 [0.53–0.88]

0.80 [0.60–1.06]

1 ABC criteria, vs. 0

0.69 [0.42–1.12]

0.57 [0.33–0.98]

0.64 [0.39–1.06]

0.63 [0.29–1.33]

2 ABC criteria, vs. 0

0.45 [0.28–0.74]

0.41 [0.23–0.71]

0.44 [0.27–0.71]

0.58 [0.28–1.20]

3 ABC criteria, vs. 0

0.36 [0.21–0.60]

0.44 [0.22–0.85]

0.35 [0.21–0.58]

0.48 [0.23–1.02]

For each criteria

0.71 [0.62–0.81]

0.75 [0.61–0.92]

0.71 [0.63–0.82]

0.85 [0.72–1.00]

2–3 ABC criteria, vs. 0–1

0.59 [0.47–0.73]

0.66 [0.48–0.91]

0.60 [0.48–0.75]

0.83 [0.61–1.12]

Composite outcome
ABC adherent, vs. non-adherent

0.70 [0.58–0.85]

0.75 [0.50–1.12]

0.70 [0.58–0.85]

0.82 [0.66–1.03]

1 ABC criteria, vs. 0

0.65 [0.45–0.95]

0.62 [0.40–0.95]

0.61 [0.42–0.90]

0.58 [0.33–1.00]

2 ABC criteria, vs. 0

0.43 [0.30–0.63]

0.46 [0.30–0.70]

0.41 [0.28–0.59]

0.46 [0.27–0.78]

3 ABC criteria, vs. 0

0.35 [0.24–0.52]

0.41 [0.24–0.71]

0.33 [0.22–0.49]

0.41 [0.23–0.71]

For each criteria

0.72 [0.65–0.79]

0.74 [0.63–0.87]

0.71 [0.64–0.79]

0.81 [0.71–0.92]

2–3 ABC criteria, vs. 0–1

0.59 [0.50–0.70]

0.66 [0.52–0.85]

0.59 [0.50–0.70]

0.72 [0.57–0.90]

Legend: HR [95%CI] adjusted for age, sex, type of AF, hypertension, diabetes, congestive heart failure, coronary artery disease, peripheral artery disease and previous
thromboembolism

Romiti et al. BMC Medicine(2022) 20:326

were observed as the number of ABC-adherent criteria
increased.
We observed consistent trends in the multimorbidityand frailty group, consistent with the primary analysis
above. In frail patients, adherence to each additional criterion was associated with a significant reduction in allcause death (HR: 0.67, 95%CI: 0.56–0.80), MACE (HR:0.75, 95%CI 0.61–0.92) and the composite outcome (HR:0.74, 95%CI: 0.63–0.87). In the polypharmacy group, we
did not observe any statistically significant associations
between complete adherence to ABC pathway and outcomes; however, patients that were adherent to at least
2 ABC criteria were at lower risk of all-cause death (HR:0.68, 95%CI: 0.53–0.88) and the composite outcome (HR:0.72, 95%CI 0.57–0.90), but not MACE (HR 0.83, 95%CI:
0.61–1.12).
Cluster analysis

Using a k-medoids cluster analysis, we identified 2 as
the number of optimal clusters, according to the averagesilhouette width method. Baseline characteristics of the

Page 5 of 12

population according to the cluster grouping are shown
in Additional file 1: Table S4.
Cluster 1 included patients with ‘high clinical complexity’, with 45% of patients being frail (median FI: 0.24,[IQR 0.20–0.29]), while cluster 2 included patients with‘moderate clinical complexity’, with 64% being pre-frail(median FI: 0.12, IQR [0.09–0.16]). Prevalence of multimorbidity and polypharmacy was higher in cluster 1(number of comorbidities: median (IQR), 5 [4–6] vs. 2[1–3], p < 0.001; numbers of drugs 6 [5–7] vs. 4 [3–5], p< 0.001). Patients in the high clinical complexity cluster
were older and more likely female, with higher thromboembolic and bleeding risks, and were less ABC adherent(23.4% vs. 35.1%, p < 0.001).
Kaplan-Meier curves for all-cause death, MACE
and the composite outcome according to clusters areshown in Figure 1 and Additional File 1: Figure S1 andS2, respectively. Patients in the high clinical complexity
cluster showed higher rates of all the outcomes investigated (p<0.001 for all; Table 2). Compared to the moderate complexity cluster, patients in the high clinicalcomplexity cluster showed an increased risk of all-cause

Fig. 1 Kaplan Meier Curves for the risk of all-cause death according to cluster analysis. Legend: p-value for log-rank test

Romiti et al. BMC Medicine(2022) 20:326

Page 6 of 12

Table 2 Risk of adverse clinical events and relationship with ABC
pathway, according to cluster (n=6091)
High clinicalcomplexity
cluster
N=2398Moderate clinicalcomplexity cluster
N=3693All-cause death, n (%)

363 (15.1)

172 (4.6)

ABC adherent, vs. nonadherent

0.74 [0.56–0.98] 0.83 [0.59–1.16]

1 ABC criteria, vs. 0

0.54 [0.34–0.84] 0.42 [0.18–1.01]

2 ABC criteria, vs. 0

0.36 [0.23–0.56] 0.32 [0.14–0.73]

3 ABC criteria, vs. 0

0.32 [0.20–0.52] 0.29 [0.12–0.69]

For each criteria

0.71 [0.62–0.82] 0.79 [0.64–0.96]

2–3 ABC criteria, vs. 0–1

0.60 [0.48–0.75] 0.67 [0.47–0.96]

MACE, n (%)

375 (15.6)

203 (5.5)

ABC adherent, vs. nonadherent

0.80 [0.60–1.08]

0.58 [0.39–0.85]

1 ABC criteria, vs. 0

0.63 [0.36–1.09]

0.62 [0.24–1.60]

2 ABC criteria, vs. 0

0.45 [0.26–0.78] 0.41 [0.16–1.03]

3 ABC criteria, vs. 0

0.41 [0.23–0.74] 0.27 [0.10–0.70]

For each criteria

0.77 [0.66–0.90] 0.65 [0.53–0.81]

2–3 ABC criteria, vs. 0–1

0.66 [0.51–0.85] 0.55 [0.38–0.79]

Composite outcome, n (%)

554 (23.1)

ABC adherent, vs. nonadherent

0.76 [0.60–0.96] 0.70 [0.54–0.92]

320 (8.7)

1 ABC criteria, vs. 0

0.62 [0.40–0.94] 0.65 [0.29–1.42]

2 ABC criteria, vs. 0

0.44 [0.29–0.66] 0.46 [0.21–1.00]

3 ABC criteria, vs. 0

0.38 [0.25–0.60] 0.36 [0.16–0.80]

For each criteria

0.75 [0.66–0.85] 0.74 [0.63–0.87]

2–3 ABC criteria, vs. 0–1

0.64 [0.53–0.78] 0.63 [0.48–0.84]

Legend: HR [95%CI] adjusted for age, sex, type of AF, hypertension, diabetes,
congestive heart failure, coronary artery disease, peripheral artery disease andprevious thromboembolism

death (aHR 1.92, 95%CI 1.59–2.32), MACEs (aHR 1.95,
95%CI 1.57–2.42) and the composite outcome (aHR 1.87,
95%CI: 1.59–2.19), after adjustment for age, sex, components of ­CHA2DS2-VASc score, use of anticoagulant andtype of AF.
Cox regression analyses (Table 2) showed that in thehigh clinical complexity cluster, adherence to ABC pathway was associated with reduced risk of all-cause death(aHR: 0.74, 95%CI: 0.56–0.98) and the composite outcome (aHR: 0.76, 95%CI: 0.60–0.96) but not MACE.
Adherence to an increasing number of ABC criteria wasassociated with risk reductions for all outcomes. Adherence to at least 2 ABC criteria was associated with a lower
risk of all events when compared to subjects’ adherent to
0 or 1 criteria.
In the moderate complexity cluster, full ABC pathway
adherence was associated with a significant reductionin the risk of MACE and composite outcome, but not
all-cause death; however, adherence to at least 2 ABC

criteria was associated with a significant reduction of therisk of all-cause death when compared to patients adherent to 0–1 criteria.
Delay of event analysis and NNT

In clinically complex patients, ABC-adherent management resulted in a significant delay of all events investigated: at 1-year follow-up, ABC adherent patients gained
402 [95%CI: 242–1018] days of survival, 396 [95%CI:
57–573] days of MACE-free time and 385 [95%CI: 303–491] days of composite outcome-free time (Table 3).
Based on absolute risk reduction at 1 year of follow-up,
the NNTs for ABC pathway adherence was 24 (95%CI:
18–37) for all-cause death, 31 (95%CI: 22–56) for MACEs
and 20 (95%CI: 15–31) for the composite outcome. Similar trends were noted in the different subgroups of frailty,
multimorbidity and polypharmacy.
When analysing the DoEs, individuals in the high clinical complexity cluster who were adherent to the ABCpathway showed gain of event-free survival for all theoutcomes at most time-points investigated (Figure 2 forall-cause mortality and Additional File 1: Figure S3 andS4 for MACE and composite outcome, respectively). At
1 year of follow-up, the ABC-adherent NNT in the highclinical complexity cluster was 21 (95%CI: 14–44) for
all-cause death, 34 (95%CI: 19–250) for MACEs, and 22(95%CI: 13–67) for the composite outcome.

Discussion
Our results show that clinically complex AF patients havea poor prognosis, encompassed by an increased risk of
all the outcomes investigated, including death, MACE
and composite outcome. Our principal findings were as
follows: (i) adherence to the ABC pathway in the clinically complex group reduced the risk of all-cause death,
MACE and the composite outcome; (ii) these findings
were further confirmed by the cluster analysis, and theDoE data whereby an ABC-adherent approach resulted
in significant gains in event-free survival for all the outcomes investigated; and (iii) the NNTs for ABC pathway
adherence was 24 for all-cause death, 31 for MACEs
and 20 for the composite outcome at 1 year of follow-up(Fig. 3).
In this study, we provide the first systematic assessment of the efficacy of a comprehensive and integrated
approach (the ABC pathway) for the management of AF
patients, in clinically complex patients. Consistent withour ‘proof of concept’ post hoc analysis from an (old)
AFFIRM trial dataset [15], ABC-adherent management
reduced the risk of all-cause death, MACE and composite outcome among clinically complex patients, and themagnitude of the effect increased with the number of theABC criteria fulfilled. With the use of K-medoids cluster

Romiti et al. BMC Medicine(2022) 20:326

Page 7 of 12

Table 3 Delay of event analysis, ABC adherent vs. non adherent (n=6091)
Clinically complex
N=4785Frailty
N=1175Multimorbidity
N=4535

Polypharmacy
N=2934High clinicalcomplexity
cluster
N=23986 months

430 [284–613]

350 [142–736]

456 [297–608]

264 [77–427]

302 [117–485]

1 year402 [242–1018]NA

405 [232–970]

342 [204–521]

359 [211–531]

2 years

214 [40–776]NA

214 [36–784]

296 [194–472]

318 [60–529]

6 months

330 [180–464]

116 [−120 to 370]

258 [110–424]

151 [−8 to 321]

161 [31–307]

1 year396 [57–573]

151 [−181 to 554]

395 [140–586]

317 [143–502]

275 [87–467]

2 years

197 [−301 to 395]

23 [−94 to 181]

194 [−342 to 432]

200 [55–393]

200 [−46 to 365]

6 months

305 [65–544]

141 [−12 to 361]

311 [31–538]

157 [29–289]

189 [70–356]

1 year385 [303–491]

275 [−24 to 626]

384 [305–490]

310 [177–422]

324 [159–481]

2 years

194 [−181 to 426]NA

197 [−147 to 422]

200 [24–379]

189 [36–356]

All-cause death

MACE

Composite outcome

Legend: The estimates are for the delay of event in the ABC adherent subgroup, calculated at each time point and according to survival in the ABC non-adherent
subgroup (and expressed as days free of the respective outcome). NA not available

Fig. 2 Delay of event analysis for all-cause death, ABC adherent vs. non-adherent in high-complexity cluster subgroup. Legend: DoE, delay of event.
Figures reported are estimates [95% confidence intervals]

Romiti et al. BMC Medicine(2022) 20:326

Page 8 of 12

Fig. 3 Central Illustration (Created with Biorender.com)

analysis, we were able to show the beneficial impact of
the ABC adherent approach according to different levelsof overall complexity, reflecting the real-world scenario of
patients with interacting frailty, multimorbidity and polypharmacy. Also, using a DoE analysis approach, ABCadherent clinically complex AF patients had a meaningful
gain in event-free survival.
For our primary analysis, we defined clinical complexity according to three domains (i.e. frailty, multimorbidity and/or polypharmacy). Our manuscript is also thefirst to analyse the efficacy of an integrated care approach
among three domains of clinical complexity, which areclosely but not interchangeable [1]; these three entities capture different expressions of clinical complexity,
which often coexist and act synergistically in real-world
patients, leading to worse outcomes. The strength of thisapproach is to consider clinical complexity as a whole
entity, encompassing not only the presence of multiple
risk factors, but also the accumulation of deficits and thecomplexities arising from polypharmacy, an often-underestimated issue in AF patients.
In the real world, the presence of frailty, multimorbidity and/or polypharmacy tend to cluster, and the resultsof our cluster analysis are particularly important giventhat AF patients often present with a multifaceted interplay between different complexity criteria, leading to asynergistic detrimental effect. Indeed, the high clinicalcomplexity cluster identified a group of AF patients (45%frail, virtually all burdened by multimorbidity, and thevast majority (83%) treated with 5 or more drugs) for
whom—given the poor prognosis—there is an urgent
need for effective interventions.
Management according to the ABC pathway provided
approximately 30% reduction of the risk of all outcomes;
the magnitude of the effect was even greater when comparing patients who were adherent to all the ABC criteria with those who were completely non-adherent, with a
65 to 71% reduction in the risk of death, MACE and composite outcome. Indeed, based on absolute risk reduction
at 1 year of follow-up, the NNTs for ABC pathway adherence show how implementation of an ABC approach can
avoid one death or the composite outcome in approximately every 20 patients who were clinically complex orin the high complexity cluster, while slightly higher figures were found for MACE events. The usefulness of the
ABC approach is further reinforced by the DoE analysis.
Indeed, an ABC-adherent approach resulted in morethan 12 months delay of all outcomes in the clinicallycomplex group at 1 year of follow-up, even in the highcomplexity cluster.
Our results are aligned with the findings of the main
analysis on the effect of the ABC-pathway in the ESCEHRA EORP Long Term Registry [14] and reinforce theimportance of a comprehensive management in the careRomiti et al. BMC Medicine(2022) 20:326

of clinically complex AF patients [15]. To date, awarenessof the effect of frailty [5, 27], multimorbidity [4, 28, 29]
and polypharmacy [3] in AF patients is increasing, withcompelling evidence on their detrimental effects on quality of care, efficacy of treatment and finally adverse outcomes [2, 4, 29]. However, there is still limited data on
how to handle complexity in clinical practice. In recent
years, there has been a shift from the focus on single
comorbidities (while important in determining the risk ofoutcomes in AF patients [30–32]), to that on multimorbidity in influencing clinical management and outcomes[4, 6, 29, 33]. In this real-world analysis from a large
contemporary European AF cohort, we show that themain issue is not exclusively the burden of diseases (northe impairment of functionality or the burden of medications), but the overall higher clinical complexity, irrespective of which are the main components, in directly
influencing the prognosis of AF patients.
Our findings have several important clinical implications. First, clinical complexity is common among thegeneral AF population and needs awareness and specific strategies to tackle the higher risks associated withthis state. Second, the proportion of clinically complex
patients adherent to the ABC pathway was unsatisfactory among all the clinical complexity domains explored,
especially so in the high complexity cluster. Given thebeneficial clinical outcomes with ABC pathway adherenc
e[17], this should lead to proactive strategies to improve
the adoption of integrated care management in thesesubgroups of patients, as advocated in other complex
chronic long-term conditions [34, 35]. Third, adherence
to the ABC pathway was effective in reducing the risk ofmajor outcomes, with a clear trend towards greater benefit with increasing ABC criteria attained, resulting in
longer event-free survival with ABC-adherence. These
improvements would impact on quality of life and healthcare-associated costs, which are highly relevant given theincreasing burden of AF on healthcare systems [36].
Limitations

Our analysis has some limitations. The observational
design and the limited power to evaluate subgroups
that were not specified in the original study design may
limit the generalizability of our findings; however, wehave analysed more than 6000 patients with complete
data on the ABC pathway, this contributing to the reliability of our estimates. Furthermore, we have provided
extensive adjustment of our analyses on the evaluation of
the effect of the ABC pathway on the risk of outcomes.
While we cannot exclude the contribution of other unaccounted bias, which may have contributed to the resultspresented, our results are consistent with previous evidence on the effect of ABC pathway in similar scenarios,

Page 9 of 12

this further reinforcing our results [15, 37]. Finally, ourcohort was established across European countries andmay not completely reflect other AF populations; therefore, our results may not be immediately applicable toother cohorts and require further evaluation in othergeographical settings.

Conclusions
An ABC-adherent approach reduces the risk of major
outcomes in AF patients characterized by clinical features of complexity (i.e. frailty, multimorbidity and polypharmacy). Ensuring adherence to the ABC pathway isessential to improve clinical outcomes among clinicallycomplex AF patients.
Abbreviations
ABC: Atrial fibrillation Better Care; ACE: Angiotensin-converting enzyme; AF:
Atrial fibrillation; CAD: Coronary artery disease; CI: Confidence interval; DoE:
Delay of event; EHRA: European Heart Rhythm Association; EORP: EURObservational Research Programme; ESC: European Society of Cardiology; FI:
Frailty index; HF: Heart failure; HR: Hazard ratio; IQR: Interquartile range; MACE:
Major adverse cardiovascular event; NNT: Number needed to treat; NOAC:
Non-vitamin K antagonist oral anticoagulant; OAC: Oral anticoagulant; PAD:
Peripheral artery disease; SD: Standard deviation; TIA: Transient ischaemic
attack; VKA: Vitamin K antagonist.

Supplementary Information
The online version contains supplementary material available at https://​doi.​
org/​10.​1186/​s12916-​022-​02526-7.
Additional file 1: Table S1. Items Included into the Frailty Index.
Table S2. Baseline Characteristics of the Cohort. Table S3. Cox Regression for the risk of major outcomes according to clinical complexity andsubgroups. Table S4. Baseline characteristics according to cluster allocation. Figure S1. Kaplan Meier Curves for the risk of MACE according tocluster analysis. Figure S2. Kaplan Meier Curves for the risk of composite
outcome according to cluster analysis. Figure S3. Delay of Event analysis
for MACE, ABC adherent vs. non-adherent in cluster 1 subgroup. Figure
S4. Delay of Event analysis for Composite Outcome, ABC adherent vs. nonadherent in cluster 1 subgroup.
Acknowledgements
EORP Oversight Committee, Executive and Steering Committees (National
Coordinators) of the EURObservational Research Programme (EORP)—Atrial
Fibrillation General Long-Term (EORP-AFGen LT) Registry of the European Society of Cardiology (ESC). Data collection was conducted by the EORP department by Patti-Ann McNeill as Project Officer and Viviane Missiamenou as DataManager. Overall activities were coordinated and supervised by Doctor Aldo P.
Maggioni (EORP Scientific Coordinator).
EURObservational Research Programme Atrial Fibrillation (EORP-AF) Long-Term
General Registry Investigators
Executive committee: G. Boriani (Chair), G.Y.H. Lip, L. Tavazzi, A. P. Maggioni,
G-A. Dan, T. Potpara, M. Nabauer, F. Marin, Z. Kalarus, L. Fauchier, R. Ferrari, A.
Shantsila.
Steering Committee (National Coordinators): A. Goda, University Hospital Center‘Mother Tereza’, Tirana, Albania; G. Mairesse, Cliniques du Sud-Luxembourg, Arlon,
Belgium; T. Shalganov, National Heart Hospital, Sofia, Bulgaria; L. Antoniades, Nicosia General Hospital, Latsia, Cyprus; M. Taborsky, University Hospital
Olomouc, Olomouc, Czech Republic; S. Riahi, Aalborg University Hospital, Aalborg,
Denmark; P. Muda, University of Tartu, Tartu, Estonia; I. García Bolao, Navarra
Institute for Health Research, Pamplona, Spain; O. Piot, Centre Cardiologique duRomiti et al. BMC Medicine(2022) 20:326

Nord, Saint-Denis, France; M. Nabauer, Ludwig-Maximilians-University, Munich,Germany; K. Etsadashvili, G. Chapidze Emergency Cardiology Center, Tbilisi,
Georgia; EN. Simantirakis, University Hospital of Heraklion, School of Medicine,
University of Crete, Heraklion, Crete, Greece; M. Haim, Soroka Medical Center, Beer
Sheva, Israel; A. Azhari, J. Najafian, Cardiovascular Research Institute, Isfahan
University of Medical Sciences, Isfahan, Iran; M. Santini, San Filippo Neri Hospital,
Rome, Italy; E. Mirrakhimov, National Center of Cardiology and Internal Medicine,
Bishkek, Kyrgyzstan; K. Kulzida, Scientific-Research Institute of Cardiology andInternal Diseases, Almaty, Republic of Kazakhstan; A. Erglis, Pauls Stradins Clinical
University Hospital University of Latvia Riga Latvia; L. Poposka, University Clinic of
Cardiology, Faculty of Medicine, Ss Cyril and Methodius University of Skopje, Skopje,
Republic of Macedonia; MR. Burg, Mater Dei Hospital, Triq Dun Karm Psaila,
Malta; H. Crijns, Ö. Erküner, Cardiovascular Research Institute Maastricht (CARIM),
Maastricht University Medical Centre, Maastricht, The Netherlands; D. Atar, Oslo
University Hospital Ullevål and Institute of Clinical Sciences, University of Oslo,
Oslo, Norway; R. Lenarczyk, Silesian Center for Heart Disease, Zabrze, Poland; M.
Martins Oliveira, Hospital Santa Marta, Lisbon, Portugal; D. Shah, Department ofMedicine Specialities, University Hospital Geneva, Geneva, Switzerland; G-A. Dan,
Colentina University Hospital, Bucharest, Romania; E. Serdechnaya, Northern
State Medical University, Arkhangelsk, Russia; T. Potpara, Cardiology Clinic, ClinicalCenter of Serbia, Belgrade, Serbia; E. Diker, Başakşehir Çam and Sakura City Hospital, Istanbul, Turkey; G.Y.H. Lip, D. Lane; City Hospital, University of Birmingham,
Birmingham, United Kingdom.
Investigators: Albania—Durrës: E. Zëra; Tirana: U. Ekmekçiu, V. Paparisto, M. Tase;
Tirana: H. Gjergo, J. Dragoti, A. Goda. Belgium—Bastogne: M. Ciutea, N. Ahadi,
Z. el Husseini, M. Raepers; Gilly: J. Leroy, P. Haushan, A. Jourdan; Haine Saint
Paul: C. Lepiece; Hasselt: L. Desteghe, J. Vijgen, P. Koopman, G. Van Genechten,
H. Heidbuchel; Kortrijk: T. Boussy, M. De Coninck, H. Van Eeckhoutte, N.
Bouckaert; La Louviere: A. Friart, J. Boreux, C. Arend; Liege: P. Evrard; Liège: L.
Stefan, E. Hoffer, J. Herzet, M. Massoz; Liège: C. Celentano, M. Sprynger, L.
Pierard; Liège: P. Melon; Overpelt: B. Van Hauwaert, C. Kuppens, D. Faes, D. Van
Lier, A. Van Dorpe; Waremme: A. Gerardy; Yvoir: O. Deceuninck, O. Xhaet, F.
Dormal, E. Ballant, D. Blommaert. Bulgaria—Pleven: D. Yakova, M. Hristov, T.
Yncheva, N. Stancheva, S. Tisheva; Plovdiv: M. Tokmakova, F. Nikolov, D.
Gencheva; Sofia: T. Shalganov, B. Kunev, M. Stoyanov; Sofia: D. Marchov, V.
Gelev, V. Traykov; Varna: A. Kisheva, H. Tsvyatkov, R. Shtereva, S. Bakalska-Georgieva, S. Slavcheva, Y. Yotov. Czech Republic—Ústí nad Labem: M. Kubíčková.
Denmark—Aalborg: A. Marni Joensen, A. Gammelmark, L. Hvilsted Rasmussen,
P. Dinesen, S. Riahi, S. Krogh Venø, B. Sorensen, A. Korsgaard, K. Andersen, C.
Fragtrup Hellum; Esbjerg: A. Svenningsen, O. Nyvad, P. Wiggers; Herning: O.
May, A. Aarup, B. Graversen, L. Jensen, M. Andersen, M. Svejgaard, S. Vester, S.
Hansen, V. Lynggaard. Estonia— Tallinn: R. Vettus; Tartu: P. Muda. Elche,
Alicante: A. Maestre; Toledo: S. Castaño. France—Abbeville: S. Cheggour;
Abbeville: J. Poulard, V. Mouquet, S. Leparrée; Aix-en-Provence: J. Bouet, J.
Taieb; Amiens: A. Doucy, H. Duquenne; Angers: A. Furber, J. Dupuis, J.
Rautureau; Aurillac: M. Font, P. Damiano; Avignon Cedex: M. Lacrimini; Brest: J.
Abalea, S. Boismal, T. Menez, J. Mansourati; Chartres: G. Range, H. Gorka, C.
Laure, C. Vassalière; Creteil: N. Elbaz, N. Lellouche, K. Djouadi; Montpellier: F.
Roubille, D. Dietz, J. Davy; Nimes: M. Granier, P. Winum, C. Leperchois-Jacquey;
Paris: H. Kassim, E. Marijon, J. Le Heuzey; Paris: J. Fedida, C. Maupain, C.
Himbert, E. Gandjbakhch, F. Hidden-Lucet, G. Duthoit, N. Badenco, T. Chastre,
X. Waintraub, M. Oudihat, J. Lacoste, C. Stephan; Pau: H. Bader, N. Delarche, L.
Giry; Pessac: D. Arnaud, C. Lopez, F. Boury, I. Brunello, M. Lefèvre, R. Mingam, M.
Haissaguerre; Rennes: M. Le Bidan, D. Pavin, V. Le Moal, C. Leclercq; Saint Denis:
O. Piot, T. Beitar; Saint Etienne: I. Martel, A. Schmid, N. Sadki, C. RomeyerBouchard, A. Da Costa; Tours: I. Arnault, M. Boyer, C. Piat, L. Fauchier. FYR
Macedonia—Bitola: N. Lozance, S. Nastevska; Ohrid: A. Doneva, B. Fortomaroska Milevska, B. Sheshoski, K. Petroska, N. Taneska, N. Bakrecheski; Skopje: K.
Lazarovska, S. Jovevska, V. Ristovski, A. Antovski; Skopje: E. Lazarova, I. Kotlar, J.
Taleski, L. Poposka, S. Kedev; Skopje: N. Zlatanovik; Štip: S. Jordanova, T.
Bajraktarova Proseva, S. Doncovska. Georgia—Tbilisi: D. Maisuradze, A. Esakia, E.
Sagirashvili, K. Lartsuliani, N. Natelashvili, N. Gumberidze, R. Gvenetadze; Tbilisi:
K. Etsadashvili, N. Gotonelia, N. Kuridze; Tbilisi: G. Papiashvili, I. Menabde.
Germany—Aachen: S. Glöggler, A. Napp, C. Lebherz, H. Romero, K. Schmitz, M.
Berger, M. Zink, S. Köster, J. Sachse, E. Vonderhagen, G. Soiron, K. Mischke; Bad
Reichenhall: R. Reith, M. Schneider; Berlin: W. Rieker; Biberach: D. Boscher, A.
Taschareck, A. Beer; Boppard: D. Oster; Brandenburg: O. Ritter, J. Adamczewski,
S. Walter; Chemnitz: A. Frommhold, E. Luckner, J. Richter, M. Schellner, S.
Landgraf, S. Bartholome; Chemnitz: R. Naumann, J. Schoeler; Dachau: D.
Westermeier, F. William, K. Wilhelm, M. Maerkl; Detmold: R. Oekinghaus, M.
Denart, M. Kriete, U. Tebbe; Ebersbach: T. Scheibner; Erlangen: M. Gruber, A.

Page 10 of 12

Gerlach, C. Beckendorf, L. Anneken, M. Arnold, S. Lengerer, Z. Bal, C. Uecker, H.
Förtsch, S. Fechner, V. Mages; Friedberg: E. Martens, H. Methe; Göttingen: T.
Schmidt; Hamburg: B. Schaeffer, B. Hoffmann, J. Moser, K. Heitmann, S. Willems,
S. Willems; Hartmannsdorf: C. Klaus, I. Lange; Heidelberg: M. Durak, E. Esen;
Itzehoe: F. Mibach, H. Mibach; Kassel: A. Utech; Kirchzarten: M. Gabelmann, R.
Stumm, V. Ländle; Koblenz: C. Gartner, C. Goerg, N. Kaul, S. Messer, D.
Burkhardt, C. Sander, R. Orthen, S. Kaes; Köln: A. Baumer, F. Dodos; Königsbrück:
A. Barth, G. Schaeffer; Leisnig: J. Gaertner, J. Winkler; Leverkusen: A. Fahrig, J.
Aring, I. Wenzel; Limburg: S. Steiner, A. Kliesch, E. Kratz, K. Winter, P. Schneider;
Ludwigsburg: A. Haag, I. Mutscher, R. Bosch; Markkleeberg: J. Taggeselle, S.
Meixner; Meissen: A. Schnabel; Meppen: A. Shamalla, H. Hötz, A. Korinth;Merzig: C. Rheinert; Moosburg: G. Mehltretter; Mühldorf: B. Schön, N. Schön, A.
Starflinger, E. Englmann; Munich: G. Baytok, T. Laschinger, G. Ritscher; Munich:
A. Gerth; Münster: D. Dechering, L. Eckardt; Nienburg: M. Kuhlmann, N.
Proskynitopoulos; Paderborn: J. Brunn, K. Foth; Pirna: C. Axthelm, H. Hohensee,
K. Eberhard, S. Turbanisch; Plauen: N. Hassler, A. Koestler; Riesa: G. Stenzel;
Riesa: D. Kschiwan, M. Schwefer, S. Neiner, S. Hettwer; Rotenburg a.d. Fulda: M.
Haeussler-Schuchardt, R. Degenhardt, S. Sennhenn, S. Steiner; Starnberg: M.
Brendel; Westerstede: A. Stoehr, W. Widjaja, S. Loehndorf, A. Logemann, J.
Hoskamp, J. Grundt; Zorneding: M. Block; Zwiesel: R. Ulrych, A. Reithmeier, V.
Panagopoulos. Italy—Bologna: C. Martignani, D. Bernucci, E. Fantecchi, I.
Diemberger, M. Ziacchi, M. Biffi, P. Cimaglia, J. Frisoni, G. Boriani; Firenze: I.
Giannini, S. Boni, S. Fumagalli, S. Pupo, A. Di Chiara, P. Mirone; Modena: E.
Fantecchi, G. Boriani, F. Pesce, C. Zoccali, V.L. Malavasi. Kazakhstan—Almaty: A.
Mussagaliyeva, B. Ahyt, Z. Salihova, K. Koshum-Bayeva. Kyrgyzstan—Bishkek: A.
Kerimkulova, A. Bairamukova, E. Mirrakhimov. Latvia—Riga: B. Lurina, R. Zuzans,
S. Jegere, I. Mintale, K. Kupics, K. Jubele, A. Erglis, O. Kalejs. Malta—Birkirkara: K.
Vanhear, M. Burg, M. Cachia, E. Abela, S. Warwicker, T. Tabone, R. Xuereb.
Montenegro—Podgorica: D. Asanovic, D. Drakalovic, M. Vukmirovic, N. Pavlovic,
L. Music, N. Bulatovic, A. Boskovic. Netherlands—Almere: H. Uiterwaal, N.
Bijsterveld; Amsterdam: J. De Groot, J. Neefs, N. van den Berg, F. Piersma, A.
Wilde; Delfzijl: V. Hagens; Enschede: J. Van Es, J. Van Opstal, B. Van Rennes, H.
Verheij, W. Breukers; Heerenveen: G. Tjeerdsma, R. Nijmeijer, D. Wegink, R.
Binnema; Hengelo: S. Said; Maastricht: Ö. Erküner, S. Philippens, W. van Doorn,
H. Crijns; Rotterdam: T. Szili-Torok, R. Bhagwandien, P. Janse, A. Muskens;s-Hertogenbosch: M. van Eck, R. Gevers, N. van der Ven; Venlo: A. Duygun, B.
Rahel, J. Meeder. Norway—Oslo: A. Vold, C. Holst Hansen, I. Engset, D. Atar.
Poland—Bytom: B. Dyduch-Fejklowicz, E. Koba, M. Cichocka; Cieszyn: A. Sokal,
A. Kubicius, E. Pruchniewicz; Gliwice: A. Kowalik-Sztylc, W. Czapla; Katowice: I.
Mróz, M. Kozlowski, T. Pawlowski, M. Tendera; Katowice: A. Winiarska-Filipek, A.
Fidyk, A. Slowikowski, M. Haberka, M. Lachor-Broda, M. Biedron, Z. Gasior;
Kielce: M. Kołodziej, M. Janion; Kielce: I. Gorczyca-Michta, B. WozakowskaKaplon; Łódź: M. Stasiak, P. Jakubowski, T. Ciurus, J. Drozdz; Łódź: M. Simiera, P.
Zajac, T. Wcislo, P. Zycinski, J. Kasprzak; Nysa: A. Olejnik, E. Harc-Dyl, J. Miarka, M.
Pasieka, M. Ziemińska-Łuć, W. Bujak; Opoczno: A. Śliwiński, A. Grech, J. Morka, K.
Petrykowska, M. Prasał; Opole: G. Hordyński, P. Feusette, P. Lipski, A. Wester;
Radlin: W. Streb; Rzeszów: J. Romanek, P. Woźniak, M. Chlebuś, P. Szafarz, W.
Stanik; Szczecin: M. Zakrzewski, J. Kaźmierczak; Szczecin: A. Przybylska, E.
Skorek, H. Błaszczyk, M. Stępień, S. Szabowski, W. Krysiak, M. Szymańska;Tarnów: J. Karasiński, J. Blicharz, M. Skura; Warsaw: K. Hałas, L. Michalczyk, Z.
Orski, K. Krzyżanowski, A. Skrobowski; Warsaw: L. Zieliński, M. TomaszewskaKiecana, M. Dłużniewski; Warsaw: M. Kiliszek, M. Peller, M. Budnik, P. Balsam, G.
Opolski, A. Tymińska, K. Ozierański, A. Wancerz; Warsaw: A. Borowiec, E. Majos,
R. Dabrowski, H. Szwed; Zabrze: A. Musialik-Lydka; Zabrze: A. Leopold-Jadczyk,
E. Jedrzejczyk-Patej, M. Koziel, R. Lenarczyk, M. Mazurek, Z. Kalarus; Zabrze: K.
Krzemien-Wolska, P. Starosta, E. Nowalany-Kozielska; Zakopane: A.
Orzechowska, M. Szpot, M. Staszel. Portugal—Almada: S. Almeida, H. Pereira, L.
Brandão Alves, R. Miranda, L. Ribeiro; Carnaxide Lisboa: F. Costa, F. Morgado, P.
Carmo, P. Galvao Santos, R. Bernardo, P. Adragão; Santarém: G. Ferreira da Silva,
M. Peres, M. Alves, M. Leal; Vila Real: A. Cordeiro, P. Magalhães, P. Fontes, S. Leão;Viseu: A. Delgado, A. Costa, B. Marmelo, B. Rodrigues, D. Moreira, J. Santos, L.
Santos. Romania—Arad: A. Terchet, D. Darabantiu, S. Mercea, V. Turcin Halka, A.
Pop Moldovan; Brasov: A. Gabor, B. Doka, G. Catanescu, H. Rus, L. Oboroceanu,
E. Bobescu; Bucharest: R. Popescu, A. Dan, A. Buzea, I. Daha, G. Dan, I. Neuhoff;
Bucharest: M. Baluta, R. Ploesteanu, N. Dumitrache, M. Vintila; Bucharest: A.
Daraban, C. Japie, E. Badila, H. Tewelde, M. Hostiuc, S. Frunza, E. Tintea, D.
Bartos; Bucharest: A. Ciobanu, I. Popescu, N. Toma, C. Gherghinescu, D. Cretu,
N. Patrascu, C. Stoicescu, C. Udroiu, G. Bicescu, V. Vintila, D. Vinereanu, M.
Cinteza, R. Rimbas; Iași: M. Grecu; Oradea: A. Cozma, F. Boros, M. Ille, O. Tica, R.
Tor, A. Corina, A. Jeewooth, B. Maria, C. Georgiana, C. Natalia, D. Alin, D.
Dinu-Andrei, M. Livia, R. Daniela, R. Larisa, S. Umaar, T. Tamara, M. Ioachim

Romiti et al. BMC Medicine(2022) 20:326

Popescu; Târgu Mureș: D. Nistor, I. Sus, O. Coborosanu; Timișoara: N.
Alina-Ramona, R. Dan, L. Petrescu; Timișoara: G. Ionescu, I. Popescu, C.
Vacarescu, E. Goanta, M. Mangea, A. Ionac, C. Mornos, D. Cozma, S. Pescariu.
Russian Federation—Arkhangelsk: E. Solodovnicova, I. Soldatova, J. Shutova, L.
Tjuleneva, T. Zubova, V. Uskov; Arkhangelsk: D. Obukhov, G. Rusanova;
Arkhangelsk: I. Soldatova, N. Isakova, S. Odinsova, T. Arhipova; Arkhangelsk: E.
Kazakevich, E. Serdechnaya, O. Zavyalova; Saint-Petersburg: T. Novikova;
Saint-Petersburg: I. Riabaia, S. Zhigalov; Saint-Petersburg: E. Drozdova, I.
Luchkina, Y. Monogarova; Vladivostok: D. Hegya, L. Rodionova, L. Rodionova, V.
Nevzorova; Vladivostok: I. Soldatova, O. Lusanova. Serbia—Belgrade: A.
Arandjelovic, D. Toncev, M. Milanov, N. Sekularac; Belgrade: M. Zdravkovic, S.
Hinic, S. Dimkovic, T. Acimovic, J. Saric; Belgrade: M. Polovina, T. Potpara, B.
Vujisic-Tesic, M. Nedeljkovic; Belgrade: M. Zlatar, M. Asanin; Belgrade: V. Vasic, Z.
Popovic; Belgrade: D. Djikic, M. Sipic, V. Peric, B. Dejanovic, N. Milosevic;
Belgrade: A. Stevanovic, A. Andric, B. Pencic, M. Pavlovic-Kleut, V. Celic;Kragujevac: M. Pavlovic, M. Petrovic, M. Vuleta, N. Petrovic, S. Simovic, Z.
Savovic, S. Milanov, G. Davidovic, V. Iric-Cupic; Niška Banja: D. Simonovic, M.
Stojanovic, S. Stojanovic, V. Mitic, V. Ilic, D. Petrovic, M. Deljanin Ilic, S. Ilic, V.
Stoickov; Pirot: S. Markovic; Šabac: S. Kovacevic. Spain—Alicante: A. García
Fernandez; Benalmadena: A. Perez Cabeza; Córdoba: M. Anguita; Elche,
Alicante: A. Maestre; Toledo: S. Castaño Granada: L. Tercedor Sanchez; Huarte:
E. Mau, J. Loayssa, M. Ayarra, M. Carpintero; Madrid: I. Roldán Rabadan; Murcia:
M. Leal; Murcia: M. Gil Ortega; Murcia: A. Tello Montoliu, E. Orenes Piñero, S.
Manzano Fernández, F. Marín, A. Romero Aniorte, A. Veliz Martínez, M.
Quintana Giner; Madrid: M. Ciudad; Pamplona: G. Ballesteros, M. Palacio, O.
Alcalde, I. García-Bolao; San Juan de Alicante: V. Bertomeu Gonzalez; Santiago
de Compostela: F. Otero-Raviña, J. García Seara, J. Gonzalez Juanatey.
Switzerland—Geneva: N. Dayal, P. Maziarski, P. Gentil-Baron, D. Shah.
Turkey—Adana: M. Koç; Afyon: E. Onrat, I. E. Dural; Ankara: K. Yilmaz, B. Özin;Ankara: S. Tan Kurklu, Y. Atmaca; Ankara: U. Canpolat, L. Tokgozoglu; Ankara: A.
K. Dolu, B. Demirtas, D. Sahin; Ankara: O. Ozcan Celebi, E. Diker; Antalya: G.
Gagirci; Bayraklı/Izmir: U.O.Turk; Bursa: H. Ari; Diyarbakır: N. Polat, N. Toprak;Gaziantep: M. Sucu; Görükle-Bursa: O. Akin Serdar; Istanbul: A. Taha Alper;
Istanbul: A. Kepez; Istanbul: Y. Yuksel; Kurupelit - Samsun: A. Uzunselvi, S. Yuksel,
M. Sahin; Merkez/Düzce: O. Kayapinar; Mersin: T. Ozcan; Sivas: H. Kaya, M. B.
Yilmaz; Trabzon: M. Kutlu; Yüreğir-Adana: M. Demir. UK—Barnstaple: C. Gibbs, S.
Kaminskiene, M. Bryce, A. Skinner, G. Belcher, J. Hunt, L. Stancombe, B.
Holbrook, C. Peters, S. Tettersell; Birmingham: A. Shantsila, D. Lane, K. Senoo, M.
Proietti, K. Russell, P. Domingos, S. Hussain, J. Partridge, R. Haynes, S. Bahadur, R.
Brown, S. McMahon, G. Y H Lip; Blackburn: J. McDonald, K. Balachandran, R.
Singh, S. Garg, H. Desai, K. Davies, W. Goddard; Blackpool: G. Galasko, I.
Rahman, Y. Chua, O. Payne, S. Preston, O. Brennan, L. Pedley, C. Whiteside, C.
Dickinson, J. Brown, K. Jones, L. Benham, R. Brady; Carlisle: L. Buchanan, A.
Ashton, H. Crowther, H. Fairlamb, S. Thornthwaite, C. Relph, A. McSkeane, U.
Poultney, N. Kelsall, P. Rice, T. Wilson; Chertsey: M. Wrigley, R. Kaba, T. Patel, E.
Young, J. Law; Cramlington: C. Runnett, H. Thomas, H. McKie, J. Fuller, S. Pick;
Exeter: A. Sharp, A. Hunt, K. Thorpe, C. Hardman, E. Cusack, L. Adams, M.
Hough, S. Keenan, A. Bowring, J. Watts; Great Yarmouth: J. Zaman, K. Goffin, H.
Nutt; Harrogate: Y. Beerachee, J. Featherstone, C. Mills, J. Pearson, L. Stephenson; Huddersfield: S. Grant, A. Wilson, C. Hawksworth, I. Alam, M. Robinson, S.
Ryan; Macclesfield: R. Egdell, E. Gibson, M. Holland, D. Leonard; Maidstone: B.
Mishra, S. Ahmad, H. Randall, J. Hill, L. Reid, M. George, S. McKinley, L. Brockway,
W. Milligan; Manchester: J. Sobolewska, J. Muir, L. Tuckis, L. Winstanley, P. Jacob,
S. Kaye, L. Morby; Nottingham: A. Jan, T. Sewell; Poole: C. Boos, B. Wadams, C.
Cope, P. Jefferey; Portsmouth: N. Andrews, A. Getty, A. Suttling, C. Turner, K.
Hudson, R. Austin, S. Howe; Redhill: R. Iqbal, N. Gandhi, K. Brophy, P. Mirza, E.
Willard, S. Collins, N. Ndlovu; Rhyl: E. Subkovas, V. Karthikeyan, L. Waggett, A.
Wood, A. Bolger, J. Stockport, L. Evans, E. Harman, J. Starling, L. Williams, V. Saul;
Salisbury: M. Sinha, L. Bell, S. Tudgay, S. Kemp, J. Brown, L. Frost; Shrewsbury: T.
Ingram, A. Loughlin, C. Adams, M. Adams, F. Hurford, C. Owen, C. Miller, D.
Donaldson, H. Tivenan, H. Button; South Shields: A. Nasser, O. Jhagra, B.
Stidolph, C. Brown, C. Livingstone, M. Duffy, P. Madgwick; Southampton: P.
Roberts, E. Greenwood, L. Fletcher, M. Beveridge, S. Earles; Taunton: D.
McKenzie, D. Beacock, M. Dayer, M. Seddon, D. Greenwell, F. Luxton, F. Venn, H.
Mills, J. Rewbury, K. James, K. Roberts, L. Tonks; Torquay: D. Felmeden, W. Taggu,
A. Summerhayes, D. Hughes, J. Sutton, L. Felmeden; Watford: M. Khan, E.
Walker, L. Norris, L. O’Donohoe; Weston-super-Mare: A. Mozid, H. Dymond, H.
Lloyd-Jones, G. Saunders, D. Simmons, D. Coles, D. Cotterill, S. Beech, S. Kidd;
Wolverhampton: B. Wrigley, S. Petkar, A. Smallwood, R. Jones, E. Radford, S.
Milgate, S. Metherell, V. Cottam; Yeovil: C. Buckley, A. Broadley, D. Wood, J.
Allison, K. Rennie, L. Balian, L. Howard, L. Pippard, S. Board, T. Pitt-Kerby.

Page 11 of 12

Authors’ contributions
GFR, MP and GYHL conceived and design the analysis; GFR and MP analysed,interpreted the data and drafted the manuscript; MV, NB, AMF, WYD, LF, FM,
MN, GAD, TSP, GB and GYHL revised the manuscript and gave relevant intellectual contribution. All authors read and approved the final manuscript.
Funding
Since the start of EORP, the following companies have supported the programme: Abbott Vascular Int. (2011–2021), Amgen Cardiovascular (2009–2018), AstraZeneca (2014–2021), Bayer (2009–2018), Boehringer Ingelheim(2009–2019), Boston Scientific (2009–2012), The Bristol Myers Squibb andPfizer Alliance (2011–2016), The Alliance Daiichi Sankyo Europe GmbH and Eli
Lilly and Company (2011–2017), Edwards (2016–2019), Gedeon Richter Plc.
(2014–2017), Menarini Int. Op. (2009–2012), MSD-Merck & Co. (2011–2014),
Novartis Pharma AG (2014–2020), ResMed (2014–2016), Sanofi (2009–2011),
SERVIER (2010–2021), Vifor (2019–2022).
Availability of data and materials
The data that support the findings of this study are available from the corresponding author, upon reasonable request, and after approval of all otherco-investigators.

Declarations
Ethics approval and consent to participate
Patient data were obtained after the signing of a written informed consent
by each patient, following the approval of study protocol by an Institutional
Review Board/Ethic Committee. The study was first approved by the National
Coordinators’ main institutions (listed in the Acknowledgements section) andsubsequently authorized by each peripheral site, under the responsibility of
the lead contact and study team (all listed in the Acknowledgements section),
according to the specific national and local regulation. Any details regarding
approval numbers for the study protocol regarding any specific site could
be obtained from the corresponding authors, upon reasonable request. The
study was performed according to the European Union Note for Guidance on
Good Clinical Practice CPMP/ECH/135/95 and the Declaration of Helsinki.
Consent for publication
Not applicableCompeting interests
MP is an investigator of the AFFIRMO project on multimorbidity in AF, which
has received funding from the European Union’s Horizon 2020 research andinnovation programme under grant agreement No 899871. LF has beena consultant and speaker for AstraZeneca, Bayer, BMS/Pfizer, Boehringer
Ingelheim, Medtronic, Novartis, Novo, XO and Zoll. FM is a consultant for Bayerand Boehringer-Ingelheim; FM received small research’s fees from AFNET,
Ferrer, Astra-Zeneca, Boehringer-Ingelheim and Bayer; FM is an investigatorof the AFFIRMO project on multimorbidity in AF, which has received funding
from the European Union’s Horizon 2020 research and innovation programme
under grant agreement No 899871. TSP is a consultant for Bayer and Pfizer,
with no fees received personally; GB a received small speaker’s fees from
Medtronic, Boston, Boehringer Ingelheim and Bayer; GYHL is a consultant andspeaker for BMS/Pfizer, Boehringer Ingelheim and Daiichi-Sankyo. No fees arereceived personally. GYHL is co-principal investigator of the AFFIRMO projecton multimorbidity in AF, which has received funding from the European
Union’s Horizon 2020 research and innovation programme under grant agreement No 899871.
Author details
1
Liverpool Centre for Cardiovascular Science, University of Liverpool and Liverpool Heart & Chest Hospital, William Henry Duncan Building, 6 West Derby
St, Liverpool L7 8TX, UK. 2 Department of Translational and Precision Medicine,
Sapienza University of Rome, Rome, Italy. 3 Department of Clinical Sciences
and Community Health, University of Milan, Milan, Italy. 4 Geriatric Unit, IRCCS
Istituti Clinici Scientifici Maugeri, Milan, Italy. 5 Cardiology Division, Departmentof Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, Modena, Italy. 6 Clinical and Experimental
Medicine PhD Program, University of Modena and Reggio Emilia, Modena,
Italy. 7 Service de Cardiologie, Centre Hospitalier Universitaire Trousseau, Tours,Romiti et al. BMC Medicine(2022) 20:326

France. 8 Department of Cardiology, Hospital Universitario Virgen de la Arrixaca,
IMIB-Arrixaca, University of Murcia, CIBER-CV, Murcia, Spain. 9 Departmentof Cardiology, Ludwig-Maximilians-University, Munich, Germany. 10 Universityof Medicine, ‘Carol Davila’, Colentina University Hospital, Bucharest, Romania.
11
School of Medicine, University of Belgrade, Belgrade, Serbia. 12 Intensive
Arrhythmia Care, Cardiology Clinic, Clinical Center of Serbia, Belgrade, Serbia.
13
Department of Clinical Medicine, Aalborg University, Aalborg, Denmark.
Received: 18 May 2022 Accepted: 12 August 2022

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