Evidence map›Paper›PMID 32011689›Full record

SynthesisEuropace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology2020

Prediction models for atrial fibrillation applicable in the community: a systematic review and meta-analysis.

Jelle C L Himmelreich, Lieke Veelers, Wim A M Lucassen, Renate B Schnabel, Michiel Rienstra, Henk C P M van Weert, Ralf E Harskamp

Open access · bronzeAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
56citing papers in PubMed, 8 pooled it
6.4field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

56 citing papers in PubMed, 8 syntheses or guidelines pooled it, 93 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 2 countries.

Jelle C L HimmelreichDepartment of General Practice, Amsterdam UMC, University of Amsterdam, Amsterdam Public Health, Meibergdreef 9, 1105 AZ Amsterdam, Netherlands.
Lieke VeelersDepartment of General Practice, Amsterdam UMC, University of Amsterdam, Amsterdam Public Health, Meibergdreef 9, 1105 AZ Amsterdam, Netherlands.
Wim A M LucassenDepartment of General Practice, Amsterdam UMC, University of Amsterdam, Amsterdam Public Health, Meibergdreef 9, 1105 AZ Amsterdam, Netherlands.
Renate B SchnabelDepartment of General and Interventional Cardiology, University Heart Center Hamburg/German Center for Cardiovascular Research, Partner Site Hamburg/Kiel/Luebeck, Martinistrasse 52, 20246 Hamburg, Germany.
Michiel RienstraDepartment of Cardiology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713 GZ Groningen, The Netherlands.
Henk C P M van WeertDepartment of General Practice, Amsterdam UMC, University of Amsterdam, Amsterdam Public Health, Meibergdreef 9, 1105 AZ Amsterdam, Netherlands.
Ralf E HarskampDepartment of General Practice, Amsterdam UMC, University of Amsterdam, Amsterdam Public Health, Meibergdreef 9, 1105 AZ Amsterdam, Netherlands.
Amsterdam University Medical Centers · NLUniversität Hamburg · DEUniversity Medical Center Groningen · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsAtrial fibrillation (AF) is a common arrhythmia associated with an increased stroke risk. The use of multivariable prediction models could result in more efficient primary AF screening by selecting at-risk individuals. We aimed to determine which model may be best suitable for increasing efficiency of future primary AF screening efforts. METHODS AND

resultsWe performed a systematic review on multivariable models derived, validated, and/or augmented for AF prediction in community cohorts using Pubmed, Embase, and CINAHL (Cumulative Index to Nursing and Allied Health Literature) through 1 August 2019. We performed meta-analysis of model discrimination with the summary C-statistic as the primary expression of associations using a random effects model. In case of high heterogeneity, we calculated a 95% prediction interval. We used the CHARMS (Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies) checklist for risk of bias assessment. We included 27 studies with a total of 2 978 659 unique participants among 20 cohorts with mean age ranging from 42 to 76 years. We identified 21 risk models used for incident AF risk in community cohorts. Three models showed significant summary discrimination despite high heterogeneity: CHARGE-AF (Cohorts for Heart and Aging Research in Genomic Epidemiology) [summary C-statistic 0.71; 95% confidence interval (95% CI) 0.66-0.76], FHS-AF (Framingham Heart Study risk score for AF) (summary C-statistic 0.70; 95% CI 0.64-0.76), and CHA2DS2-VASc (summary C-statistic 0.69; 95% CI 0.64-0.74). Of these, CHARGE-AF and FHS-AF had originally been derived for AF incidence prediction. Only CHARGE-AF, which comprises easily obtainable measurements and medical history elements, showed significant summary discrimination among cohorts that had applied a uniform (5-year) risk prediction window.

conclusionCHARGE-AF appeared most suitable for primary screening purposes in terms of performance and applicability in older community cohorts of predominantly European descent.

Indexed as

Atrial FibrillationStrokeAdultAgedHumansIncidenceMiddle AgedRisk AssessmentRisk FactorsAtrial fibrillationCommunityMeta-analysisRisk modelScreeningSystematic review

Identifiers

PMID32011689
PMCPMC7526764
OpenAlexW3004830772

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.