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.
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.
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Who cites it
56 citing papers in PubMed, 8 syntheses or guidelines pooled it, 93 citations in OpenAlex.
- Development and performance of female breast cancer incidence risk prediction models: a systematic review and meta-analysis.Annals of medicine · 2025Pooled it
- Circulating Proteomics and Risk of Atrial Fibrillation: A Systematic Review of Cohort Studies.Journal of cellular and molecular medicine · 2025Pooled it
- Systematic evaluation of predictive models for futile recanalization before thrombectomy in patients with acute ischemic stroke.Frontiers in neurology · 2025Pooled it
- Prediction models for urinary incontinence after robotic-assisted laparoscopic radical prostatectomy: a systematic review.Journal of robotic surgery · 2024Pooled it
- 2023 ACC/AHA/ACCP/HRS Guideline for the Diagnosis and Management of Atrial Fibrillation: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines.Journal of the American College of Cardiology · 2024Guideline
- Guideline
- Prediction models for post-thrombectomy brain edema in patients with acute ischemic stroke: a systematic review and meta-analysis.Frontiers in neurology · 2023Pooled it
- Prediction of incident atrial fibrillation in community-based electronic health records: a systematic review with meta-analysis.Heart (British Cardiac Society) · 2022Pooled it
- Impact of a clinical atrial fibrillation risk estimation tool on cardiac rhythm monitor utilization following acute ischemic stroke: A prepost clinical trial.American heart journal · 2025Trial
- [The role of psychosocial risk factors in the development and course of atrial fibrillation].Herzschrittmachertherapie & Elektrophysiologie · 2026Review
- Accumulation of chronic conditions in patients aged <65 years diagnosed with atrial fibrillation.Heart rhythm · 2026Article
- Artificial Intelligence for Prediction and Detection of Atrial Fibrillation from Sinus-Rhythm Electrocardiograms and Ambulatory Monitoring.Biomedicines · 2026Review
- CARDIAC-FM: A Multimodal Foundation Model for Cardiovascular Risk Prediction Using ECG and Cardiac MRI.medRxiv : the preprint server for health sciences · 2026Article
- Article
- Active Monitoring for AtriaL FIbrillation (AMALFI): Rationale, protocol, and pilot for a pragmatic, randomized, controlled trial of remote screening for asymptomatic atrial fibrillation.American heart journal · 2025Article
- Machine Learning and Arrhythmia: Advances in Atrial Fibrillation Detection and Management.Current atherosclerosis reports · 2025Review
- Prediction of Atrial Fibrillation From the ECG in the Community Using Deep Learning: A Multinational Study.Circulation. Arrhythmia and electrophysiology · 2025Article
- Are Machine Learning methods effective in detecting undiagnosed atrial fibrillation in primary care settings using electronic health records? A systematic review.PLOS digital health · 2025Article
- Association of life's essential 8 score with incidence of atrial fibrillation: The Framingham heart study.American journal of preventive cardiology · 2025Article
- Machine-learning approach to atrial fibrillation prediction among individuals without prior cardiovascular diseases.Open heart · 2025Article
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
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.
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