SynthesisPLoS medicine2019
Estimated stroke risk, yield, and number needed to screen for atrial fibrillation detected through single time screening: a multicountry patient-level meta-analysis of 141,220 screened individuals.
Synthesis in PLoS medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers, 2 of them syntheses that pooled it.
What it found
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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.
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.
Who cites it
70 citing papers in PubMed, 2 syntheses or guidelines pooled it, 122 citations in OpenAlex.
- Impact of Mobile Health Devices for the Detection of Atrial Fibrillation: Systematic Review.JMIR mHealth and uHealth · 2021Pooled it
- 2021 ISHNE/ HRS/ EHRA/ APHRS collaborative statement on mHealth in Arrhythmia Management: Digital Medical Tools for Heart Rhythm Professionals: From the International Society for Holter and Noninvasive Electrocardiology/Heart Rhythm Society/European Heart Rhythm Association/Asia Pacific Heart Rhythm Society.Annals of noninvasive electrocardiology : the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc · 2021Guideline
- Randomized trial of smartphone application and bed sensor for atrial fibrillation detection in high-risk patients.Scientific reports · 2026Trial
- Screening for Atrial Fibrillation in Older Adults at Primary Care Visits: VITAL-AF Randomized Controlled Trial.Circulation · 2022Trial
- Incidence of atrial fibrillation in elderly patients with type 2 diabetes mellitus.BMJ open diabetes research & care · 2022Trial
- Predictive Accuracy of a Clinical and Genetic Risk Model for Atrial Fibrillation.Circulation. Genomic and precision medicine · 2021Trial
- Opportunistic screening versus usual care for detection of atrial fibrillation in primary care: cluster randomised controlled trial.BMJ (Clinical research ed.) · 2020Trial
- Deep Neural Networks for Automatic Atrial Fibrillation Detection Using Long-Term Ambulatory Electrocardiography: Retrospective Diagnostic Accuracy Study.JMIR cardio · 2026Article
- Multimodal PSOCT-NIRS catheter for guided ablation of atrial fibrillation.Journal of biomedical optics · 2026Article
- Recent-onset atrial fibrillation: challenges and opportunities.European heart journal · 2026Review
- Cost-effectiveness of atrial fibrillation screening programmes across European nations.European heart journal. Quality of care & clinical outcomes · 2026Article
- Atrial Fibrillation Screening in Those with Rheumatic Heart Disease: A Narrative Policy Content Review.Global heart · 2026Review
- Contributions of risk factors, additional yield and number needed to screen to prevalence of diabetes in tuberculosis-exposed households.BMC public health · 2025Article
- Atrial Fibrillation Detected by Handheld ECG and Ischemic Stroke Risk in a 55- to 64-Year-Old Chinese Population.JACC. Asia · 2025Article
- Systematic screening for atrial fibrillation with non-invasive devices: a systematic review and meta-analysis.The Lancet regional health. Europe · 2025Article
- Utility of Routine 24-Hour Electrocardiographic Holter Monitoring for Detecting Atrial Fibrillation in Patients Admitted with Acute Stroke Syndromes.Sultan Qaboos University medical journal · 2025Article
- Subclinical Atrial Fibrillation Screening in Dialytic Chronic Kidney Disease Patients Using Portable Device.Arquivos brasileiros de cardiologia · 2025Article
- 2025 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association.Circulation · 2025Review
- Left atrial size and echocardiographic diastolic parameters as predictors of incident atrial fibrillation in older hospitalized patients.Aging clinical and experimental research · 2025Article
- Challenging the status quo: a scoping review of value-based care models in cardiology and electrophysiology.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 · 2024Article
10 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
39 authors at 20 institutions in 14 countries.
Funding
Abstract
backgroundThe precise age distribution and calculated stroke risk of screen-detected atrial fibrillation (AF) is not known. Therefore, it is not possible to determine the number needed to screen (NNS) to identify one treatable new AF case (NNS-Rx) (i.e., Class-1 oral anticoagulation [OAC] treatment recommendation) in each age stratum. If the NNS-Rx is known for each age stratum, precise cost-effectiveness and sensitivity simulations can be performed based on the age distribution of the population/region to be screened. Such calculations are required by national authorities and organisations responsible for health system budgets to determine the best age cutoffs for screening programs and decide whether programs of screening should be funded. Therefore, we aimed to determine the exact yield and calculated stroke-risk profile of screen-detected AF and NNS-Rx in 5-year age strata. METHODS AND
findingsA systematic review of Medline, Pubmed, and Embase was performed (January 2007 to February 2018), and AF-SCREEN international collaboration members were contacted to identify additional studies. Twenty-four eligible studies were identified that performed a single time point screen for AF in a general ambulant population, including people ≥65 years. Authors from eligible studies were invited to collaborate and share patient-level data. Statistical analysis was performed using random effects logistic regression for AF detection rate, and Poisson regression modelling for CHA2DS2-VASc scores. Nineteen studies (14 countries from a mix of low- to middle- and high-income countries) collaborated, with 141,220 participants screened and 1,539 new AF cases. Pooled yield of screening was greater in males across all age strata. The age/sex-adjusted detection rate for screen-detected AF in ≥65-year-olds was 1.44% (95% CI, 1.13%-1.82%) and 0.41% (95% CI, 0.31%-0.53%) for <65-year-olds. New AF detection rate increased progressively with age from 0.34% (<60 years) to 2.73% (≥85 years). Neither the choice of screening methodology or device, the geographical region, nor the screening setting influenced the detection rate of AF. Mean CHA2DS2-VASc scores (n = 1,369) increased with age from 1.1 (<60 years) to 3.9 (≥85 years); 72% of ≥65 years had ≥1 additional stroke risk factor other than age/sex. All new AF ≥75 years and 66% between 65 and 74 years had a Class-1 OAC recommendation. The NNS-Rx is 83 for ≥65 years, 926 for 60-64 years; and 1,089 for <60 years. The main limitation of this study is there are insufficient data on sociodemographic variables of the populations and possible ascertainment biases to explain the variance in the samples.
conclusionsPeople with screen-detected AF are at elevated calculated stroke risk: above age 65, the majority have a Class-1 OAC recommendation for stroke prevention, and >70% have ≥1 additional stroke risk factor other than age/sex. Our data, based on the largest number of screen-detected AF collected to date, show the precise relationship between yield and estimated stroke risk profile with age, and strong dependence for NNS-RX on the age distribution of the population to be screened: essential information for precise cost-effectiveness calculations.
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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.