6533b85dfe1ef96bd12bddf6

RESEARCH PRODUCT

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.

F. Russell QuinnVivian W Y LeePhilipp S. WildDavid FitzmauriceDavid FitzmauriceWilliam KeenYi ChenYi ChenGeorges H. MairesseJulie W. MartinJuan José Gómez-doblasJake OlivierThomas MünzelJuliet NakamyaFd Richard HobbsNicole LowresJoseph HarbisonBen FreedmanJeff S. HealeyBreda SmythGregory Y.h. LipGregory Y.h. LipAndrea K RoalfeShih Ann ChenShih Ann ChenRoopinder K. SandhuLuis ÁNgel Pérula De TorresTze Fan ChaoTze Fan ChaoJonathan MantAxel Cosmus Pyndt DiederichsenBryan P. YanFemke KaasenbroodLis NeubeckMarco ProiettiMarco ProiettiMarco ProiettiJi-guang WangJi-guang WangDavid D. McmanusDavid D. McmanusJessica OrchardRenate B. SchnabelEnrique Martín-rioboóJes LindholtJavier MuñizRobert G. TielemanApurv Soni

subject

MaleHealth ScreeningEconomicsSocial Sciences030204 cardiovascular system & hematologyVascular MedicineScreening programmeElectrocardiography0302 clinical medicineRisk FactorsHealth careAtrial FibrillationMedicine and Health SciencesMass ScreeningPublic and Occupational Health030212 general & internal medicinemedia_commonAged 80 and overRAge FactorsGeneral MedicineMiddle AgedUniversity hospitalPrognosis3. Good healthStrokeBioassays and Physiological AnalysisNeurologyHealthMedicineFemaleTraining programArrhythmiaResearch ArticleAdultCerebrovascular DiseasesCost-Effectiveness AnalysisCardiologyLibrary scienceResearch and Analysis MethodsRisk AssessmentStroke risk03 medical and health sciencesYoung AdultAge DistributionSex FactorsPopulation MetricsPredictive Value of TestsPolitical sciencemedia_common.cataloged_instanceHumansEarly careerEuropean unionIschemic StrokeAgedHealth Care PolicyPopulation Biologybusiness.industryElectrophysiological TechniquesBiology and Life SciencesNumber needed to screenEconomic AnalysisHealth CareAge GroupsPeople and PlaceseHealthPopulation GroupingsCardiac ElectrophysiologybusinessScreening Guidelines

description

Background The 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 findings A 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 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.

https://www.repository.cam.ac.uk/handle/1810/296426