Pooled yield of screening was greater in males across all age strata .
Neither the choice of screening methodology or device , the geographical region , nor the screening setting influenced the detection rate of AF .
The main limitation of this study is there are insufficient data on sociodemographic variables of the population s and possible ascertainment biases to explain the variance in the sample s. CONCLUSIONS People 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 .
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 aim ed to determine the exact yield and calculated stroke-risk profile of screen-detected AF and NNS-Rx in 5-year age strata .
Effect of a Home-Based Wearable Continuous ECG Monitoring Patch on Detection of Undiagnosed Atrial Fibrillation: The mSToPS Randomized Clinical Trial
Importance Opportunistic screening for atrial fibrillation ( AF ) is recommended , and improved methods of early identification could allow for the initiation of appropriate therapies to prevent the adverse health outcomes associated with AF . Objective To determine the effect of a self-applied wearable electrocardiogram ( ECG ) patch in detecting AF and the clinical consequences associated with such a detection strategy . Design , Setting , and Participants A direct-to-participant r and omized clinical trial and prospect i ve matched observational cohort study were conducted among members of a large national health plan . Recruitment began November 17 , 2015 , and was completed on October 4 , 2016 , and 1-year cl aims -based follow-up concluded in January 2018 . For the clinical trial , 2659 individuals were r and omized to active home-based monitoring  to start immediately or delayed by 4 months . For the observational study , 2 deidentified age- , sex- and CHA2DS2-VASc – matched controls were selected for each actively monitored individual . Interventions The actively monitored cohort wore a self-applied continuous ECG monitoring patch at home during routine activities for up to 4 weeks , initiated either immediately after enrolling ( n = 1364 ) or delayed for 4 months after enrollment ( n = 1291 ) . Main Outcomes and Measures The primary end point was the incidence of a new diagnosis of AF at 4 months among those r and omized to immediate monitoring vs delayed monitoring . A secondary end point was new AF diagnosis at 1 year in the combined actively monitored groups vs matched observational controls . Other outcomes included new prescriptions for anticoagulants and health care utilization ( outpatient cardiology visits , primary care visits , or AF-related emergency department visits and hospitalizations ) at 1 year . Results The r and omized groups included 2659 participants ( mean [ SD ] age , 72.4 [ 7.3 ] years ; 38.6 % women ) , of whom 1738 ( 65.4 % ) completed active monitoring . The observational study comprised 5214 ( mean [ SD ] age , 73.7 [ 7.0 ] years ; 40.5 % women ; median CHA2DS2-VASc score , 3.0 ) , including 1738 actively monitored individuals from the r and omized trial and 3476 matched controls . In the r and omized study , new AF was identified by 4 months in 3.9 % ( 53/1366 ) of the immediate group vs 0.9 % ( 12/1293 ) in the delayed group ( absolute difference , 3.0 % [ 95 % CI , 1.8%-4.1 % ] ) . At 1 year , AF was newly diagnosed in 109 monitored ( 6.7 per 100 person-years ) and 81 unmonitored ( 2.6 per 100 person-years ; difference , 4.1 [ 95 % CI , 3.9 - 4.2 ] ) individuals . Active monitoring was associated with increased initiation of anticoagulants  ( 5.7 vs 3.7 per 100 person-years ; difference , 2.0 [ 95 % CI , 1.9 - 2.2 ] ) , outpatient cardiology visits ( 33.5 vs 26.0 per 100 person-years ; difference , 7.5 [ 95 % CI , 7.2 - 7.9 ) , and primary care visits ( 83.5 vs 82.6 per 100 person-years ; difference , 0.9 [ 95 % CI , 0.4 - 1.5 ] ) . There was no difference in AF-related emergency department visits and hospitalizations ( 1.3 vs 1.4 per 100 person-years ; difference , 0.1 [ 95 % CI , −0.1 to 0 ] ) . Conclusions and Relevance Among individuals at high risk for AF , immediate monitoring with a home-based wearable ECG sensor patch , compared with delayed monitoring , result ed in a higher rate of AF diagnosis after 4 months . Monitored individuals , compared with nonmonitored controls , had higher rates of AF diagnosis , greater initiation of anticoagulants , but also increased health care re source utilization at 1 year . Trial Registration Clinical Trials.gov Identifier :
Pooled yield of screening was greater in males across all age strata .
Neither the choice of screening methodology or device , the geographical region , nor the screening setting influenced the detection rate of AF .
The main limitation of this study is there are insufficient data on sociodemographic variables of the population s and possible ascertainment biases to explain the variance in the sample s. CONCLUSIONS People 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 .
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 aim ed to determine the exact yield and calculated stroke-risk profile of screen-detected AF and NNS-Rx in 5-year age strata .