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

Author summaryWhy was this study done? Atrial fibrillation is a common heart rhythm problem that often has no symptoms, so people are unaware they have this condition. People with atrial fibrillation can have a very high stroke risk if they are not appropriately treated with anticoagulant medications, and this risk increases with age. Screening for atrial fibrillation is recommended in many guidelines, although the precise age distribution and calculated stroke risk of atrial fibrillation detected by screening is not known. Accurate age-specific data are required for cost-effectiveness analysis, to inform the most appropriate age cutoff for screening based on the age distribution of the population to be screened. What did the researchers do and find? Investigators from 19 atrial fibrillation screening studies across the world agreed to collaborate and share patient-level data, providing a combined database of 141,220 people screened and 1,539 screen-detected cases of atrial fibrillation. Our study was able to quantify the yield and stroke risk for atrial fibrillation in 5-year age brackets, showing the exact relationship of how the yield of screening and stroke risk of screen-detected atrial fibrillation increases with age. The yield of screening was not influenced by the screening method used or the recruitment setting, indicating that screening programs can be established based on available resources. To our knowledge, this is the first study to demonstrate the precise relationship of the number that need to be screened to identify one new atrial fibrillation case, or one new atrial fibrillation case in whom anticoagulant treatment is guideline recommended, in 5-year age brackets. What do these findings mean? This study demonstrates the high calculated stroke risk of screen-detected AF and the high proportion with at least one additional stroke risk factor other than age or sex. These data allow for accurate simulations of cost-effectiveness of screening, including sensitivity analyses, based on the age distribution of the population to be screened. Ultimately, these data may be used to assist development of health policy around the development of atrial fibrillation screening programs, tailored to the specific health system and resources available. 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 CHA(2)DS(2)-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 CHA(2)DS(2)-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 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. 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.