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 .
Subclinical atrial fibrillation and the risk of stroke.
BACKGROUND One quarter of strokes are of unknown cause , and sub clinical atrial fibrillation may be a common etiologic factor . Pacemakers can detect sub clinical episodes of rapid atrial rate , which correlate with electrocardiographically documented atrial fibrillation . We evaluated whether sub clinical episodes of rapid atrial rate detected by implanted devices were associated with an increased risk of ischemic stroke in patients who did not have other evidence of atrial fibrillation . METHODS We enrolled 2580 patients , 65 years of age or older , with hypertension and no history of atrial fibrillation , in whom a pacemaker or defibrillator had recently been implanted . We monitored the patients for 3 months to detect sub clinical atrial tachyarrhythmias ( episodes of atrial rate > 190 beats per minute for more than 6 minutes ) and followed them for a mean of 2.5 years for the primary outcome of ischemic stroke or systemic embolism .  Patients with pacemakers  were r and omly assigned to receive or not to receive continuous atrial overdrive pacing . RESULTS By 3 months , sub clinical atrial tachyarrhythmias detected by implanted devices had occurred in 261 patients ( 10.1 % ) . Sub clinical atrial tachyarrhythmias were associated with an increased risk of clinical atrial fibrillation ( hazard ratio , 5.56 ; 95 % confidence interval [ CI ] , 3.78 to 8.17 ; P<0.001 ) and of ischemic stroke or systemic embolism ( hazard ratio , 2.49 ; 95 % CI , 1.28 to 4.85 ; P=0.007 ) . Of 51 patients who had a primary outcome event , 11 had had sub clinical atrial tachyarrhythmias detected by 3 months , and none had had clinical atrial fibrillation by 3 months . The population attributable risk of stroke or systemic embolism associated with sub clinical atrial tachyarrhythmias was 13 % . Sub clinical atrial tachyarrhythmias remained predictive of the primary outcome after adjustment for predictors of stroke ( hazard ratio , 2.50 ; 95 % CI , 1.28 to 4.89 ; P=0.008 ) . Continuous atrial overdrive pacing did not prevent atrial fibrillation . CONCLUSIONS Sub clinical atrial tachyarrhythmias , without clinical atrial fibrillation , occurred frequently in patients with pacemakers and were associated with a significantly increased risk of ischemic stroke or systemic embolism . ( Funded by St. Jude Medical ; ASSERT Clinical Trials.gov number , NCT00256152 . )
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 .