Ontology highlight
ABSTRACT: Background
Access to long-term ambulatory recording to detect atrial fibrillation (AF) is limited for economical and practical reasons. We aimed to determine whether 24 h ECG (24hECG) data can predict AF detection on extended cardiac monitoring.Methods
We included all US patients from 2020, aged 17-100 years, who were monitored for 2-30 days using the PocketECG device (MEDICALgorithmics), without AF ≥30 s on the first day (n = 18,220, mean age 64.4 years, 42.4% male). The population was randomly split into equal training and testing datasets. A Lasso model was used to predict AF episodes ≥30 s occurring on days 2-30.Results
The final model included maximum heart rate, number of premature atrial complexes (PACs), fastest rate during PAC couplets and triplets, fastest
SUBMITTER: Johnson LS
PROVIDER: S-EPMC10646379 | biostudies-literature | 2023 Oct
REPOSITORIES: biostudies-literature