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Artificial intelligence-guided screening for atrial fibrillation using electrocardiogram during sinus rhythm: a prospective non-randomised interventional trial.
Noseworthy, Peter A; Attia, Zachi I; Behnken, Emma M; Giblon, Rachel E; Bews, Katherine A; Liu, Sijia; Gosse, Tara A; Linn, Zachery D; Deng, Yihong; Yin, Jun; Gersh, Bernard J; Graff-Radford, Jonathan; Rabinstein, Alejandro A; Siontis, Konstantinos C; Friedman, Paul A; Yao, Xiaoxi.
Afiliación
  • Noseworthy PA; Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA; Robert D and Patricia E Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA. Electronic address: noseworthy.peter@mayo.edu.
  • Attia ZI; Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA.
  • Behnken EM; Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN, USA.
  • Giblon RE; Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
  • Bews KA; Robert D and Patricia E Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA.
  • Liu S; Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, MN, USA.
  • Gosse TA; Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA.
  • Linn ZD; Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA.
  • Deng Y; Robert D and Patricia E Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA.
  • Yin J; Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
  • Gersh BJ; Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA.
  • Graff-Radford J; Department of Neurology, Mayo Clinic, Rochester, MN, USA.
  • Rabinstein AA; Department of Neurology, Mayo Clinic, Rochester, MN, USA.
  • Siontis KC; Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA.
  • Friedman PA; Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA.
  • Yao X; Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA; Robert D and Patricia E Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA.
Lancet ; 400(10359): 1206-1212, 2022 10 08.
Article en En | MEDLINE | ID: mdl-36179758
BACKGROUND: Previous atrial fibrillation screening trials have highlighted the need for more targeted approaches. We did a pragmatic study to evaluate the effectiveness of an artificial intelligence (AI) algorithm-guided targeted screening approach for identifying previously unrecognised atrial fibrillation. METHODS: For this non-randomised interventional trial, we prospectively recruited patients with stroke risk factors but with no known atrial fibrillation who had an electrocardiogram (ECG) done in routine practice. Participants wore a continuous ambulatory heart rhythm monitor for up to 30 days, with the data transmitted in near real time through a cellular connection. The AI algorithm was applied to the ECGs to divide patients into high-risk or low-risk groups. The primary outcome was newly diagnosed atrial fibrillation. In a secondary analysis, trial participants were propensity-score matched (1:1) to individuals from the eligible but unenrolled population who served as real-world controls. This study is registered with ClinicalTrials.gov, NCT04208971. FINDINGS: 1003 patients with a mean age of 74 years (SD 8·8) from 40 US states completed the study. Over a mean 22·3 days of continuous monitoring, atrial fibrillation was detected in six (1·6%) of 370 patients with low risk and 48 (7·6%) of 633 with high risk (odds ratio 4·98, 95% CI 2·11-11·75, p=0·0002). Compared with usual care, AI-guided screening was associated with increased detection of atrial fibrillation (high-risk group: 3·6% [95% CI 2·3-5·4] with usual care vs 10·6% [8·3-13·2] with AI-guided screening, p<0·0001; low-risk group: 0·9% vs 2·4%, p=0·12) over a median follow-up of 9·9 months (IQR 7·1-11·0). INTERPRETATION: An AI-guided targeted screening approach that leverages existing clinical data increased the yield for atrial fibrillation detection and could improve the effectiveness of atrial fibrillation screening. FUNDING: Mayo Clinic Robert D and Patricia E Kern Center for the Science of Health Care Delivery.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Fibrilación Atrial Tipo de estudio: Clinical_trials / Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Límite: Aged / Humans Idioma: En Revista: Lancet Año: 2022 Tipo del documento: Article Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Fibrilación Atrial Tipo de estudio: Clinical_trials / Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Límite: Aged / Humans Idioma: En Revista: Lancet Año: 2022 Tipo del documento: Article Pais de publicación: Reino Unido