Predicting stroke in Asian patients with atrial fibrillation using machine learning: A report from the KERALA-AF registry, with external validation in the APHRS-AF registry.


Chen, Yang ORCID: 0000-0002-2808-6286, Gue, Ying ORCID: 0000-0001-9994-8915, Calvert, Peter, Gupta, Dhiraj ORCID: 0000-0002-3490-090X, McDowell, Garry ORCID: 0000-0002-2880-5236, Azariah, Jinbert Lordson, Namboodiri, Narayanan, Bucci, Tommaso ORCID: 0000-0003-2895-6234, Jabir, A, Tse, Hung Fat et al (show 4 more authors) (2024) Predicting stroke in Asian patients with atrial fibrillation using machine learning: A report from the KERALA-AF registry, with external validation in the APHRS-AF registry. Current problems in cardiology, 49 (4). p. 102456.

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Abstract

Atrial fibrillation (AF) is a significant risk factor for stroke. Based on the higher stroke associated with AF in the South Asian population, we constructed a one-year stroke prediction model using machine learning (ML) methods in KERALA-AF South Asian cohort. External validation was performed in the prospective APHRS-AF registry. We studied 2101 patients and 83 were to patients with stroke in KERALA-AF registry. The random forest showed the best predictive performance in the internal validation with receiver operator characteristic curve (AUC) and G-mean of 0.821 and 0.427, respectively. In the external validation, the light gradient boosting machine showed the best predictive performance with AUC and G-mean of 0.670 and 0.083, respectively. We report the first demonstration of ML's applicability in an Indian prospective cohort, although the more modest prediction on external validation in a separate multinational Asian registry suggests the need for ethnic-specific ML models.

Item Type: Article
Uncontrolled Keywords: KERALA-AF Registry & APHRS-AF Registry Investigators joint senior authors
Divisions: Faculty of Health and Life Sciences
Faculty of Health and Life Sciences > Institute of Life Courses and Medical Sciences
Faculty of Health and Life Sciences > Institute of Life Courses and Medical Sciences > School of Medicine
Depositing User: Symplectic Admin
Date Deposited: 01 Mar 2024 08:13
Last Modified: 01 Mar 2024 08:22
DOI: 10.1016/j.cpcardiol.2024.102456
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3179006
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