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Artificial intelligence-enabled prediction of chemotherapy-induced cardiotoxicity from baseline electrocardiograms.
- Source :
- Nature Communications; 1/11/2024, Vol. 15 Issue 1, p1-10, 10p
- Publication Year :
- 2024
-
Abstract
- Anthracyclines can cause cancer therapy-related cardiac dysfunction (CTRCD) that adversely affects prognosis. Despite guideline recommendations, only half of the patients undergo surveillance echocardiograms. An AI model detecting reduced left ventricular ejection fraction from 12-lead electrocardiograms (ECG) (AI-EF model) suggests ECG features reflect left ventricular pathophysiology. We hypothesized that AI could predict CTRCD from baseline ECG, leveraging the AI-EF model’s insights, and developed the AI-CTRCD model using transfer learning on the AI-EF model. In 1011 anthracycline-treated patients, 8.7% experienced CTRCD. High AI-CTRCD scores indicated elevated CTRCD risk (hazard ratio (HR), 2.66; 95% CI 1.73–4.10; log-rank p < 0.001). This remained consistent after adjusting for risk factors (adjusted HR, 2.57; 95% CI 1.62–4.10; p < 0.001). AI-CTRCD score enhanced prediction beyond known factors (time-dependent AUC for 2 years: 0.78 with AI-CTRCD score vs. 0.74 without; p = 0.005). In conclusion, the AI model robustly stratified CTRCD risk from baseline ECG.Anthracyclines can induce cancer therapy-related cardiac dysfunction (CTRCD), of which occurrence remains unpredictable. Here, the authors develop an artificial intelligence model to robustly predict CTRCD from a single recording of 12-lead electrocardiogram taken before the initiation of chemotherapy in cancer patients treated with anthracyclines. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 20411723
- Volume :
- 15
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- Nature Communications
- Publication Type :
- Academic Journal
- Accession number :
- 176259569
- Full Text :
- https://doi.org/10.1038/s41467-024-45733-x