Risk Stratification of Cancer Therapy-Related Cardiac Dysfunction Using AI-Enhanced Electrocardiography
Risk Stratification of Cancer Therapy-Related Cardiac Dysfunction Using AI-Enhanced Electrocardiography
This study investigates the use of AI-enhanced electrocardiogram (ECG) for risk stratification of cancer therapy-related cardiac dysfunction (CTRCD) before the initiation of cancer therapy. The study includes patients treated with anthracyclines, HER2 inhibitors, or immune checkpoint inhibitors (ICIs) at Severance Hospital between May 2006 and November 2022, who underwent an ECG within 90 days prior to chemotherapy. The primary goal is to evaluate whether AI-ECG can accurately predict the risk of CTRCD and compare its performance to existing risk stratification models. In addition, we aim to assess whether the variation in AI-ECG scores between pre- and post-chemotherapy assessments could serve as a predictor of CTRCD. Eligible participants are adults without prior heart failure, cardiomyopathy, or myocarditis, and with baseline left ventricular ejection fraction (LVEF) ≥40%. For trajectory analysis, only patients with an additional ECG within 90 days after chemotherapy are included. The primary outcome is the development of CTRCD within 12 months after the last treatment cycle (and no more than 24 months after the first). The secondary outcomes are severe CTRCD (LVEF <40%) and all-cause mortality.
This study aims to validate the clinical utility of AI-enhanced ECG as a simple, accessible, and cost-effective tool for predicting CTRCD across diverse cancer treatment regimens, including newer immunotherapies.
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