Deep learning applied to 12-lead ECGs showed that myocardial ischemia risk increased gradually before cancer diagnosis and peaked immediately after diagnosis in individuals with suspected cancer during health checkups.
Does the estimated risk of myocardial ischemia on ECG change temporally around the time of cancer diagnosis?
Deep learning analysis of 12-lead ECGs indicates that the estimated risk of myocardial ischemia peaks immediately after cancer diagnosis, suggesting an acute cardiovascular impact of diagnosis-related psychological stress.
Effect estimate: Increase in probability of myocardial ischemia risk peaking immediately after cancer diagnosis compared to >1 year before diagnosis
Previous studies have suggested the potential effect of psychological stress related to cancer diagnosis on cardiovascular mortality. This study aimed to investigate the temporal trends of cardiovascular risk before and after cancer diagnosis using a deep learning model applied to 12-lead electrocardiograms (ECGs). We developed a deep learning model using a publicly available large-scale dataset to quantify myocardial ischemia risk from 12-lead ECGs. We collected ECG records from individuals diagnosed with cancer at a university hospital who also underwent an ECG as part of a health checkup within 90 days prior to cancer diagnosis. The deep learning model was then applied to the ECGs of individuals with cancer, and the temporal trend of cardiovascular risk was examined. The deep learning model demonstrated high predictive performance, with an area under the receiver operating characteristic curve of 0.930 (95% confidence interval = 0.920–0.941). The model was then applied to 523 ECG records of 89 individuals with cancer. The estimated probability of ECG-indicated myocardial ischemia increased until cancer diagnosis, peaked shortly after diagnosis, and then declined. These findings support the immediate effect of psychological stress related to cancer diagnosis on increased cardiovascular risks.
Kurisu et al. (Mon,) conducted a other in Individuals aged ≥18 years diagnosed with cancer at The Jikei University Hospital who underwent 12-lead electrocardiogram during health checkups within 90 days prior to cancer diagnosis (n=89). Deep learning model applied to 12-lead ECG vs. Reference period >1 year before cancer diagnosis was evaluated on Probability of myocardial ischemia (ST-T changes or myocardial infarction) estimated from 12-lead ECG (Increase in probability of myocardial ischemia risk peaking immediately after cancer diagnosis compared to >1 year before diagnosis). Deep learning applied to 12-lead ECGs showed that myocardial ischemia risk increased gradually before cancer diagnosis and peaked immediately after diagnosis in individuals with suspected cancer during health checkups.
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