Artificial Intelligence-Enabled Electrocardiogram Estimates Left Atrium Enlargement as a Predictor of Future Cardiovascular Disease

Figures

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  Figure A1. Summary of the baseline distributions in development, tuning, internal validation, and external validation sets. Abbreviations: ECHO, echocardiography; BMI, body mass index; DM, diabetes mellitus; HLP, hyperlipidemia; CKD, chronic kidney disease; CAD, coronary artery disease; HF, heart failure; COPD, chronic obstructive pulmonary disease; LA, left atrium; LV-D, left ventricle (end-diastole); LV-S, left ventricle (end-systole); IVS, interventricular septum; LVPW, left ventricular posterior wall; AO, aortic root; RV, right ventricle; PASP, pulmonary artery systolic pressure; PE, pericardial effusion; EF, ejection fraction; HTN, hypertension; STK, stroke; MR, mitral regurgitation; Afib, atrial fibrillation.

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  Figure A2. Kaplan–Meier curves for each severity of electrocardiogram-based left atrium enlargement (ECG-LAE) and echocardiography-based left atrium enlargement (ECHO-LAE) on new-onset hypertension (HTN) in internal validation set. The cutoff points of without, mild-to-moderate, and severe LAE were defined as 45 and 55 mm, respectively. The C-index was calculated based on the continuous value combined with sex and age. The table shows the at-risk population and cumulative risk for the given time intervals in each risk stratification.

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  Figure A3. Kaplan–Meier curves for each severity of electrocardiogram-based left atrium enlargement (ECG-LAE) and echocardiography-based left atrium enlargement (ECHO-LAE) on new-onset hypertension (HTN) in external validation set. The cutoff points of without, mild-to-moderate, and severe LAE were defined as 45 and 55 mm, respectively. The C-index was calculated based on the continuous value combined with sex and age. The table shows the at-risk population and cumulative risk for the given time intervals in each risk stratification.

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  Figure A4. Kaplan–Meier curves for each severity of electrocardiogram-based left atrium enlargement (ECG-LAE) and echocardiography-based left atrium enlargement (ECHO-LAE) on new-onset stroke (STK) in internal validation set. The cutoff points of without, mild-to-moderate, and severe LAE were defined as 45 and 55 mm, respectively. The C-index was calculated based on the continuous value combined with sex and age. The table shows the at-risk population and cumulative risk for the given time intervals in each risk stratification.

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  Figure A5. Kaplan–Meier curves for each severity of electrocardiogram-based left atrium enlargement (ECG-LAE) and echocardiography-based left atrium enlargement (ECHO-LAE) on new-onset stroke (STK) in external validation set. The cutoff points of without, mild-to-moderate, and severe LAE were defined as 45 and 55 mm, respectively. The C-index was calculated based on the continuous value combined with sex and age. The table shows the at-risk population and cumulative risk for the given time intervals in each risk stratification.

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  Figure A6. Kaplan–Meier curves for each severity of electrocardiogram-based left atrium enlargement (ECG-LAE) and echocardiography-based left atrium enlargement (ECHO-LAE) on new-onset mitral regurgitation (MR) in internal validation set. The cutoff points of without, mild-to-moderate, and severe LAE were defined as 45 and 55 mm, respectively. The C-index was calculated based on the continuous value combined with sex and age. The table shows the at-risk population and cumulative risk for the given time intervals in each risk stratification.

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  Figure A7. Kaplan–Meier curves for each severity of electrocardiogram-based left atrium enlargement (ECG-LAE) and echocardiography-based left atrium enlargement (ECHO-LAE) on new-onset mitral regurgitation (MR) in external validation set. The cutoff points of without, mild-to-moderate, and severe LAE were defined as 45 and 55 mm, respectively. The C-index was calculated based on the continuous value combined with sex and age. The table shows the at-risk population and cumulative risk for the given time intervals in each risk stratification.

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  Figure A8. Kaplan–Meier curves for each severity of electrocardiogram-based left atrium enlargement (ECG-LAE) and echocardiography-based left atrium enlargement (ECHO-LAE) on new-onset atrial fibrillation (Afib) in internal validation set. The cutoff points of without, mild-to-moderate, and severe LAE were defined as 45 and 55 mm, respectively. The C-index was calculated based on the continuous value combined with sex and age. The table shows the at-risk population and cumulative risk for the given time intervals in each risk stratification.

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  Figure A9. Kaplan–Meier curves for each severity of electrocardiogram-based left atrium enlargement (ECG-LAE) and echocardiography-based left atrium enlargement (ECHO-LAE) on new-onset atrial fibrillation (Afib) in external validation set. The cutoff points of without, mild-to-moderate, and severe LAE were defined as 45 and 55 mm, respectively. The C-index was calculated based on the continuous value combined with sex and age. The table shows the at-risk population and cumulative risk for the given time intervals in each risk stratification.

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  Figure A10. Stratified analysis for the C-index comparison between electrocardiogram-based left atrium (ECG-LA) diameter and echocardiography-based left atrium (ECHO-LA) diameter on new-onset complications in external validation set. The analyses were stratified by the disease histories of the populations. The C-index was calculated based on the ECG-LA/ECHO-LA combined with sex and age. *: p < 0.05; **: p < 0.01; ***: p < 0.001. The overall population analyses were performed with an unstratified Cox proportional-hazards model.

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  Figure 1. Development, tuning, internal validation, and external validation set generation and ECG labeling of the left atrium in a private dataset. Illustration of the dataset generation. This dataset creation was designed to assure the reliability and robustness of the data for training, tuning, and validation of the deep learning model. To avoid cross-contamination, once patients were included in one of the datasets, patients were not included in other datasets. The details of the workflow and the usage of each dataset are described in the Methods.

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  Figure 2. Scatter plots of the predicted left atrium (ECG-LA) diameter via an ECG only compared to the actual left atrium (LA) diameter. The x-axis indicates the actual LA diameter, and the y-axis presents the ECG-LA diameter. The highest density is represented by red points, followed by yellow, green, light blue, and dark blue points. We presented the mean difference (Diff), Pearson correlation coefficients (COR), and mean absolute errors (MAE) to demonstrate the accuracy of the DLM. The black lines with 95% confidence intervals are fitted via simple linear regression.