China-calibration-ready echocardiographic feature modeling for LVEF-derived dysfunction classification: a surrogate-label proof-of-concept.

Introduction: This study presents a reproducible echocardiographic feature-engineering and machine-learning pipeline for classifying a left ventricular ejection fraction (LVEF)-derived surrogate dysfunction label, using publicly available two-dimensional echocardiographic tracings. The work is explicitly framed as a methodological proof-of-concept rather than a clinically validated model for predicting anthracycline-related right ventricular cardiotoxicity. Methods: A derivative dataset comprising 10,930 records was assembled from the EchoNet-Dynamic database and a CAMUS-derived frame-mask archive. From this pool, a stratified 1,000-record working sample was extracted to support auditable and transparent model development. After mutual-information ranking performed within the training folds, twelve geometric and morphometric features were retained, including left ventricular trace-area change, bounding-box area change, and cohort-median-normalized calibration variables-these were deliberately designed for later substitution with age- and sex-specific Chinese reference values from the EMINCA-II study. Five classifiers were trained using an 800/200 stratified split, with five-fold cross-validation applied inside the training set. Results: Among the five classifiers, logistic regression achieved the highest held-out ROC-AUC of 0.996 and F1 score of 0.966. However, these performance metrics reflect the geometric coupling between the engineered left-ventricular features and the LVEF-derived label, rather than independent clinical predictive capability. A descriptive mediation analysis further showed that the association between bounding-box area change and the dysfunction label was largely transmitted through left ventricular trace-area change. Discussion: The available public data do not include information on anthracycline exposure, Chinese patient identity, right ventricular functional outcomes, or prospective cardiotoxicity endpoints. Therefore, the primary contribution of this study is a transparent, calibration-ready analytical scaffold that can be reused and extended in future prospective Chinese anthracycline cohorts that incorporate true right ventricular outcome measures.