Abstract
Background: Non-invasive identification of coronary stenosis in stable coronary artery disease (CAD) patients lacking regional wall motion abnormalities (RWMA) remains challenging. This study aimed to develop and validate a myocardial work-derived nomogram for predicting significant coronary stenosis in these patients. Methods: In this retrospective study, 181 consecutive patients with angiographically confirmed CAD, preserved LVEF (≥55%), and no resting wall motion abnormalities were enrolled. Global myocardial work efficiency (GWE) was assessed using echocardiographic pressure-strain loop analysis. A multivariable-derived nomogram incorporating GWE and clinical biomarkers was developed and externally validated for predicting severe coronary stenosis. Results: The nomogram incorporating GWE, lipoprotein-associated phospholipase A2 (LP-PLA2), N-terminal pro brain natriuretic peptide (NT-proBNP), and serum creatinine (Scr) demonstrated favorable discrimination in both the training set (AUC 0.916, 95% CI 0.866-0.952) and validation set (AUC 0.911, 95% CI 0.853-0.951), with good calibration (mean absolute error: 1.9% vs 3.2% in training vs validation, respectively). Decision curve analysis confirmed clinical utility across all probability thresholds. Conclusions: Our nomogram provides a non-invasive tool for preoperative risk stratification and optimizes the use of invasive diagnostics in stable CAD patients without RWMA.