# Global Myocardial Work-Derived Nomogram for Coronary Stenosis Assessment in Stable Coronary Artery Disease: Development and External Validation

## TL;DR

This study creates and validates a non-invasive tool using heart function data to identify significant coronary blockages in patients with stable heart disease.

## Contribution

A novel nomogram combining global myocardial work efficiency and clinical biomarkers is developed and validated for coronary stenosis assessment.

## Key findings

- The nomogram achieved high discrimination in both training and validation sets (AUC 0.916 and 0.911, respectively).
- The model showed good calibration with low mean absolute error in both training and validation sets.
- Decision curve analysis confirmed the clinical utility of the nomogram across all probability thresholds.

## 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.