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Published on: December 6, 2024
Global Myocardial Work-Derived Nomogram for Coronary Stenosis Assessment in Stable Coronary Artery Disease:
Miao Li1, Wenfang Wu1, Lin Li1
1Department of Cardiovascular Ultrasound, Nanjing First Hospital, Nanjing Medical University, 68 Changle Road, Nanjing 210006, China.
Insights
A new nomogram using myocardial work efficiency and biomarkers accurately predicts coronary artery disease (CAD) in patients without wall motion abnormalities. This non-invasive tool aids risk stratification and optimizes diagnostic decisions for stable CAD.
Area of Science:
- Cardiology
- Medical Imaging
- Diagnostic Tools
Background:
- Non-invasive identification of coronary stenosis in stable coronary artery disease (CAD) patients lacking regional wall motion abnormalities (RWMA) is difficult.
- Current diagnostic methods may involve invasive procedures, posing risks and increasing healthcare costs.
- There is a need for accurate, non-invasive tools to assess stenosis severity in this specific patient group.
Purpose of the Study:
- To develop and validate a nomogram using myocardial work-derived parameters and clinical biomarkers for predicting significant coronary stenosis.
- To provide a non-invasive tool for risk stratification in stable CAD patients without RWMA.
- To optimize the use of invasive diagnostic procedures.
Main Methods:
- Retrospective study of 181 patients with confirmed CAD, preserved LVEF, and no resting RWMA.
- Global myocardial work efficiency (GWE) assessed via echocardiographic pressure-strain loop analysis.
- Development and external validation of a multivariable nomogram incorporating GWE and biomarkers (LP-PLA2, NT-proBNP, Scr).
Main Results:
- The nomogram incorporating GWE, LP-PLA2, NT-proBNP, and Scr showed high predictive accuracy (AUC 0.916 training, 0.911 validation).
- The model demonstrated good calibration in both training and validation sets.
- Decision curve analysis confirmed the clinical utility of the nomogram across various probability thresholds.
Conclusions:
- The developed nomogram offers a valuable non-invasive method for predicting significant coronary stenosis in stable CAD patients without RWMA.
- This tool can aid in preoperative risk stratification and improve the efficiency of invasive diagnostic testing.
- The findings support the integration of myocardial work analysis into routine clinical practice for selected CAD patients.
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.
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