Diagnostic Cut-off Values for Newly Developed Noninvasive Elastance-Based Indices in Duchenne Muscular Dystrophy–Associated Cardiomyopathy

Duchenne muscular dystrophy–associated cardiomyopathy (DMDAC) is a leading cause of mortality in patients with Duchenne muscular dystrophy. Conventional reliance on ejection fraction (EF) may underestimate early myocardial dysfunction. This study utilized the previously published dataset by Ajiboye et al. (Heart Vessels 40(8):696–706, 2025) comprising 30 DMDAC patients who underwent serial cardiac magnetic resonance (CMR) imaging between 2014 and 2023. Noninvasive indices—mean elastance, contractility, and energy efficiency—were derived using an innovative optimization approach by integrating patients specific brachial blood pressure and CMR-based left-ventricular volume changes. Diagnostic performance of the proposed indices relative to EF < 55% was obtained using receiver operating characteristic (ROC) curve to determing the cut-off values. All three indices, derived noninvasively, demonstrated statistically significant delineation for 55% EF, with AUC of 0.92 for mean elastance, 0.96 for contractility, and 1.00 for energy efficiency. Optimal cut-offs were 0.50 mmHg/mL, 1.72 mmHg/mL, and 69.8%, respectively. These findings support newly developed mean elastance, contractility, and energy efficiency as viable noninvasive diagnostic indices for DMDAC. Incorporating these indices alongside EF could improve early detection and risk stratification in clinical decision making.

Authors

Institutions

Publication Details

Journal
Pediatric Cardiology
Published
2026-02-12
DOI
https://doi.org/10.1007/s00246-026-04188-1
Primary Topic
Cardiovascular Function and Risk Factors
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Diagnostic Cut-off Values for Newly Developed Noninvasive Elastance-Based Indices in Duchenne Muscular Dystrophy–Associated Cardiomyopathy

Rupak K. Banerjee, M. Yvonne Taylor, Israel O. Ajiboye
Pediatric Cardiology
Cardiovascular Function and Risk Factors
article

Diagnostic Cut-off Values for Newly Developed Noninvasive Elastance-Based Indices in Duchenne Muscular Dystrophy–Associated Cardiomyopathy

Rupak K. Banerjee, M. Yvonne Taylor, Israel O. Ajiboye
article en

Abstract

Duchenne muscular dystrophy–associated cardiomyopathy (DMDAC) is a leading cause of mortality in patients with Duchenne muscular dystrophy. Conventional reliance on ejection fraction (EF) may underestimate early myocardial dysfunction. This study utilized the previously published dataset by Ajiboye et al. (Heart Vessels 40(8):696–706, 2025) comprising 30 DMDAC patients who underwent serial cardiac magnetic resonance (CMR) imaging between 2014 and 2023. Noninvasive indices—mean elastance, contractility, and energy efficiency—were derived using an innovative optimization approach by integrating patients specific brachial blood pressure and CMR-based left-ventricular volume changes. Diagnostic performance of the proposed indices relative to EF < 55% was obtained using receiver operating characteristic (ROC) curve to determing the cut-off values. All three indices, derived noninvasively, demonstrated statistically significant delineation for 55% EF, with AUC of 0.92 for mean elastance, 0.96 for contractility, and 1.00 for energy efficiency. Optimal cut-offs were 0.50 mmHg/mL, 1.72 mmHg/mL, and 69.8%, respectively. These findings support newly developed mean elastance, contractility, and energy efficiency as viable noninvasive diagnostic indices for DMDAC. Incorporating these indices alongside EF could improve early detection and risk stratification in clinical decision making.

Pediatric Cardiology
University of Cincinnati (US), The University of Texas at Austin (US)
Affordable and clean energy
Openalex Percentile: Top 60%
Cardiovascular Function and Risk Factors
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.