Abstract 4368775: Feature Tracking Global Longitudinal Strain Enhances Risk Stratification for Sudden Cardiac Death in Hypertrophic Cardiomyopathy

Background: Left ventricular global longitudinal strain (LV-GLS) assessed by cardiac magnetic resonance feature tracking (CMR-FT) is an emerging marker for predicting adverse outcomes in hypertrophic cardiomyopathy (HCM), but its incremental prognostic value and potential mechanistic role in sudden cardiac death (SCD) risk stratification remain unclear. Objectives: To evaluate the incremental prognostic utility of LV-GLS beyond current European Society of Cardiology (ESC) and American College of Cardiology/American Heart Association (ACC/AHA) SCD risk models, and to explore whether LV-GLS mediates the relationship between myocardial hypertrophy, fibrosis, and SCD risk in patients with HCM. Methods: We retrospectively analyzed 2,009 HCM patients (mean age 50±14 years; 70% men) who underwent CMR imaging between 2010 and 2017. LV-GLS was quantified using cine-CMR feature tracking. The primary endpoint included SCD and aborted SCD. Prognostic performance was assessed using time-dependent receiver operating characteristic (ROC) analysis, Kaplan-Meier survival analysis, and competing risk regression. Mediation analysis was used to investigated how LV-GLS mediated the association between myocardial abnormalities and SCD. Results: Over a median follow-up of 88.2 months, 85 patients (4.2%) experienced SCD events. These patients had significantly lower absolute LV-GLS values (9.0±3.6% vs. 11.1±3.6%, P < .001). In competing risk regression, LV-GLS independently predicted SCD after adjustment for ESC (sHR: 1.12 per 1% decrease, 95% CI: 1.06–1.22, P < .001) and AHA risk factors (sHR: 1.09, 95% CI: 1.02–1.18, P = .016). Adding LV-GLS improved the 5-year predictive accuracy of both ESC and AHA models (area under the curve [AUC]: from 0.71 to 0.76 and 0.71 to 0.75, respectively). Absolute LV-GLS with a cutoff of 9.23% also stratified risk in patient subgroups with either Class II or Class III recommendations for implantable cardioverter-defibrillator (ICD) implantation (all log-rank P < .001). Mediation analysis showed LV-GLS partially mediated the relationship between maximum wall thickness and SCD (proportion-mediated: 23.1%, P < .001), and between extent of fibrosis and SCD (proportion-mediated: 17.5%, P < .001). Conclusions: In HCM patients, CMR-derived LV-GLS is an incremental predictor of SCD beyond current guideline-based risk models and partially mediates the association between myocardial abnormalities and SCD.

Authors

Institutions

Publication Details

Journal
Circulation
Published
2025-11-03
DOI
https://doi.org/10.1161/circ.152.suppl_3.4368775
Primary Topic
Cardiomyopathy and Myosin Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract 4368775: Feature Tracking Global Longitudinal Strain Enhances Risk Stratification for Sudden Cardiac Death in Hypertrophic Cardiomyopathy

Shujuan Yang, Shihua Zhao, Yun Tang, Xingrui Chen et al.
Circulation
Cardiomyopathy and Myosin Studies
article

Abstract 4368775: Feature Tracking Global Longitudinal Strain Enhances Risk Stratification for Sudden Cardiac Death in Hypertrophic Cardiomyopathy

Shujuan Yang, Shihua Zhao, Yun Tang, Xingrui Chen, Xuan Ma
article en

Abstract

Background: Left ventricular global longitudinal strain (LV-GLS) assessed by cardiac magnetic resonance feature tracking (CMR-FT) is an emerging marker for predicting adverse outcomes in hypertrophic cardiomyopathy (HCM), but its incremental prognostic value and potential mechanistic role in sudden cardiac death (SCD) risk stratification remain unclear. Objectives: To evaluate the incremental prognostic utility of LV-GLS beyond current European Society of Cardiology (ESC) and American College of Cardiology/American Heart Association (ACC/AHA) SCD risk models, and to explore whether LV-GLS mediates the relationship between myocardial hypertrophy, fibrosis, and SCD risk in patients with HCM. Methods: We retrospectively analyzed 2,009 HCM patients (mean age 50±14 years; 70% men) who underwent CMR imaging between 2010 and 2017. LV-GLS was quantified using cine-CMR feature tracking. The primary endpoint included SCD and aborted SCD. Prognostic performance was assessed using time-dependent receiver operating characteristic (ROC) analysis, Kaplan-Meier survival analysis, and competing risk regression. Mediation analysis was used to investigated how LV-GLS mediated the association between myocardial abnormalities and SCD. Results: Over a median follow-up of 88.2 months, 85 patients (4.2%) experienced SCD events. These patients had significantly lower absolute LV-GLS values (9.0±3.6% vs. 11.1±3.6%, P < .001). In competing risk regression, LV-GLS independently predicted SCD after adjustment for ESC (sHR: 1.12 per 1% decrease, 95% CI: 1.06–1.22, P < .001) and AHA risk factors (sHR: 1.09, 95% CI: 1.02–1.18, P = .016). Adding LV-GLS improved the 5-year predictive accuracy of both ESC and AHA models (area under the curve [AUC]: from 0.71 to 0.76 and 0.71 to 0.75, respectively). Absolute LV-GLS with a cutoff of 9.23% also stratified risk in patient subgroups with either Class II or Class III recommendations for implantable cardioverter-defibrillator (ICD) implantation (all log-rank P < .001). Mediation analysis showed LV-GLS partially mediated the relationship between maximum wall thickness and SCD (proportion-mediated: 23.1%, P < .001), and between extent of fibrosis and SCD (proportion-mediated: 17.5%, P < .001). Conclusions: In HCM patients, CMR-derived LV-GLS is an incremental predictor of SCD beyond current guideline-based risk models and partially mediates the association between myocardial abnormalities and SCD.

CirculationVol. 152(Suppl_3)
Chinese Academy of Medical Sciences & Peking Union Medical College (CN), Beijing Anzhen Hospital (CN), Fu Wai Hospital (CN)
Openalex Percentile: Top 51%
Cardiomyopathy and Myosin Studies
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.