Objectives:To investigate the predictive value of epicardial fat volume(EFV)and atrioventricular groove fat thickness(AVGT)—morphological biomarkers of epicardial adipose tissue—for major adverse cardiovascular events(MACE)in patients with dilated cardiomyopathy(DCM).Methods:This study enrolled 216 DCM patients.EFV and AVGT were obtained from cardiac magnetic resonance imaging(CMR).Patients were divided into event-free group(n=142)and event group(n=74)based on MACE occurrence during follow-up.Receiver operating characteristic(ROC)curve analysis was used to determine optimal cutoff values.Survival differences were assessed using Kaplan-Meier analysis,Cox proportional hazards regression analysis was used to identify independent risk factors,and restricted cubic spline(RCS)models were used to evaluate dose-response relationships.Results:AVGT and EFV were significantly higher in the event group than in event-free group(both P<0.05).ROC analysis identified optimal MACE-predicting cutoffs as follows:AVGT≥7.74 mm(area under the curve[AUC]=0.57)and EFV≥78.6 ml(AUC=0.62).Kaplan-Meier analysis revealed significantly lower MACE-free survival rates in patients with AVGT≥7.74 mm and EFV≥78.6 ml(both P<0.05).Cox regression analysis confirmed that AVGT(HR=2.18,95%CI:1.34-3.54)and EFV(HR=1.81,95%CI:1.11-2.96)were independent MACE risk factors(both P<0.05)in this patient cohort.RCS models demonstrated the significant linear associations between EFV/AVGT and MACE risk(bothoverall P<0.05).Conclusions:EFV and AVGT,the non-invasive imaging biomarkers quantifying and characterizing fat distribution,are independently correlated with elevated MACE risk in DCM patients.These metrics serve as potential prognostic indicators,enriching risk stratification indicators for early identification of high-risk patients and guiding personalized medication strategies.

Objectives:To investigate the predictive value of epicardial fat volume(EFV)and atrioventricular groove fat thickness(AVGT)—morphological biomarkers of epicardial adipose tissue—for major adverse cardiovascular events(MACE)in patients with dilated cardiomyopathy(DCM).Methods:This study enrolled 216 DCM patients.EFV and AVGT were obtained from cardiac magnetic resonance imaging(CMR).Patients were divided into event-free group(n=142)and event group(n=74)based on MACE occurrence during follow-up.Receiver operating characteristic(ROC)curve analysis was used to determine optimal cutoff values.Survival differences were assessed using Kaplan-Meier analysis,Cox proportional hazards regression analysis was used to identify independent risk factors,and restricted cubic spline(RCS)models were used to evaluate dose-response relationships.Results:AVGT and EFV were significantly higher in the event group than in event-free group(both P<0.05).ROC analysis identified optimal MACE-predicting cutoffs as follows:AVGT≥7.74 mm(area under the curve[AUC]=0.57)and EFV≥78.6 ml(AUC=0.62).Kaplan-Meier analysis revealed significantly lower MACE-free survival rates in patients with AVGT≥7.74 mm and EFV≥78.6 ml(both P<0.05).Cox regression analysis confirmed that AVGT(HR=2.18,95%CI:1.34-3.54)and EFV(HR=1.81,95%CI:1.11-2.96)were independent MACE risk factors(both P<0.05)in this patient cohort.RCS models demonstrated the significant linear associations between EFV/AVGT and MACE risk(bothoverall P<0.05).Conclusions:EFV and AVGT,the non-invasive imaging biomarkers quantifying and characterizing fat distribution,are independently correlated with elevated MACE risk in DCM patients.These metrics serve as potential prognostic indicators,enriching risk stratification indicators for early identification of high-risk patients and guiding personalized medication strategies.