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.

Background: Clinical assessment and treatment guidance for heart failure depends on a variety of biomarkers. The objective of this study was to investigate the prognostic predictive value of growth differentiation factor-15 (GDF-15) and N-terminal prohormone of brain natriuretic peptide (NT-proBNP) in assessing hospitalized patients with acute heart failure (AHF). Methods: In total, 260 patients who were admitted for AHF in the First Affiliated Hospital of Nanjing Medical University were enrolled from April 2012 to May 2016. Medical history and blood samples were collected within 24 h after the admission. The primary endpoint was the all-cause mortality within 1 year. The patients were divided into survival group and death group based on the endpoint. With established mortality risk factors and serum GDF-15 level, receiver-operator characteristic (ROC) analyses were performed. Cox regression analyses were used to further analyze the combination values of NT-proBNP and GDF-15. Results: Baseline GDF-15 and NT-proBNP were significantly higher amongst deceased than those in survivors (P < 0.001). In ROC analyses, area under curve (AUC) for GDF-15 to predict 1-year mortality was 0.707 (95% confidence interval [CI]: 0.648–0.762, P < 0.001), and for NT-proBNP was 0.682 (95% CI: 0.622–0.738, P < 0.001). No statistically significant difference was found between the two markers (P = 0.650). Based on the optimal cut-offs (GDF-15: 4526.0 ng/L; NT-proBNP: 1978.0 ng/L), the combination of GDF-15 and NT-proBNP increased AUC for 1-year mortality prediction (AUC = 0.743, 95% CI: 0.685–0.795, P < 0.001). Conclusions: GDF-15, as a prognostic marker in patients with AHF, is not inferior to NT-proBNP. Combining the two markers could provide an early recognition of high-risk patients and improve the prediction values of AHF long-term prognosis. Clinical trial registration ChiCTR-ONC-12001944, http://www.chictr.org.cn.