Objective To investigate the correlation between serum vitamin D level and heart failure based on cross-sectional analysis.Methods A total of 10,411 subjects included in the Na-tional Health and Nutrition Examination Survey(NHANES)database from 2013 to 2016 were select-ed as the study population.The serum 25-hydroxyvitamin D[25(OH)D]levels of all subjects were measured.According to the quartiles of serum vitamin D levels,the subjects were divided into four groups.Multivariate logistic regression analysis and restricted cubic spline regression analysis were employed to explore the correlation between serum vitamin D level and heart failure.Results There were statistically significant differences among the four groups in terms of age,gender,educational at-tainment,race,diabetes,hypertension,alcohol consumption,physical activity,and body mass index(P＜0.05).The incidence rates of heart failure in the four vitamin D quartile groups(from low to high)were 3.9％,2.7％,2.9％and 4.1％respectively,with a statistically significant difference(P＜0.05).The results of multivariate logistic regression analysis revealed that,compared with the subjects in the first quartile group of vitamin D,the odds ratios(OR)and 95％confidence intervals(CI)of heart failure in the second,third,and fourth quartile groups of vitamin D were 0.64(0.46 to 0.89),0.53(0.38 to 0.73)and 0.48(0.35 to 0.66)respectively,and the trend test showed P was less than 0.001.The results of restricted cubic spline regression analysis indicated that serum vitamin D level was non-linearly negatively correlated with heart failure(non-linear test P=0.005).At the initial stage,the risk of heart failure decreased with the increase in vitamin D level;when the vitamin D level reached a certain level,the risk of heart failure tended to stabilize or even increase slightly.Con-clusion Serum vitamin D level is non-linearly negatively correlated with the risk of heart failure.

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.

Objective:To compare the prognostic values of different classification by using transpulmonary pressure gradient (TPG), diastolic pressure gradient (DPG) and pulmonary vascular resistance (PVR) in patients with pulmonary hypertension due to left heart disease (PH-LHD), and investigated hemodynamic and clinical factors associated with mortality in patients with PH-LHD.Methods:This was a single-center prospective cohort study. In-hospital patients diagnosed with PH-LHD via right heart catheterization at the Department of Cardiology, the First Affiliated Hospital of Nanjing Medical University, from September 2013 to December 2019 were enrolled. Patients were divided according to TPG (cutoff value 12 mmHg; 1 mmHg=0.133 kPa), DPG (cutoff value 7 mmHg), PVR (cutoff value 3 Wood Units), and the combination of TPG and PVR. Baseline characteristic was recorded. All patients were followed up until the occurrence of endpoint event, defined as all-cause death that occurred during the follow-up period, or until April 18, 2022. Receiver operating characteristic curves were used to compare the predictive value of 3 classification methods for all-cause death in PH-LHD patients. The optimal cutoff values were calculated using Jorden index. Survival analysis was performed using Kaplan-Meier analysis, and log-rank test was used to compare the predictive efficacy of classification methods based on optimal cutoff values or guidance-recommended thresholds for the survival of PH-LHD patients. Variables showing statistical significance in the univariate analysis were incorporated into multivariate Cox regression model to analyze the independent risk factors for all-cause mortality.Results:A total of 243 patients were enrolled, aged (54.9±12.7) years old, including 169 (69.5%) males. During a median follow-up of 57 months, there were 101 (41.6%) deaths occurred. Grouping results were as follows: (1) TPG: TPG≤12 mmHg group 115 patients, TPG>12 mmHg group 128 patients; (2) DPG: DPG<7 mmHg group 193 patients, DPG≥7 mmHg group 50 patients; (3) PVR: PVR≤3 Wood Units group 108 patients, PVR>3 Wood Units group 135 patients; (4) TPG and PVR: TPG≤12 mmHg and PVR≤3 Wood Units group 89 patients, TPG>12 mmHg and PVR>3 Wood Units group 109 patients. PVR ( AUC=0. 698,95% CI:0.631-0.766) had better predictive value for all-cause mortality than TPG ( AUC=0.596, 95% CI: 0.523-0.669) and DPG ( AUC=0.526, 95% CI: 0.452-0.601) (all P<0.05). The optimal cutoff values for TPG, DPG, and PVR were13.9 mmHg, 2.8 mmHg, and 3.8 Wood Units, respectively. Kaplan-Meier analysis based on the optimal cutoff values or guidance-recommended thresholds showed that PVR and TPG were the predictors of survival ( P<0.05), while DPG did not showed significance ( P>0.05). Multivariate Cox regression analysis showed that age, PVR and log 2N-terminal pro-B-type natriuretic peptide were independent risk factors for all-cause mortality in PH-LHD patients (all P<0.05). Conclusion:Classification according to PVR was most valuable in predicting all-cause death in PH-LHD patients, while TPG showed moderate predictive ability and DPG had no predictive value.