Background: Estimated plasma volume status (ePVS) has been reported that associated with poor prognosis in heart failure patients. However, no researchinvestigated the association of ePVS and prognosis in patients with acute myocardial infarction (AMI). Therefore, we aimed to determine the association between ePVS and in-hospital mortality in AMI patients. Methods and results: We extracted AMI patients data from MIMIC-III database. A generalized additive model and logistic regression model were used to demonstrate the association between ePVS levels and in-hospital mortality in AMI patients. Kaplan–Meier survival analysis was used to pooled the in-hospital mortality between the various group. ROC curve analysis were used to assessed the discrimination of ePVS for predicting in-hospital mortality. 1534 eligible subjects (1004 males and 530 females) with an average age of 67.36 ± 0.36 years old were included in our study finally. 136 patients (73 males and 63 females) died in hospital, with the prevalence of in-hospital mortality was 8.9%. The result of the Kaplan–Meier analysis showed that the high-ePVS group (ePVS ≥ 5.28 mL/g) had significant lower survival possibility in-hospital admission compared with the low-ePVS group (ePVS < 5.28 mL/g). In the unadjusted model, high-level of ePVS was associated with higher OR (1.09; 95% CI 1.06–1.12; P < 0.001) compared with low-level of ePVS. After adjusted the vital signs data, laboratory data, and treatment, high-level of ePVS were also associated with increased OR of in-hospital mortality, 1.06 (95% CI 1.03–1.09; P < 0.001), 1.05 (95% CI 1.01–1.08; P = 0.009), 1.04 (95% CI 1.01–1.07; P = 0.023), respectively. The ROC curve indicated that ePVS has acceptable discrimination for predicting in-hospital mortality. The AUC value was found to be 0.667 (95% CI 0.653–0.681). Conclusion: Higher ePVS values, calculated simply from Duarte’s formula (based on hemoglobin/hematocrit) was associated with poor prognosis in AMI patients. EPVS is a predictor for predicting in-hospital mortality of AMI, and could help refine risk stratification.

Objective. To assess the correlation between renal artery anatomy and blood pressure in Undiagnosed Hypertension and Diagnosed Hypertension. Methods. The renal artery CT scanning imaging data and laboratory data of 3000 inpatients and outpatients were collected retrospectively in 4 centers of China. Morphometric parameters were assessed using the quantitative vascular analysis (unit: mM). Results. 687 cases (23.2%) had accessory renal arteries unilaterally, and 216 cases (7.3%) had bilateral accessory renal arteries, including left kidney 825 (27.9%) and right kidney 798 (27.0%). The presence of accessory renal arteries and renal artery branches was higher in the diagnosed hypertension group as compared with the undiagnosed hypertension group (MARB, p < 0.001; ARA, < 0.001; others, < 0.001). Consequently, multivariate regression analysis showed that age (OR = 2.519 (95% CI: 0.990–6.411, < 0.001)), dyslipidemia (OR = 1.187 (95% CI: 0.960–1.454, = 0.007)), renal hilum Outside the main renal artery branch (MRAB) (OR = 2.069 (95% CI: 1.614–2.524, = 0.002)), and accessory renal artery (ARA) (OR = 2.071 (95% CI: 1.614–2.634, = 0.001)) were risk factors of hypertension. In addition, higher renin activity was associated with ARA patients (2.19 ± 2.91 vs. 1.75 ± 2.85, < 0.001). Conclusions. When comparing renal arteries side by side, the anatomical length of the renal arteries is significantly different. In addition, the prevalence of accessory renal arteries and renal artery branches is higher in the hypertension group. The auxiliary renal artery and the main renal artery branch outside the renal portal are independent factors of hypertension. Renal sympathetic nerve activity is affected by renin activity and is related to the accessory renal artery.

Background and Aims: Epidemiological studies show that high circulating cystatin C is associated with risk of cardiovascular disease (CVD), independent of creatinine-based renal function measurements. However, the relationship between serum cystatin C level and coronary atherosclerotic plaque burden is limited. We aimed to evaluate the relationship between circulating cystatin C and coronary atherosclerotic plaque burden. Methods: This study was a cross-sectional study based on China community population. Measurements of plaque burden were based on the segment-involvement score (SIS) and segment stenosis score (SSS), which derived from the Coronary Artery Tree Model Depicting Coronary Artery Plaque Scores. Logistic regression model was used to demonstrate the association between cystatin C level and coronary artery plaque burden. Mendelian randomization (MR) analyses were conducted to assess the causal effect of cystatin C level on coronary atherosclerosis risk. Results: A total of 3,043 objects were included in the present study. The odds risks (OR) of severe plaque burden in the highest serum cystatin C levels (OR: 2.50; Cl:1.59–3.91; P < 0.001) and medium-level cystatin C levels (OR: 1.86; 95% Cl: 1.21–2.88; P = 0.005) were significantly higher after fulled adjusted confounders compared with the lowest levels of serum cystatin C by SSS. The MR analysis showed that genetic predicted cystatin C levels was associated with an increased risk of coronary atherosclerosis (OR, 1.004; 95% CI, 1.002–1.006, P < 0.001) . Conclusion: Elevated serum cystatin C levels were associated with coronary atherosclerotic plaque burden. Cystatin C levels had a causal effect on an increased risk of coronary atherosclerosis at the genetic level. What is already known on this topic?: Coronary artery disease is currently the most common cardiovascular disease and the leading global cause of mortality. Previous studies reported that higher serum cystatin C levels were associated with an increased risk for future cardiovascular events, independent of the normal creatinine levels or estimated glomerular filtration rate (eGFR) values. The presence of high-risk coronary atherosclerotic plaque burden is associated with increased risk of cardiovascular events. However, the association between serum cystatin C and coronary atherosclerotic plaque burden is not very clear. What this study adds?: Our study demonstrated that the elevated serum cystatin C levels were associated with coronary atherosclerotic plaque burden. In addition, we found that serum cystatin C levels had a causal effect on an increased risk of coronary atherosclerosis at the genetic level. How this study might affect research, practice or policy?: Current research finds that serum cystatin C levels were associated with coronary atherosclerosis. The metabolic pathway of cystatin C could be a target for new therapies against CAD.

Background: Metabolic score for visceral fat (METS‐VF), a novel index which represents visceral fat, is able to predict the incidence of prediabetes and diabetes. Our study aimed to investigate the association between METS‐VF, cumulative METS‐VF (CumMETS‐VF), dynamic changes in METS‐VF, and outcomes of prediabetes among middle‐aged and older adults. Methods: This study included 2066 participants from a large Chinese cohort. METS‐VF was measured based on anthropometric and biochemical indicators, including waist circumference, height, sex, age, and the metabolic insulin resistance score, which consisted of triglyceride, fasting glucose, body mass index, and high‐density lipoprotein cholesterol. Multinomial logistic regression models were utilized to present associations between METS‐VF and progression and regression of prediabetes as a continuous variable and as a categorical variable based on tertiles. CumMETS‐VF was calculated using Wave 1 and Wave 3 of data. The predictive value of dynamic changes in METS‐VF (3 clusters) in participants with prediabetes was also assessed. Furthermore, subgroup analyses were conducted to better stratify analyses and show the interaction of variables. The relationships were visualized by restricted cubic splines with 4 knots. Results: Of 2066 participants, the mean age was 59.36±(8.60), and 46.22% were males. METS‐VF and CumMETS‐VF were prominently elevated in people from prediabetes progression to diabetes. Also, METS‐VF and CumMETS‐VF were correlated significantly with progression and regression of prediabetes. People in the high‐increasing (Class 3) METS‐VF cluster levels showed greater connection with outcomes of prediabetes compared with low‐stable (Class 1) cluster. The associations remained robust after all covariates adjustment. Besides, nonlinear relationships were observed between METS‐VF, CumMETS‐VF, and prediabetes progression and regression. The results of subgroup analyses were basically consistent with the main findings. The predictive performance of METS‐VF outperformed other common indicators. Conclusions: Our study highlighted that METS‐VF, CumMETS‐VF, and the high trajectory of METS‐VF significantly connected with prediabetes progression and regression. Monitoring of METS‐VF is important for individuals with prediabetes in clinical practice.