Development and validation of a prediction model for all-cause mortality in maintenance dialysis patients: a multicenter retrospective cohort study.

BACKGROUND: The mortality risk varies considerably among individual dialysis patients. This study aimed to develop a user-friendly predictive model for predicting all-cause mortality among dialysis patients. METHODS: Retrospective data regarding dialysis patients were obtained from two hospitals. Patients in training cohort (N = 1421) were recruited from the Fifth Affiliated Hospital of Sun Yat-sen University, and patients in external validation cohort (N = 429) were recruited from the First Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine. The follow-up endpoint event was all-cause death. Variables were selected by LASSO-Cox regression, and the model was constructed by Cox regression, which was presented in the form of nomogram and web-based tool. The discrimination and accuracy of the prediction model were assessed using C-indexes and calibration curves, while the clinical value was assessed by decision curve analysis (DCA). RESULTS: The best predictors of 1-, 3-, and 5-year all-cause mortality contained nine independent factors, including age, body mass index (BMI), diabetes mellitus (DM), cardiovascular disease (CVD), cancer, urine volume, hemoglobin (HGB), albumin (ALB), and pleural effusion (PE). The 1-, 3-, and 5-year C-indexes in the training set (0.840, 0.866, and 0.846, respectively) and validation set (0.746, 0.783, and 0.741, respectively) were consistent with comparable performance. According to the calibration curve, the nomogram predicted survival accurately matched the actual survival rate. The DCA showed the nomogram got more clinical net benefit in both the training and validation sets. CONCLUSIONS: The effective and convenient nomogram may help clinicians quantify the risk of mortality in maintenance dialysis patients.

Correlation of serum vitamin D with lipid profiles in middle-aged and elderly Chinese individuals.

BACKGROUND AND OBJECTIVES: Deficiency of vitamin D has been associated with various health conditions. The purpose of this study was to evaluate the associations between the serum 25OHD concentration and lipid profiles in Chinese individuals. METHODS AND STUDY DESIGN: Serum 25OHD and lipid profiles were obtained for a cross sectional sample of 10100 individuals aged 40-75 years from Lanzhou city, which is located in western China. Linear-by-linear association, partial correlation analysis and multiple logistic regression analysis were used to evaluate associations between serum 25OHD concentration and lipid profiles. RESULTS: 10038 subjects aged 40- 75 years were included in the study. The 25OHD deficient and insufficient groups had higher TC, LDL-C and TG when compared to the optimal group. The dyslipidemia rates of vitamin D deficiency, insufficiency, and sufficiency groups were 45.4%, 41.6%, 38.8%, respectively. The prevalence rates of dyslipidemia, high cholesterol, high LDL-C, hypertriglyceridemia and mixed type hyperlipidemia exhibited decline trend in vitamin D deficiency, insufficiency and sufficiency groups. The correlation coefficients in between TC and 25OHD, LDL-C and 25OHD, TG and 25OHD were -0.033, -0.022, -0.044, respectively. Low 25OHD levels were associated with the risk of onset of dyslipidemia [OR 1.225 (95% CI 1.075-1.397), p=0.002] in the logistical regression analyses. CONCLUSIONS: Deficient serum 25OHD is associated with higher TC, LDL-C, and TG in middle-aged and elderly Chinese individuals. These findings suggest that low 25OHD levels observationally is simply a marker for elevated atherogenic lipoproteins and question a role for vitamin D supplementation in the prevention of cardiovascular disease.