INTRODUCTION The Kidney Failure Risk Equation (KFRE) was developed to predict the risk of progression to end-stage kidney disease (ESKD). Although the KFRE has been validated in multinational cohorts, the Southeast Asian population was under-represented. This study aimed to validate the KFRE in a multi-ethnic Singapore chronic kidney disease (CKD) cohort. METHODS Stage 3–5 CKD patients referred to the renal medicine department at Singapore General Hospital in 2009 were included. The primary outcome (time to ESKD) was traced until 30 June 2017. The eight- and four-variable KFRE (non-North America) models using age, gender, estimated glomerular filtration rate, urine albumin-creatinine ratio, serum albumin, phosphate, bicarbonate and calcium were validated in our cohort. Cox regression, likelihood ratio (Χ2), adequacy index, Harrell’s C-index and calibration curves were calculated to assess the predictive performance, discrimination and calibration of these models on the cohort. RESULTS A total of 1,128 patients were included. During the study period, 252 (22.3%) patients reached ESKD at a median time to ESKD of 84.8 (range 0.1–104.7) months. Both the eight- and four-variable KFRE models showed excellent predictive performance and discrimination (eight-variable: C-index 0.872, 95% confidence interval [CI] 0.850–0.894, adequacy index 97.3%; four-variable: C-index 0.874, 95% CI 0.852–0.896, adequacy index 97.9%). There was no incremental improvement in the prediction ability of the eight-variable model over the four-variable model in this cohort. CONCLUSION The KFRE was validated in a multi-ethnic Singapore CKD cohort. This risk score may help to identify patients requiring early renal care.

Background: Obesity is associated with cardiovascular disease (CVD) risk factors (hypertension, dyslipidemia and diabetes) and metabolic syndrome (MetS), and it may be flawed that most studies only use one obesity index to predict these risk factors. Therefore, our study aims to compare the various combined obesity indices systematically, and to find the optimal combined obesity indices to predict CVD risk factors and MetS. Methods: A total of 16,766 participants aged 18–79 years old were recruited in Jilin Province in 2012. Receiver operating characteristic curve (ROC) curves and multiple logistic regressions were used to evaluate the predictive capacity of the combined obesity indices for CVD risk factors and MetS. Results: The adjusted area under receiver operating characteristic (AUROC) with two combined obesity indices had been improved up to 19.45%, compared with one single obesity index. In addition, body mass index (BMI) and waist circumference (WC) were the optimal combinations, where the AUROC (95% confidence interval (CI)) for hypertension, dyslipidemia, diabetes and MetS in males were 0.730 (0.718, 0.740), 0.694 (0.682, 0.706), 0.725 (0.709, 0.742) and 0.820 (0.810, 0.830), and in females were 0.790 (0.780, 0.799), 0.727 (0.717, 0.738), 0.746 (0.731, 0.761) and 0.828 (0.820, 0.837), respectively. Conclusions: The more abnormal obesity indices that one has the higher the risk for CVD risk factors and MetS, especially in males. In addition, the combined obesity indices have better predictions than one obesity index, where BMI and WC are the optimal combinations.

Carotenoid levels are inversely associated with blood pressure (BP). This study focused on the effects of individual and combined serum carotenoids on BP and hypertension, which have not been established to date. Data from National Health and Nutrition Examination Survey (NHANES) 2001–2006 were analyzed in this cross-sectional study. Multivariate logistic, linear, and weighted quantile sum (WQS) regression analyses were applied to explore the associations of six serum carotenoids (α-carotene, β-cryptoxanthin, lutein/zeaxanthin, trans-lycopene, trans-β-carotene, and cis-β-carotene), individually and in combination, with BP/hypertension. The linearity of correlations was further assessed using restricted cubic spline (RCS) regression. A total of 11,336 adults were included for analysis. Data from multivariate models showed that all six carotenoids were independently and negatively associated with both systolic blood pressure (SBP) and diastolic blood pressure (DBP; all p < 0.05). Compared to the first quartile, the fourth quartile of α-carotene (odds ratio [OR] = 0.64 [0.52–0.77]), β-cryptoxanthin (OR = 0.74 [0.60–0.90]), trans-β-carotene (OR = 0.50 [0.40–0.61]), and cis-β-carotene (OR = 0.47 [0.35–0.64]) were significantly and inversely related to hypertension (all p < 0.05). Moreover, WQS analysis revealed that the combination of all six serum carotenoids was negatively associated with BP and hypertension (all P<0.001), among which trans-β-carotene was the most significant contributor to the protective effect against hypertension (weight, 59.50%). Dose-response analyses demonstrated a linear inverse association of all carotenoids with hypertension (p for non-linearity > 0.05). Our collective findings indicate that higher levels of all six mixed serum carotenoids are correlated with decreased prevalence of hypertension, among which β-carotene exerts the most significant effect, which may provide a basis and direction for further studies.