Background and aims: Dyslipidemia is common in patients with chronic kidney disease and particular prevalent in patients receiving peritoneal dialysis. However, whether markers of atherogenic dyslipidemia correlate with outcomes in dialysis patients as in the general population is uncertain. The aim of this study was to explore the prognostic value of the serum triglyceride/HDL cholesterol (TG/HDL-C) ratio and non-HDL-C/HDL-C ratio to predict mortality in peritoneal dialysis patients. Methods: Two hundred fourteen peritoneal dialysis patients were retrospectively analyzed from January 2011 to December 2015, with a median follow-up of 59 months. We used receiver operating curves (ROC) to determine the optimal threshold for TG/HDL-C and non-HDL/HDL-C ratios at baseline to predict overall survival during follow-up. Prognostic values were accessed by univariate and multivariate COX regression analysis and Kaplan-Meier curve. A predictive nomogram was developed to predict prognosis for overall survival, and the predictive accuracy was evaluated by concordance index (c-index). Results: The optimal cut-off values for TG/HDL-C ratio and non-HDL-C/HDL-C ratio to predict mortality were 1.94 and 2.86, respectively. A high TG/HDL-C ratio and a high non-HDL-C/HDL-C ratio strongly correlated with worse overall survival in peritoneal dialysis patients. Multivariate analysis demonstrated that elevated TG/HDL-C ratio (HR 3.57, 95% CI 1.99, 6.39, P < 0.000) as well as non-HDL/HDL-C ratio (HR 2.58, 95%CI 1.39–4.81, P = 0.003) were independent markers to predict reduced OS. A nomogram was constructed to predict overall survival, with a c-index for predictive accuracy of 0.795. Conclusion: TG/HDL-C ratio and non-HDL-C/HDL-C may serve as potential prognostic biomarkers in PD patients.

Background: Zinc is an essential trace element involved in multiple metabolic processes. Acute kidney injury (AKI) is associated with low plasma zinc, but outcomes with zinc supplementation in critically ill patients with AKI remain unknown. Our objective was to investigate the effectiveness of zinc supplementation in this patient population.Methods: Critically ill patients with AKI were identified from the Medical Informative Mart for Intensive Care IV database. Prosperity score matching (PSM) was applied to match patients receiving zinc treatment to those without zinc treatment. The association between zinc sulfate use and in-hospital mortality and 30-day mortality, need for renal replacement therapy (RRT), and length of stay was determined by logistic regression and Cox proportional hazards modeling.Results: A total of 9,811 AKI patients were included in the study. PSM yielded 222 pairs of patients who received zinc treatment and those who did not. Zinc supplementation was associated with reduced in-hospital mortality (HR = 0.48 (95% CI: 0.28, 0.83) P = 0.009) and 30-day mortality (HR = 0.51 (95% CI, 0.30, 0.86) P = 0.012). In the subgroup analysis, zinc use was associated with reduced in-hospital mortality in patients with stage 1 AKI and those with sepsis.Conclusions: Zinc supplementation was associated with improved survival in critically ill patients with AKI. The supplementation was especially effective in those with stage 1 AKI and sepsis. These results need to be verified in randomized controlled trials.

Background and aims: Acute hyperglycemia has been identified as a risk factor for acute kidney injury occurrence and mortality in various diseases. The aim of the current study was to investigate the relationship between stress-induced hyperglycemia and adverse outcomes in critically ill patients with AKI. Methods: We extracted clinical data from Multiparameter Intelligent Monitoring in Intensive Care III version 1.4. Blood glucose and glycosylated hemoglobin during the first 24 h of ICU admission were used to calculate glycemic gap and stress hyperglycemia ratio (SHR). The outcomes included ICU mortality and need for renal replacement therapy. The association of the glycemic gap and SHR with outcomes were determined via logistic regression model and receiver-operating curves. The subgroup analysis of patients with and without diabetes was performed separately. Results: Higher glycemic gap and SHR were observed in patients who had increased need of RRT, higher mortality rates and longer ICU stay. Multivariate analysis demonstrated that higher glycemic gap (OR 1.01, 95%CI 1.00-1.02, P = 0.015), as well as SHR (OR 1.32; 95%CI 1.07–1.64, P = 0.009), were independently associated with ICU mortality after adjusting for potential covariates. In subgroup analysis, the association of glycemic gap and SHR were only significant in the non-diabetic population as for the outcome of ICU mortality (OR 2.25, 95%CI 1.64–3.08, P < 0.001 and OR 1.99; 95%CI 1.46–2.72, P < 0.001, respectively). Conclusions: The glycemic gap and SHR might serve as a potential prognostic indicator of ICU mortality in critically ill patients with AKI, especially in the non-diabetic population.

Background: Inflammation has been reported to be involved in carcinogenesis and cancer progression. This study was designed to explore the prognostic significance of lymphocyte-to-monocyte ratio (LMR) and serum C-reactive protein (CRP) in nonmetastatic clear cell renal cell carcinoma (ccRCC) patients after treatment. Methods: The retrospective study consisted of 985 patients with ccRCC who had undergone nephrectomy from 2005 to 2010 at multiple centers. The patients were divided into four groups using a quartile of LMR or CRP, and their associations with clinical characteristics and outcome were systematically estimated. Results: Both low LMR and high CRP significantly diminished overall survival (OS) and metastasis-free survival (MFS) in patients with ccRCC. Further investigation indicated that LMR and CRP were independent prognostic factors of both OS and MFS. Integration of LMR and CRP into a predictive model, including significant variables in multivariate analysis, established a nomogram to predict accurately the 3- and 5-year survival for nonmetastatic patients with ccRCC. Conclusion: LMR and CRP represent independent prognostic factors of OS and MFS for patients with ccRCC. Incorporation of LMR and CRP into the traditional TNM staging system may improve their predictive performance.

Fibrinogen to albumin ratios (FAR) have shown to be a promising prognostic factor for improving the predictive accuracy in various diseases. This study explores FAR's prognostic significance in critically ill patients with acute kidney injury (AKI). All clinical data were extracted from the Multiparameter Intelligent Monitoring in Intensive Care Database III version 1.4. All patients were divided into four groups based on FAR quartiles. The primary endpoint was in-hospital mortality. A generalized additive model was applied to explore a nonlinear association between FAR and in-hospital mortality. The Cox proportional hazards models were used to determine the association between FAR and in-hospital mortality. A total of 5001 eligible subjects were enrolled. Multivariate analysis demonstrated that higher FAR was an independent predictor of in-hospital mortality after adjusting for potential confounders (HR, 95% CI 1.23, 1.03–1.48, P = 0.025). A nonlinear relationship between FAR and in-hospital mortality was observed. FAR may serve as a potential prognostic biomarker in critically patients with AKI and higher FAR was associated with increased risk of in-hospital mortality among these patients.

Background: Though the albumin-to-alkaline phosphatase ratio (AAPR) is used as a biomarker in various diseases, little is known about its effect on outcomes after peritoneal dialysis (PD).Methods: This multicenter retrospective study comprised 357 incident PD patients stratified according to the AAPR. Propensity score matching (PSM) was performed to identify 85 patients for a well-matched comparison of all-cause and cardiovascular mortality. Using Cox regression, we performed univariate and multivariate analyses to investigate the prognostic value of the AAPR and established a Kaplan-Meier curve-predicted nomogram to estimate expected overall survival (OS). We assessed the predictive accuracy using the concordance index (c-index).Results: We found that the optimal cut-off of the AAPR to predict mortality was 0.36. In the present cohort of patients undergoing PD, a low AAPR strongly correlated with worse OS. In the multivariate analysis, the AAPR was shown to be an independent marker predicting reduced OS both before [hazard ratio (HR) 1.68, 95% confidence interval (CI) 1.08–2.60, P = 0.020] and after PSM (HR 1.96, 95% CI 1.06–3.62, P = 0.020). We also observed significant differences in OS in several subgroups, but not the group of patients with comorbidities. A nomogram was established to predict overall survival, with a c-index for prediction accuracy was 0.71 after PSM.Conclusion: AAPR has potential as an independent prognostic biomarker in patients undergoing PD.