Association Between Comprehensive Nutritional Scoring System (CNSS) and Outcomes of Continuous Ambulatory Peritoneal Dialysis Patients

Albumin-globulin ratio and mortality in patients on peritoneal dialysis: a retrospective study

Background

Albumin-globulin ratio (AGR), a variable based on serum albumin and non-albumin proteins, has been demonstrated as a predictor of mortality in patients with malignant neoplasm. The aim of this study was to evaluate the prognostic value of AGR on peritoneal dialysis (PD) patients.

Methods

We retrospectively analyzed 602 incident PD patients from January 1st, 2008, to December 31st, 2017, at our center and followed them until December 31st, 2018. Kaplan-Meier curves and multivariate Cox regression models were applied to analyze the association between AGR and all-cause of mortality and cardiovascular mortality.

Results

The median follow-up time was 32.17 (interquartile range = 32.80) months. During follow-up, 131 (21.8%) patients died, including 57 patients (43.5%) who died due to cardiovascular diseases. Kaplan-Meier curves showed that patients with AGR > 1.26 had better rates of survival than those with AGR ≤ 1.25 (p < 0.001). After adjusting for potential confounders, the lower AGR level was significantly associated with an increased all-cause and cardiovascular mortality [hazard ratio (HR): 1.57, 95% confidence interval (CI): 1.07–2.32, p = 0.022 and HR: 2.01, 95% CI: 1.10–3.69, p = 0.023 respectively].

Conclusions

Patients with a low AGR level had an increased all-cause and cardiovascular mortality. AGR may be a useful index in identifying patients on PD at risk for CVD and all-cause of mortality.

Development of a risk prediction model for infection-related mortality in patients undergoing peritoneal dialysis

Background

Assessment of infection-related mortality remains inadequate in patients undergoing peritoneal dialysis. This study was performed to develop a risk model for predicting the 2-year infection-related mortality risk in patients undergoing peritoneal dialysis.

Methods

The study cohort comprised 606 patients who started and continued peritoneal dialysis for 90 at least days and was drawn from the Fukuoka Peritoneal Dialysis Database Registry Study in Japan. The patients were registered from 1 January 2006 to 31 December 2016 and followed up until 31 December 2017. To generate a prediction rule, the score for each variable was weighted by the regression coefficients calculated using a Cox proportional hazard model adjusted by risk factors for infection-related mortality, including patient characteristics, comorbidities, and laboratory data.

Results

During the follow-up period (median, 2.2 years), 138 patients died; 58 of them of infectious disease. The final model for infection-related mortality comprises six factors: age, sex, serum albumin, serum creatinine, total cholesterol, and weekly renal Kt/V. The incidence of infection-related mortality increased linearly with increasing total risk score (P for trend <0.001). Furthermore, the prediction model showed adequate discrimination (c-statistic = 0.79 [0.72–0.86]) and calibration (Hosmer–Lemeshow test, P = 0.47).

Conclusion

In this study, we developed a new model using clinical measures for predicting infection-related mortality in patients undergoing peritoneal dialysis.