Literature DB >> 33546035

Analysis of risk factors and construction of prediction model of drop out from peritoneal dialysis.

Li Li1,2, Hualian Pei3, Zhenhui Liu4, Jingjing Zhang1.   

Abstract

ABSTRACT: This study is to investigate the risk factors for the drop out from peritoneal dialysis.We retrospectively analyzed patients who underwent catheterization between January 1, 2009 and September 30, 2019. The follow-up period ended on November 30, 2019. End point events were the cessation of peritoneal dialysis, including death, conversion to hemodialysis, and kidney transplantation. Kaplan-Meier method was used to analyze peritoneal dialysis curve. Significant factors were included in the multivariate Cox proportional hazards model. Calibration curve was plotted.A total of 377 patients were included in this study. The dropout rate of peritoneal dialysis was 41.38%. The main drop out reason was conversion to hemodialysis, accounting for 41.67% of the total number of drop out, followed by kidney transplantation (28.21%) and death (25%). According to multivariable Cox proportional hazards model analysis, the medium education level (hazard ratio (HR): 2.53, 95% confidence interval (CI): 1.08-5.91, P = .03), high education level (HR: 2.47, 95% CI: 1.03-5.93, P = .04), diabetes (HR: 1.87, 95% CI: 1.24-2.83, P < .03), hypertension (HR: 2.40, 95% CI: 1.64-3.51, P < .01), repeated peritonitis (HR: 5.18, 95% CI: 3.04-8.80, P < .01), and repeated chest complications (HR: 4.98, 95% CI: 2.79-8.89, P < .01) were independent risk factors for dropping out from peritoneal dialysis, while the number of hospitalizations after catheterization (HR: 0.94, 95% CI: 0.89-0.98, P = .01) was protective factor for maintenance of peritoneal dialysis. The C index of the prediction model was 0.74.Higher education level, diabetes, hypertension, repeated peritonitis, and repeated chest complications were the risk factors of dropping out from peritoneal dialysis, while higher number of hospitalizations after catheterization was a protective factor for the maintenance of peritoneal dialysis. The nomogram could predict the probability of dropping out from peritoneal dialysis.
Copyright © 2021 the Author(s). Published by Wolters Kluwer Health, Inc.

Entities:  

Year:  2021        PMID: 33546035     DOI: 10.1097/MD.0000000000024195

Source DB:  PubMed          Journal:  Medicine (Baltimore)        ISSN: 0025-7974            Impact factor:   1.889


  1 in total

1.  Establishment of a Nomogram Model for Predicting Cardiovascular and Cerebrovascular Events in Diabetic Nephropathy Patients Receiving Maintenance Hemodialysis.

Authors:  Xiaobing Liu; Caili Yan; Xiuxiu Niu; Jiechun Zeng
Journal:  Appl Bionics Biomech       Date:  2022-07-07       Impact factor: 1.664

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.