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Title: A Clinical Risk Prediction Tool for Peritonitis-Associated Treatment Failure in Peritoneal Dialysis Patients
Authors: Surapon Nochaiwong
Chidchanok Ruengorn
Kiatkriangkrai Koyratkoson
Kednapa Thavorn
Ratanaporn Awiphan
Chayutthaphong Chaisai
Sirayut Phatthanasobhon
Kajohnsak Noppakun
Yuttitham Suteeka
Setthapon Panyathong
Phongsak Dandecha
Wilaiwan Chongruksut
Sirisak Nanta
Yongyuth Ruanta
Apichart Tantraworasin
Uraiwan Wongsawat
Boontita Praseartkul
Kittiya Sattaya
Suporn Busapavanich
Keywords: Multidisciplinary
Issue Date: 1-Dec-2018
Abstract: © 2018, The Author(s). A tool to predict peritonitis-associated treatment failure among peritoneal dialysis (PD) patients has not yet been established. We conducted a multicentre, retrospective cohort study among 1,025 PD patients between 2006 and 2016 in Thailand to develop and internally validate such a tool. Treatment failure was defined as either a requirement for catheter removal, a switch to haemodialysis, or peritonitis-associated mortality. Prediction model performances were analysed using discrimination (C-statistics) and calibration (Hosmer-Lemeshow test) tests. Predictors were weighted to calculate a risk score. In total, 435 patients with 855 episodes of peritonitis were identified; 215 (25.2%) episodes resulted in treatment failure. A total risk score of 11.5 was developed including, diabetes, systolic blood pressure <90 mmHg, and dialysate leukocyte count >1,000/mm3and >100/mm3on days 3–4 and day 5, respectively. The discrimination (C-statistic = 0.92; 95%CI, 0.89–0.94) and calibration (P > 0.05) indicated an excellent performance. No significant difference was observed in the internal validation cohort. The rate of treatment failure in the different groups was 3.0% (low-risk, <1.5 points), 54.4% (moderate-risk, 1.5–9 points), and 89.5% (high-risk, >9 points). A simplified risk-scoring scheme to predict treatment failure may be useful for clinical decision making regarding PD patients with peritonitis. External validation studies are needed.
ISSN: 20452322
Appears in Collections:CMUL: Journal Articles

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