Predicting catheter removal in peritoneal dialysis peritonitis patients visiting the emergency department: a multivariable logistic regression and decision tree analysis

Peritonitis is a debilitating complication of peritoneal dialysis (PD). Identifying high-risk patients requiring PD catheter removal based on early information in the emergency room (ER) is critical. This cross-sectional study included 518 PD patients who visited the ER in the Chang Gung Memorial Hospital, Chia-Yi branch between 2002 and 2018. Among the 518 PD patients, 31 (6%) required PD catheter removed during the visit. Decision tree analysis, incorporating five key factors (neutrophil count, CRP, age, sodium, and albumin), identified 16 terminal nodes (TNs), with four higher risk groups (> 20%): lower neutrophils with lower CRP and younger age (TN1), lower neutrophils with higher CRP (TN4), higher neutrophils with moderate age and lower albumin (TN14), and high neutrophils with older age (TN16). Decision tree analysis effectively predicts the optimal timing for catheter removal in PD peritonitis patients. Clinically, this approach helps reduce mortality resulting from delayed catheter removal.

Authors

Institutions

Publication Details

Journal
Updates in Surgery
Published
2025-05-25
DOI
https://doi.org/10.1007/s13304-025-02256-4
Primary Topic
Dialysis and Renal Disease Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Predicting catheter removal in peritoneal dialysis peritonitis patients visiting the emergency department: a multivariable logistic regression and decision tree analysis

Shih-Jiun Lin, Yung‐Chien Hsu, Da-Wei Lin, Cheng‐Chih Chang et al.
Updates in Surgery
Dialysis and Renal Disease Management
article

Predicting catheter removal in peritoneal dialysis peritonitis patients visiting the emergency department: a multivariable logistic regression and decision tree analysis

Shih-Jiun Lin, Yung‐Chien Hsu, Da-Wei Lin, Cheng‐Chih Chang, Ching-Chuan Hsieh, Chun‐Liang Lin, Ya‐Hsueh Shih, Cheng-Chi Liu, David Ming Then Tsai
article en

Abstract

Peritonitis is a debilitating complication of peritoneal dialysis (PD). Identifying high-risk patients requiring PD catheter removal based on early information in the emergency room (ER) is critical. This cross-sectional study included 518 PD patients who visited the ER in the Chang Gung Memorial Hospital, Chia-Yi branch between 2002 and 2018. Among the 518 PD patients, 31 (6%) required PD catheter removed during the visit. Decision tree analysis, incorporating five key factors (neutrophil count, CRP, age, sodium, and albumin), identified 16 terminal nodes (TNs), with four higher risk groups (> 20%): lower neutrophils with lower CRP and younger age (TN1), lower neutrophils with higher CRP (TN4), higher neutrophils with moderate age and lower albumin (TN14), and high neutrophils with older age (TN16). Decision tree analysis effectively predicts the optimal timing for catheter removal in PD peritonitis patients. Clinically, this approach helps reduce mortality resulting from delayed catheter removal.

Updates in Surgery
St. Martin de Porres Hospital (TW), Chiayi Chang Gung Memorial Hospital (TW)
Good health and well-being
Openalex Percentile: Top 86%
Dialysis and Renal Disease Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Predicting catheter removal in peritoneal dialysis peritonitis patients visiting the emergency department: a multivariable logistic regression and decision tree analysis — Shih-Jiun Lin, Yung‐Chien Hsu, et al. · Updates in Surgery (2025) | TGRS Research Map | TGRS