A nomogram for predicting the risk of peritoneal dialysis-associated peritonitis in patients with end-stage renal disease undergoing peritoneal dialysis: model development and validation study DOI Creative Commons
Yuehong Wang, Zhimin Wu, Li‐Ting Huang

et al.

BMC Nephrology, Journal Year: 2025, Volume and Issue: 26(1)

Published: May 19, 2025

This study aimed to develop and validate a nomogram predict the risk of peritoneal dialysis-associated peritonitis (PDAP) in patients undergoing peritopreneal dialysis. A retrospective analysis was conducted on clinical data from 376 at Nanhai District People's Hospital Foshan City, Guangdong Province, between December 2017 2024. The dataset randomly divided into training set (n = 244) validation 132). Risk factors for PDAP were identified using Least Absolute Shrinkage Selection Operator (LASSO) regression logistic regression, predictive developed validated R4.1.3. model's performance evaluated through receiver operating characteristic (ROC) curves, Hosmer-Lemeshow goodness-of-fit test, decision curve (DCA), impact curves (CICs). Eight potential predictors selected by LASSO analysis. Multivariate confirmed that age, dialysis duration, albumin, hemoglobin, β2-microglobulin, Potassium lymphocyte count independent occurrence (P 0.001). nomogram's area under (AUC) 0.929 (95% CI: 0.896-0.962) 0.905 0.855-0.955) set. test indicated good model fit (training χ2 13.181, P 0.106; 8.264, 0.408). Both DCA CIC revealed had utility predicting PDAP. proposed exhibited excellent utility, providing valuable tool early identification intervention Further external prospective studies are recommended.

Language: Английский

A Nomogram for Predicting the Risk of Peritoneal Dialysis-Associated Peritonitis in Patients with End-Stage Renal Disease Undergoing Peritoneal Dialysis: Model Development and Validation Study DOI Creative Commons

Yi-Ying Wang,

Zhimin Wu, Li‐Ting Huang

et al.

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: March 31, 2025

Abstract Objective: This study aimed to develop and validate a nomogram predic the risk of peritoneal dialysis-associated peritonitis (PDAP) in patients undergoing dialysis. Methods: A retrospective analysis was conducted on clinical data from 376 at Nanhai District People's Hospital Foshan City, Guangdong Province, between December 2017 2024. The dataset randomly divided into training set (n =244) validation =132). Risk factors for PDAP were identified using Least Absolute Shrinkage Selection Operator（LASSO） regression logistic regression, predictive developed validated R4.1.3. model’s performance evaluated through receiver operating characteristic (ROC) curves, Hosmer-Lemeshow goodness-of-fit test, decision curve (DCA), impact curves (CICs). Results: Eight potential predictors selected by LASSO analysis. Multivariate confirmed that age, dialysis duration, albumin, hemoglobin, β2-microglobulin, Potassium lymphocyte count independent occurrence（P=0.001）. nomogram’s area under (AUC) 0.929 (95% CI: 0.896-0.962) 0.905 0.855-0.955) set. test indicated good model fit (training χ2=13.181, P=0.106; χ2=8.264, P=0.408). Both DCA CIC revealed had utility predicting PDAP. Conclusion: proposed exhibited excellent utility, providing valuable tool early identification intervention Further external prospective studies are recommended.

Language: Английский

Citations

0
Development and validation of a nomogram for predicting low Kt/Vurea in peritoneal dialysis patients DOI Creative Commons

Danfeng Zhang,

Tian Zhao,

Liting Gao

et al.

BMC Nephrology, Journal Year: 2025, Volume and Issue: 26(1)

Published: May 2, 2025

Language: Английский

Citations

0
A nomogram for predicting the risk of peritoneal dialysis-associated peritonitis in patients with end-stage renal disease undergoing peritoneal dialysis: model development and validation study DOI Creative Commons
Yuehong Wang, Zhimin Wu, Li‐Ting Huang

et al.

BMC Nephrology, Journal Year: 2025, Volume and Issue: 26(1)

Published: May 19, 2025

This study aimed to develop and validate a nomogram predict the risk of peritoneal dialysis-associated peritonitis (PDAP) in patients undergoing peritopreneal dialysis. A retrospective analysis was conducted on clinical data from 376 at Nanhai District People's Hospital Foshan City, Guangdong Province, between December 2017 2024. The dataset randomly divided into training set (n = 244) validation 132). Risk factors for PDAP were identified using Least Absolute Shrinkage Selection Operator (LASSO) regression logistic regression, predictive developed validated R4.1.3. model's performance evaluated through receiver operating characteristic (ROC) curves, Hosmer-Lemeshow goodness-of-fit test, decision curve (DCA), impact curves (CICs). Eight potential predictors selected by LASSO analysis. Multivariate confirmed that age, dialysis duration, albumin, hemoglobin, β2-microglobulin, Potassium lymphocyte count independent occurrence (P 0.001). nomogram's area under (AUC) 0.929 (95% CI: 0.896-0.962) 0.905 0.855-0.955) set. test indicated good model fit (training χ2 13.181, P 0.106; 8.264, 0.408). Both DCA CIC revealed had utility predicting PDAP. proposed exhibited excellent utility, providing valuable tool early identification intervention Further external prospective studies are recommended.

Language: Английский

Citations

0