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Development and validation of a nomogram to predict protein-energy wasting in patients with peritoneal dialysis: a multicenter cohort study.
Mei, Ziwei; Zhu, Bin; Sun, Xiaoli; Zhou, Yajie; Qiu, Yuanyuan; Ye, Xiaolan; Zhang, Hongjuan; Lu, Chunlan; Chen, Jun; Zhu, Hong.
Afiliación
  • Mei Z; Lishui Municipal Central Hospital, Lishui, China.
  • Zhu B; Zhejiang Provincial People's Hospital, Hangzhou, China.
  • Sun X; Lishui Municipal Central Hospital, Lishui, China.
  • Zhou Y; Lishui Municipal Central Hospital, Lishui, China.
  • Qiu Y; Longquan People's Hospital, Longquan, China.
  • Ye X; Zhejiang Provincial People's Hospital, Hangzhou, China.
  • Zhang H; Zhejiang Provincial People's Hospital, Hangzhou, China.
  • Lu C; Zhejiang Provincial People's Hospital, Hangzhou, China.
  • Chen J; Zhejiang Chinese Medical University, Hangzhou, China.
  • Zhu H; Lishui Municipal Central Hospital, Lishui, China.
PeerJ ; 11: e15507, 2023.
Article en En | MEDLINE | ID: mdl-37304869
ABSTRACT

Background:

Protein-energy wasting (PEW) is a common complication in patients with peritoneal dialysis (PD). Few investigations involved risk factors identification and predictive model construction related to PEW. We aimed to develop a nomogram to predict PEW risk in patients with peritoneal dialysis.

Methods:

We collected data from end-stage renal disease (ESRD) patients who regularly underwent peritoneal dialysis between January 2011 and November 2022 at two hospitals retrospectively. The outcome of the nomogram was PEW. Multivariate logistic regression screened predictors and established a nomogram. We measured the predictive performance based on discrimination ability, calibration, and clinical utility. Evaluation indicators were receiver operating characteristic (ROC), calibrate curve, and decision curve analysis (DCA). The performance calculation of the internal validation cohort validated the nomogram.

Results:

In this study, 369 enrolled patients were divided into development (n = 210) and validation (n = 159) cohorts according to the proportion of 64. The incidence of PEW was 49.86%. Predictors were age, dialysis duration, glucose, C-reactive protein (CRP), creatinine clearance rate (Ccr), serum creatinine (Scr), serum calcium, and triglyceride (TG). These variables showed a good discriminate performance in development and validation cohorts (ROC = 0.769, 95% CI [0.705-0.832], ROC = 0.669, 95% CI [0.585-0.753]). This nomogram was adequately calibrated. The predicted probability was consistent with the observed outcome.

Conclusion:

This nomogram can predict the risk of PEW in patients with PD and provide valuable evidence for PEW prevention and decision-making.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Diálisis Renal / Diálisis Peritoneal Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: PeerJ Año: 2023 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Diálisis Renal / Diálisis Peritoneal Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: PeerJ Año: 2023 Tipo del documento: Article País de afiliación: China