ArticlePeerJ2023
Development and validation of a nomogram to predict protein-energy wasting in patients with peritoneal dialysis: a multicenter cohort study.
Article in PeerJ, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.
- Risk prediction models for malnutrition in dialysis patients in China: a systematic review and meta-analysis.Renal failure · 2026Pooled it
- Development and validation of a machine learning-based prediction model for malnutrition risk in peritoneal dialysis patients: a multi‑center retrospective study.International urology and nephrology · 2026Article
- Development and Validation of a Risk-Prediction Nomogram for Nutritional Risk in Non-Dialysis Chronic Renal Failure Patients.Risk management and healthcare policy · 2026Article
- Analysis of risk factors for depression in peritoneal dialysis patients and establishment of a risk nomogram model.Clinics (Sao Paulo, Brazil) · 2025Article
- External validation of a novel nomogram for diagnosis of Protein Energy Wasting in adult hemodialysis patients.Frontiers in nutrition · 2024Article
Corrections and comments
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Authors and funding
10 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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 ( 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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