ArticleFrontiers in medicine2022
Development and Validation of a Prediction Model for the Cure of Peritoneal Dialysis-Associated Peritonitis: A Multicenter Observational Study.
Article in Frontiers in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed, 10 citations in OpenAlex.
- Development of risk-prediction tool for peritoneal dialysis related peritonitis and external validation in the PDTAP cohort.Chinese medical journal · 2026Article
- A predictive model of treatment effectiveness of refractory peritoneal dialysis-related peritonitis in patients with peritoneal dialysis: a single-center observational study in South China.Clinical kidney journal · 2024Article
- Application of metagenomic next-generation sequencing technology in the etiological diagnosis of peritoneal dialysis-associated peritonitis.Open life sciences · 2024Article
- Technique failure in peritoneal dialysis-related peritonitis: risk factors and patient survival.Renal failure · 2023Article
- Effect of different dialysis duration on the prognosis of peritoneal dialysis-associated peritonitis: a single-center, retrospective study.Renal failure · 2023Article
- Random forest can accurately predict the technique failure of peritoneal dialysis associated peritonitis patients.Frontiers in medicine · 2023Article
- Construction and validation of a predictive model for the risk of peritoneal dialysis-associated peritonitis after peritoneal dialysis catheterization.Frontiers in medicine · 2023Article
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Authors and funding
10 authors at 3 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Aim: Peritoneal dialysis (PD)-associated peritonitis (PDAP) is a severe complication of PD. It is an important issue about whether it can be cured. At present, there is no available prediction model for peritonitis cure. Therefore, this study aimed to develop and validate a prediction model for peritonitis cure in patients with PDAP. Methods: Patients with PD who developed PDAP from four dialysis centers in Northeast China were followed up. According to the region of PD, data were divided into training and validation datasets. Initially, a nomogram for peritonitis cure was established based on the training dataset. Later, the nomogram performance was assessed by discrimination (C-statistic), calibration, and decision curves. Results: Totally, 1,011 episodes of peritonitis were included in the final analysis containing 765 in the training dataset and 246 in the validation dataset. During the follow-up period, peritonitis cure was reported in 615 cases from the training dataset and 198 from the validation dataset. Predictors incorporated in the final nomogram included PD duration, serum albumin, antibiotics prior to admission, white cell count in peritoneal dialysate on day 5 (/μl) ≥ 100/μl, and type of causative organisms. The C-statistic values were 0.756 (95% CI: 0.713-0.799) in the training dataset and 0.756 (95% CI: 0.681-0.831) in the validation dataset. The nomogram exhibited favorable performance in terms of calibration in both the training and validation datasets. Conclusion: This study develops a practical and convenient nomogram for the prediction of peritonitis cure in patients with PDAP, which assists in clinical decision-making.
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