SynthesisInternational urology and nephrology2026
Risk prediction models for peritoneal dialysis-associated peritonitis: a systematic review and meta-analysis.
Synthesis in International urology and nephrology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Metabolic Mechanisms of Neutrophil Phagocytic Activity in Patients with Widespread Purulent Peritonitis Bacterial Peritonitis Before and After Surgery.International journal of molecular sciences · 2026Article
- Comment on "Predictive value of the C-reactive protein-albumin-lymphocyte (CALLY) index for all-cause mortality in peritoneal dialysis patients".International urology and nephrology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
backgroundPeritoneal dialysis-associated peritonitis (PDAP) remains a major complication in patients undergoing peritoneal dialysis (PD), often leading to technique failure, hospitalization, and increased mortality. This study aims to systematically evaluate and compare existing risk prediction models for PDAP and quantify their overall performance and key predictors.
methodsFollowing PRISMA guidelines, eight databases were systematically searched including PubMed, Web of Science, Cochrane Library, Embase, China National Knowledge Infrastructure (CNKI), Chinese Science and Technology Journal Database (VIP), Wanfang, and SinoMed, covering literature from their inception to March 19, 2025. Data extraction focused on study design, participant characteristics, sample size, outcome definitions, predictors, and model performance. The bias risk assessment tool for prediction model studies (PROBAST) was employed to assess bias risk and applicability, while Stata 17.0 facilitated meta-analysis.
resultsEleven studies involving 11 logistic regression models were included. The reported area under the curve (AUC) values ranged from 0.659 to 0.997, with a combined AUC of 0.88 (95% CI 0.83-0.93), indicating robust predictive performance. Four predictors associated with peritonitis were albumin (Alb) (OR = 0.672; 95% CI 0.475-0.868; P < 0.001), C-reactive protein (CRP) (OR = 2.568; 95% CI 1.081-4.055; P < 0.001), neutrophil-to-lymphocyte ratio (NLR) (OR = 1.377; 95% CI 1.065-1.689; P < 0.001), and diabetes mellitus (DM) (OR = 3.549; 95% CI 1.272-5.825; P < 0.002).
conclusionsDespite demonstrating strong predictive capabilities, the models exhibited high bias risks, primarily due to data sources and statistical methods. Future research should prioritize large-scale, multicenter studies with rigorous designs and external validation to enhance reliability and clinical applicability.
Indexed as
Identifiers
40975843What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.