Evidence map›Paper›PMID 42100845›Full record

ArticleJBI evidence synthesis2026

Predictive models for patients treated with or evaluated for peritoneal dialysis: a scoping review protocol.

Jakub Ruszkowski, Sudha Ramakrishnan, Julia Strzelec, Weronika Roztkowska, Alicja M Dębska-Ślizień, Monika Lichodziejewska-Niemierko

Abstract read
In one paragraph

Article in JBI evidence synthesis, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Jakub RuszkowskiDepartment of Nephrology, Transplantology and Internal Medicine, Faculty of Medicine, Medical University of Gdańsk, Gdańsk, Poland.ORCID 0000-0002-9666-9627
Sudha RamakrishnanBaylor Scott and White Health Library, Dallas, TX, USA.ORCID 0000-0003-2710-9690
Julia StrzelecStudent Scientific Circle at the Department of Nephrology, Transplantology and Internal Medicine, Faculty of Medicine, Medical University of Gdańsk, Gdańsk, Poland.ORCID 0009-0000-5273-7280
Weronika RoztkowskaStudent Scientific Circle at the Department of Nephrology, Transplantology and Internal Medicine, Faculty of Medicine, Medical University of Gdańsk, Gdańsk, Poland.ORCID 0009-0005-5506-4233
Alicja M Dębska-ŚlizieńDepartment of Nephrology, Transplantology and Internal Medicine, Faculty of Medicine, Medical University of Gdańsk, Gdańsk, Poland.ORCID 0000-0001-8210-8063
Monika Lichodziejewska-NiemierkoDepartment of Nephrology, Transplantology and Internal Medicine, University Clinical Center, Gdańsk, Poland.ORCID 0000-0002-0262-3493

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis scoping review will map available research regarding predictive models for clinical and patient-reported outcomes in patients receiving or considered for peritoneal dialysis.

introductionChronic kidney disease affects over 840 million people worldwide, with peritoneal dialysis offering a home-based kidney replacement therapy. Although evidence demonstrates equivalent long-term survival between dialysis modalities, the individual patient prognosis may favor a particular modality, making personalized outcome prediction essential. Available research evidence is not reflected in guideline recommendations, with clinicians relying on clinical experience rather than evidence-based prediction models. An evaluation of prediction models is required to identify validated tools and guide their clinical implementation. ELIGIBILITY CRITERIA: This review will include patients receiving peritoneal dialysis or who are being considered for initiation, with no restrictions regarding age, modality, or chronicity of disease. The scope will encompass the development, validation, and evaluation of clinical models utilizing multiple predictors for peritoneal dialysis-relevant outcomes. Any health care setting will be included, with no geographic or language restrictions.

methodsMEDLINE (Ovid), Embase, Web of Science Core Collection, and Scopus will be searched, complemented by citation tracking and gray literature searches. Two independent reviewers will conduct title/abstract screening and full-text assessment using predefined criteria. Data extraction will be performed using standardized forms combining CHARMS, TRIPOD+AI, PROBAST, and PROGRESS-Plus. Data synthesis will follow a descriptive quantitative analysis and narrative synthesis, with outcomes categorized using the Standardised Outcomes in Nephrology-Peritoneal Dialysis framework. The analysis will combine outcome mapping, predictor database development, model validation assessment, clinical accessibility evaluation, and population gap identification. REVIEW REGISTRATION: OSF https://osf.io/7dmaq/.

Indexed as

Peritoneal DialysisRenal Insufficiency, ChronicHumansPatient Reported Outcome MeasuresPrediction AlgorithmsPrognosisResearch DesignScoping Reviews as Topicperitoneal dialysispredictive learning modelsprognosisrenal insufficiency

Identifiers

PMID42100845
PMCPMC13460330

What Socratic holds

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LicenceCC BY-NC-ND
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Registered trials

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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.