ArticlePloS one2022
Prediction models used in the progression of chronic kidney disease: A scoping review.
Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.
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
9 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Systematic review of the application of the Kidney Failure Risk Equation and Oxford classification in estimating prognosis in IgA Nephropathy.Systematic reviews · 2025Pooled it
- Mathematical expansion and clinical application of chronic kidney disease stage as vector field.PloS one · 2024Pooled it
- Risk prediction of the progression of chronic kidney disease stage 1 based on peripheral blood samples: construction and internal validation of a nomogram.Renal failure · 2023Trial
- The Chronic Kidney Disease Care Model: Quantifying Management Strategies for Improving Patient Outcomes in the USA.PharmacoEconomics - open · 2026Article
- Gavage versus dietary adenine administration is more effective for the female mouse model of chronic kidney disease.Scientific reports · 2025Article
- A Novel Kidney Failure Prediction Model in Individuals With CKD: Impact of Serum Bilirubin Levels.The Journal of clinical endocrinology and metabolism · 2025Article
- In silico medicine and -omics strategies in nephrology: contributions and relevance to the diagnosis and prevention of chronic kidney disease.Kidney research and clinical practice · 2025Article
- Prediction of chronic kidney disease progression using recurrent neural network and electronic health records.Scientific reports · 2023Article
- Chronic kidney disease prediction using boosting techniques based on clinical parameters.PloS one · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo provide a review of prediction models that have been used to measure clinical or pathological progression of chronic kidney disease (CKD).
designScoping review. DATA SOURCES: Medline, EMBASE, CINAHL and Scopus from the year 2011 to 17th February 2022. STUDY SELECTION: All English written studies that are published in peer-reviewed journals in any country, that developed at least a statistical or computational model that predicted the risk of CKD progression. DATA EXTRACTION: Eligible studies for full text review were assessed on the methods that were used to predict the progression of CKD. The type of information extracted included: the author(s), title of article, year of publication, study dates, study location, number of participants, study design, predicted outcomes, type of prediction model, prediction variables used, validation assessment, limitations and implications.
resultsFrom 516 studies, 33 were included for full-text review. A qualitative analysis of the articles was compared following the extracted information. The study populations across the studies were heterogenous and data acquired by the studies were sourced from different levels and locations of healthcare systems. 31 studies implemented supervised models, and 2 studies included unsupervised models. Regardless of the model used, the predicted outcome included measurement of risk of progression towards end-stage kidney disease (ESKD) of related definitions, over given time intervals. However, there is a lack of reporting consistency on details of the development of their prediction models.
conclusionsResearchers are working towards producing an effective model to provide key insights into the progression of CKD. This review found that cox regression modelling was predominantly used among the small number of studies in the review. This made it difficult to perform a comparison between ML algorithms, more so when different validation methods were used in different cohort types. There needs to be increased investment in a more consistent and reproducible approach for future studies looking to develop risk prediction models for CKD progression.
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Identifiers
What 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.