ArticleHealth science reports2026
Bayesian Analysis of Frailty Risk Factors in Chronic Kidney Disease: A Nationwide Cross-Sectional Survey.
Article in Health science reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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
1 citing paper in PubMed.
- Bayesian Analysis of Frailty Risk Factors in Chronic Kidney Disease: A Nationwide Cross-Sectional Survey.Health science reports · 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
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Frailty in chronic kidney disease (CKD) patients is associated with increased risk of adverse health outcomes. Understanding the contributing factors to frailty in this population is crucial for developing targeted interventions and improving patient care. The objective of this study is to identify and quantify potential risk factors associated with frailty in chronic kidney disease patients. Methods: We conducted a cross-sectional study using data from the China Health and Retirement Longitudinal Study (CHARLS) cohorts of 2011 and 2015. A Bayesian mixed-effects logistic regression model was utilized to analyze the relationship between selected features and frailty in chronic kidney disease. Results: Of 1,924 participants, about one-third ( Conclusion: This study identified several potential contributing factors to frailty in CKD patients, with depression emerging as the strongest predictor. The counterintuitive relationship between creatinine levels and frailty underscores the complex interplay between muscle mass/quality and kidney function in frailty development, warranting further investigation.
Indexed as
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.