SynthesisBMC nephrology2025
Risk prediction models for sarcopenia in maintenance hemodialysis patients: a systematic review and meta-analysis.
Synthesis in BMC nephrology, 2025. 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
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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
1 citing paper in PubMed.
- Association between remnant cholesterol inflammation index and handgrip strength in maintenance hemodialysis patients.Frontiers in endocrinology · 2026Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSarcopenia can severely affect patients undergoing maintenance hemodialysis. A high-quality prediction model could facilitate early identification and prevention. Despite the growing number of risk prediction models for sarcopenia in these patients, their quality and clinical utility remain uncertain.
objectiveThis study aims to systematically review existing studies on risk prediction models for sarcopenia in maintenance hemodialysis patients.
methodsA comprehensive literature search was conducted across PubMed, Web of Science, Embase, The Cochrane Library, CINAHL, CNKI, VIP, CBM, Wanfang databases, and Clinical Trials.gov from their inception until May 12, 2024. Studies on sarcopenia risk prediction models for maintenance hemodialysis patients were included. Two independent reviewers screened studies using the Prediction Model Risk of Bias Assessment Tool (PROBAST) and the CHARMS checklist, applying predefined inclusion and exclusion criteria. Relevant data were extracted, and the risk of bias in the included studies was assessed.
resultsEighteen studies, encompassing 21 prediction models, were included. Sample sizes ranged from 60 to 805 participants, with outcome event incidence rates varying between 6.6% and 70.0%. The reported risk factors were age, gender, body mass index, grip strength and so on. The area under the receiver operating characteristic curve (AUC) for the models ranged from 0.73 to 0.955. Most studies had a high risk of bias, primarily due to issues related to study population selection and data analysis, including inappropriate data sources, insufficient outcome events, and poor management of missing data. Only two studies raised concerns regarding applicability.
conclusionCurrent models for predicting sarcopenia in maintenance hemodialysis patients exhibit a high risk of bias, as determined by PROBAST criteria. Future research should focus on improving existing models or developing new ones using rigorous methodologies. REGISTRATION: This study is registered with PROSPERO (registration number: CRD42024544944). CLINICAL TRIAL NUMBER: Not applicable.
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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 OpenQuestion graph.