Effect of Protein Supplementation on Health-Related Quality of Life in Individuals With Advanced Chronic Kidney Disease: A Systematic Review and Meta-Analysis of Randomized Controlled Trials
Bibliographic record
Abstract
OBJECTIVE: We performed a systematic review and meta-analysis to evaluate the effect of protein/amino acid supplementation on health-related quality of life (HRQOL) in advanced chronic kidney disease (CKD) including individuals on dialysis. METHODS: Medline, Cochrane Central, Embase, and Cumulative Index to Nursing and Allied Health Literature were searched (establishment until August 2022) for randomized controlled trials evaluating the effect of protein or amino acid supplementation (>5 g/day) on individuals with advanced chronic kidney disease (estimated glomerular filtration rate <30 mL/min and/or on dialysis). Primary outcome was change in HRQOL. Secondary outcomes included biochemical, anthropometric measures, and physical function. Two reviewers independently screened articles for inclusion based on the prespecified criteria, extracted data, and assessed risk of bias. Meta-analysis was performed by pooling mean difference or standardized mean difference using a random effects model if at least three included studies reported our prespecified outcomes. RESULTS: = 0%), as compared with controls. CONCLUSIONS: A small number of studies prevented meta-analysis for HRQOL. Statistically significant improvements in serum albumin and body mass index were observed with protein supplementation compared to controls. Small number of studies, high risk of bias, and heterogeneity of included studies support the need for rigorous clinical trials, investigating the effect of protein supplementation on patient-relevant outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.024 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".