Skeletal muscle atrophy in clinical and preclinical models of chronic kidney disease: A systematic review and meta‐analysis
Bibliographic record
Abstract
Abstract Patients with chronic kidney disease (CKD) are often regarded as experiencing wasting of muscle mass and declining muscle strength and function, collectively termed sarcopenia. The extent of skeletal muscle wasting in clinical and preclinical CKD populations is unclear. We evaluated skeletal muscle atrophy in preclinical and clinical models of CKD, with multiple sub‐analyses for muscle mass assessment methods, CKD severity, sex and across the different preclinical models of CKD. We performed a systematic literature review of clinical and preclinical studies that measured muscle mass/size using the following databases: Ovid Medline, Embase and Scopus. A random effects meta‐analysis was utilized to determine standard mean difference (SMD; Hedges' g) between healthy and CKD. Heterogeneity was evaluated using the I 2 statistic. Preclinical study quality was assessed via the Systematic Review Centre for Laboratory Animal Experimentation and clinical studies quality was assessed via the Newcastle‐Ottawa Scale. This study was registered in PROSPERO (CRD42020180737) prior to initiation of the search. A total of 111 studies were included in this analysis using the following subgroups: 106 studies in the primary CKD analysis, 18 studies that accounted for diabetes and 7 kidney transplant studies. Significant atrophy was demonstrated in 78% of the preclinical studies and 49% of the clinical studies. The random effects model demonstrated a medium overall SMD (SMD = 0.58, 95% CI = 0.52–0.64) when combining clinical and preclinical studies, a medium SMD for the clinical population (SMD = 0.48, 95% CI = 0.42–0.55; all stages) and a large SMD for preclinical CKD (SMD = 0.95, 95% CI = 0.76–1.14). Further sub‐analyses were performed based upon assessment methods, disease status and animal model. Muscle atrophy was reported in 49% of the clinical studies, paired with small mean differences. Preclinical studies reported significant atrophy in 78% of studies, with large mean differences. Across multiple clinical sub‐analyses such as severity of CKD, dialysis modality and diabetes, a medium mean difference was found. Sub‐analyses in both clinical and preclinical studies found a large mean difference for males and medium for females suggesting sex‐specific implications. Muscle atrophy differences varied based upon assessment method for clinical and preclinical studies. Limitations in study design prevented conclusions to be made about the extent of muscle loss with disease progression, or the impact of dialysis. Future work would benefit from the use of standardized measurement methods and consistent clinical staging to improve our understanding of atrophy changes in CKD progression, and analysis of biological sex differences.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".