Association of muscularity status with clinical and physical function outcomes in critically ill patients with COVID‐19: A systematic review and meta‐analysis
Bibliographic record
Abstract
Pre-coronavirus disease 2019 (COVID-19) critical care research underscored the importance of muscularity on patient outcomes. This study investigates the association between skeletal muscle mass and quality with clinical and physical function outcomes in critically ill patients with COVID-19. We systematically searched MEDLINE, EMBASE, and CINAHL from database inception to April 24, 2024, for studies using objective methods to evaluate muscularity in critically ill adults with COVID-19, without language restrictions. Co-primary outcomes were overall mortality and muscle strength. Random-effect meta-analyses were performed in RevMan 5.4.1. We included 20 studies (N = 1818), assessing muscularity via computed tomography (twelve studies), ultrasound (seven studies), and bioelectrical impedance analysis (one study); none had low risk of bias. In analyses of high vs low muscularity, high muscle mass was significantly associated with lower overall mortality (nine studies; risk ratio = 0.74; 95% CI, 0.57-0.98; P = 0.03). When muscularity was analyzed as a continuous variable, COVID-19 survivors had higher skeletal muscle area (SMA) (13 studies; mean difference [MD] = 1.18; 95% CI, 0.03-2.33; P = 0.05) confirmed by sensitivity analysis using standardized MD (0.23, 95% CI 0.05-0.42, P = 0.01) and significantly higher muscle quality (five studies; standardized MD = 0.45; 95% CI, 0.20-0.70; P = 0.0004). Muscle strength findings were inconsistent: one study showed significant correlations between muscle strength with muscle mass parameters (r = 0.365-0.375, P < 0.001) whereas another found no association. In critically ill adults with COVID-19, high muscle mass was associated with lower mortality risk. Survivors had significantly higher SMA and muscle quality. Findings on physical function outcomes remain inconclusive (PROSPERO ID: CRD42022384155).
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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 | 0.010 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.032 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".