Body Composition According to Spinal Cord Injury Level: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
The level of injury is linked with biochemical alterations and limitations in physical activity among individuals with spinal cord injury (SCI), which are crucial determinants of body composition. We searched five electronic databases from inception until 22 July 2021. The pooled effect estimates were computed using random-effects models, and heterogeneity was calculated using I2 statistics and the chi-squared test. Study quality was assessed using the Newcastle–Ottawa Scale. We pooled 40 studies comprising 4872 individuals with SCI (3991 males, 825 females, and 56 sex-unknown) in addition to chronic SCI (median injury duration 12.3 y, IQR 8.03–14.8). Individuals with tetraplegia had a higher fat percentage (weighted mean difference (WMD) 1.9%, 95% CI 0.6, 3.1) and lower lean mass (WMD −3.0 kg, 95% CI −5.9, −0.2) compared to those with paraplegia. Those with tetraplegia also had higher indicators of central adiposity (WMD, visceral adipose tissue area 0.24 dm2 95% CI 0.05, 0.43 and volume 1.05 L 95% CI 0.14, 1.95), whereas body mass index was lower in individuals with tetraplegia than paraplegia (WMD −0.9 kg/mg2, 95% CI −1.4, −0.5). Sex, age, and injury characteristics were observed to be sources of heterogeneity. Thus, individuals with tetraplegia have higher fat composition compared to paraplegia. Anthropometric measures, such as body mass index, may be inaccurate in describing adiposity in SCI individuals.
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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 | 0.017 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.039 | 0.008 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".