Lower-extremity muscle atrophy and fat infiltration after chronic spinal cord injury.
Bibliographic record
Abstract
BACKGROUND: Atrophy and fatty-infiltration of lower-extremity muscle after spinal cord injury (SCI) predisposes individuals to metabolic disease and related mortality. OBJECTIVES: To determine the magnitude of atrophy and fatty-infiltration of lower-extremity muscles and related factors in a group of individuals with chronic SCI and diverse impairment. METHODS: Muscle cross-sectional area and density were calculated from peripheral quantitative computed tomography scans of the 66% site of the calf of 70 participants with chronic SCI [50 male, mean age 49 (standard deviation 12) years, C2-T12, AIS A-D] and matched controls. Regression models for muscle area and density were formed using 16 potential correlates selected a priori. RESULTS: Participants with motor-complete SCI had ≈ 32% lower muscle area, and ≈ 43% lower muscle density values relative to controls. Participants with motor-incomplete SCI had muscle area and density values that were both ≈ 14% lower than controls. Body mass (+), tetraplegia (+), motor function (+), spasticity (+), vigorous physical activity (+), wheelchair use (-), age (-), and waist circumference (-) were associated with muscle size and/or density in best-fit regression models. CONCLUSIONS: There are modifiable factors related to muscle size, body composition, and activity level that may offer therapeutic targets for preserving metabolic health after chronic SCI.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".