Muscle Density and Bone Quality of the Distal Lower Extremity Among Individuals with Chronic Spinal Cord Injury
Bibliographic record
Abstract
BACKGROUND: Understanding the related fates of muscle density and bone quality after chronic spinal cord injury (SCI) is an important initial step in determining endocrine-metabolic risk. OBJECTIVE: To examine the associations between muscle density and indices of bone quality at the distal lower extremity of adults with chronic SCI. METHODS: A secondary data analysis was conducted in 70 adults with chronic SCI (C2-T12; American Spinal Injury Association Impairment Scale [AIS] A-D; ≥2 years post injury). Muscle density and cross-sectional area (CSA) and bone quality indices (trabecular bone mineral density [TbBMD] at the distal tibia [4% site] and cortical thickness [CtTh], cortical area [CtAr], cortical BMD [CtBMD], and polar moment of inertia [PMI] at the tibial shaft [66% site]) were measured using peripheral quantitative computed tomography. Calf lower extremity motor score (cLEMS) was used as a clinical measure of muscle function. Multivariable linear regression analyses were performed to determine the strength of the muscle-bone associations after adjusting for confounding variables (sex, impairment severity [AIS A/B vs AIS C/D], duration of injury, and wheelchair use). RESULTS: Muscle density was positively associated with TbBMD (b = 0.85 [0.04, 1.66]), CtTh (b = 0.02 [0.001, 0.034]), and CtBMD (b = 1.70 [0.71, 2.69]) (P < .05). Muscle CSA was most strongly associated with CtAr (b = 2.50 [0.12, 4.88]) and PMI (b = 731.8 [161.7, 1301.9]) (P < .05), whereas cLEMS was most strongly associated with TbBMD (b = 7.69 [4.63, 10.76]) (P < .001). CONCLUSIONS: Muscle density and function were most strongly associated with TbBMD at the distal tibia in adults with chronic SCI, whereas muscle size was most strongly associated with bone size and geometry at the tibial shaft.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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 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".