Muscle Torque Relative to Cross-Sectional Area and the Functional Muscle-Bone Unit in Children and Adolescents With Chronic Disease
Bibliographic record
Abstract
Measures of muscle mass or size are often used as surrogates of forces acting on bone. However, chronic diseases may be associated with abnormal muscle force relative to muscle size. The muscle-bone unit was examined in 64 children and adolescents with new-onset Crohn's disease (CD), 54 with chronic kidney disease (CKD), 51 treated with glucocorticoids for nephrotic syndrome (NS), and 264 healthy controls. Muscle torque was assessed by isometric ankle dynamometry. Calf muscle cross-sectional area (CSA) and tibia cortical section modulus (Zp) were assessed by quantitative CT. Log-linear regression was used to determine the relations among muscle CSA, muscle torque, and Zp, adjusted for tibia length, age, Tanner stage, sex, and race. Muscle CSA and muscle torque-relative-to-muscle CSA were significantly lower than controls in advanced CKD (CSA -8.7%, p = 0.01; torque -22.9%, p < 0.001) and moderate-to-severe CD (CSA -14.1%, p < 0.001; torque -7.6%, p = 0.05), but not in NS. Zp was 11.5% lower in advanced CKD (p = 0.005) compared to controls, and this deficit was attenuated to 6.7% (p = 0.05) with adjustment for muscle CSA. With additional adjustment for muscle torque and body weight, Zp was 5.9% lower and the difference with controls was no longer significant (p = 0.09). In participants with moderate-to-severe CD, Zp was 6.8% greater than predicted (p = 0.01) given muscle CSA and torque deficits (R(2) = 0.92), likely due to acute muscle loss in newly-diagnosed patients. Zp did not differ in NS, compared with controls. In conclusion, muscle torque relative to muscle CSA was significantly lower in CKD and CD, compared with controls, and was independently associated with Zp. Future studies are needed to determine if abnormal muscle strength contributes to progressive bone deficits in chronic disease, independent of muscle area. © 2014 American Society for Bone and Mineral Research.
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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 | 0.001 | 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".