Bone Quality and Muscle Strength in Female Athletes with Lower Limb Stress Fractures
Bibliographic record
Abstract
PURPOSE: Lower limb stress fractures (SF) have a high prevalence in female athletes of running-related sports. The purpose of this study was to investigate bone quality, including bone microarchitecture and strength, and muscle strength in athletes diagnosed with SF. METHODS: Female athletes with lower limb SF (SF subjects, n = 19, 18-45 yr, premenopausal) and healthy female athletes (NSF subjects, n = 19) matched according to age, sport, and weekly training volume were recruited. Bone microarchitecture of all participants was assessed using high-resolution peripheral quantitative computed tomography at two skeletal sites along the distal tibia of the dominant leg. Bone strength and load distribution between cortical and trabecular bone was estimated by finite element analysis. Using dual-energy x-ray absorptiometry, areal bone mineral density (aBMD) at the hip, femoral neck, and spine was measured. Muscle torque (knee extension, plantarflexion, eversion/inversion) was assessed (Biodex dynamometer) as a measure of lower leg muscle strength. RESULTS: SF subjects, after adjusting for body weight, had thinner tibia compared with NSF subjects as indicated by a lower tibial cross-sectional area (-7.8%, P = 0.02) and higher load carried by the cortex as indicated by finite element analysis (4.1%, P = 0.02). Further site-specific regional analysis revealed that, in the posterior region of the tibia, SF subjects had lower trabecular BMD (-19.8%, P = 0.02) and less cortical area (-5.2%, P = 0.02). The SF group exhibited reduced knee extension strength (-18.3%, P = 0.03) compared with NSF subjects. CONCLUSIONS: These data suggest an association of impaired bone quality, particularly in the posterior region of the distal tibia, and decreased muscle strength with lower limb SF in female athletes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".