Prevalence of fracture and low bone mineral density in competitive road cyclists
Bibliographic record
Abstract
Low bone density is considered a risk factor for fracture. Recent studies have shown that competitive road cyclists have significantly lower bone mineral density (BMD) than matched controls. Objective The aim of this study was to evaluate the possible association between BMD and fracture in competitive cyclists. Method This was a case‐control study design including 101 professional road cyclists as cases and 30 healthy males as controls. Results The age‐adjusted relative risk of fracture in cyclists was 4.24 (P = 0.002). Cyclists had lower BMD Z‐scores at the femur (−0.8 SD 0.95, P < 0.001), lumbar (−0.9 SD 0.75, P < 0.001), and radius UD (−0.5 SD 1.1, P = 0.063) compared to controls. Amongst professional cyclists, 53% had a low lumbar BMD (−1.54 SD 0.35) while the proportion was 32% in elite (−1.49 SD 0.49) and 13% in controls. The number of fracture in cyclists was significantly though weakly correlated with Femoral neck BMD (r = −0.28, P = 0.02). Conclusion While a high prevalence of fracture could be observed in competitive road cyclists as well as a widespread low BMD especially among professional cyclists, no clear relationship could be detected between fracture and low BMD in these well trained endurance 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 | 0.001 | 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 | 0.001 | 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".