Fracture risk and areal bone mineral density in adolescent females with anorexia nervosa
Bibliographic record
Abstract
OBJECTIVE: To (i) compare fracture prevalence in adolescent females with anorexia nervosa (AN) versus normal-weight controls and (ii) examine whether reductions in areal bone mineral density (aBMD) predict fracture risk in females with AN. METHOD: Four-hundred eighteen females (310 with active AN and 108 normal-weight controls) 12- to 22-years-old were studied cross-sectionally. Lifetime fracture history was recorded by a physician during participant interviews. Body composition and aBMD measurements of the whole body, whole body less head, lumbar spine, and hip were assessed by dual-energy X-ray absorptiometry, and bone mineral apparent density (BMAD) was calculated for the lumbar spine. RESULTS: Participants with AN and normal-weight controls did not differ for chronological age, sexual maturity, or height. The lifetime prevalence of prior fracture was 59.8% higher in those with AN as compared to controls (31.0% vs. 19.4%, p = 0.02), and the fracture incidence rate peaked in our cohort after the diagnosis of AN. Lower aBMD and lumbar BMAD were not associated with a higher prevalence of fracture in the AN or control group on univariate or multivariate analyses. Compared to controls, fracture prevalence was significantly higher in the subgroup of girls with AN who had normal aBMD or only modest reductions of aBMD (Z-scores > -1 or -1.5). DISCUSSION: This is the first study to show that the risk of fracture during childhood and adolescence is significantly higher in patients with AN than in normal-weight controls. Fracture prevalence is increased in this cohort of participants with AN even without significant reductions in aBMD.
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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) | 0.001 | 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".