Physiologic estrogen replacement increases bone density in adolescent girls with anorexia nervosa
Bibliographic record
Abstract
Anorexia nervosa (AN) is prevalent in adolescents and is associated with decreased bone mineral accrual at a time critical for optimizing bone mass. Low BMD in AN is a consequence of nutritional and hormonal alterations, including hypogonadism and low estradiol levels. Effective therapeutic strategies to improve BMD in adolescents with AN have not been identified. Specifically, high estrogen doses given as an oral contraceptive do not improve BMD. The impact of physiologic estrogen doses that mimic puberty on BMD has not been examined. We enrolled 110 girls with AN and 40 normal-weight controls 12 to 18 years of age of similar maturity. Subjects were studied for 18 months. Mature girls with AN (bone age [BA] ≥15 years, n = 96) were randomized to 100 µg of 17β-estradiol (with cyclic progesterone) or placebo transdermally for 18 months. Immature girls with AN (BA < 15 years, n = 14) were randomized to incremental low-dose oral ethinyl-estradiol (3.75 µg daily from 0 to 6 months, 7.5 µg from 6 to 12 months, 11.25 µg from 12 to 18 months) to mimic pubertal estrogen increases or placebo for 18 months. All BMD measures assessed by dual-energy X-ray absorptiometry (DXA) were lower in girls with AN than in control girls. At baseline, girls with AN randomized to estrogen (AN E + ) did not differ from those randomized to placebo (AN E-) for age, maturity, height, BMI, amenorrhea duration, and BMD parameters. Spine and hip BMD Z-scores increased over time in the AN E+ compared with the AN E- group, even after controlling for baseline age and weight. It is concluded that physiologic estradiol replacement increases spine and hip BMD in girls with AN.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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".