Olanzapine <i>versus</i> placebo for out-patients with anorexia nervosa
Bibliographic record
Abstract
BACKGROUND: Anorexia nervosa (AN) is a serious psychiatric illness associated with significant morbidity and mortality. There is little empirical support for specific treatments and new approaches are sorely needed. This two-site study aimed to determine whether olanzapine is superior to placebo in increasing body mass index (BMI) and improving psychological symptoms in out-patients with AN. METHOD: A total of 23 individuals with AN were randomly assigned in double-blind fashion to receive olanzapine or placebo for 8 weeks together with medication management sessions that emphasized compliance. Weight, other physical assessments and measures of psychopathology were collected. RESULTS: End-of-treatment BMI, with initial BMI as a covariate, was significantly greater in the group receiving olanzapine [F(1, 20)=6.64, p=0.018]. Psychological symptoms improved in both groups, but there were no statistically significant group differences. Of the 23 participants, 17 (74%) completed the 8-week trial. Participants tolerated the medication well with sedation being the only frequent side effect and no adverse metabolic effects were noted. CONCLUSIONS: This small study suggests that olanzapine is generally well tolerated by, and may provide more benefit than placebo for out-patients with AN. Further study is indicated to determine whether olanzapine may affect psychological symptoms in addition to BMI.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".