Evidence-based pharmacotherapy of eating disorders
Bibliographic record
Abstract
The objective was to review scientific evidence for efficacy and safety of pharmacotherapy in adults or children with an eating disorder (ED). We conducted a computer search for all randomized controlled trials (RCTs) published between 1960 and May 2010 for treatment of anorexia nervosa (AN), bulimia nervosa (BN) or binge-eating disorder (BED). For drugs for which no RCT was found, open trials or case reports were retrieved. Clinically relevant RCTs in the treatment of AN have used atypical antipsychotics, selective serotonin reuptake inhibitors (SSRIs), and zinc supplementation. Olanzapine demonstrated an adjunctive effect for in-patient treatment of underweight AN patients, and fluoxetine helped prevent relapse in weight-restored AN patients in 1/2 studies. For treatment of BN, controlled studies have used SSRIs, other antidepressants, and mood stabilizers. In 9/11 studies, pharmacotherapy yielded a statistically significant although moderate reduction in binge/purge frequency, and some additional benefits. For BED, RCTs have been conducted using SSRIs and one serotonin norepinephrine reuptake inhibitor (SNRI), mood stabilizers, and anti-obesity medications. In 11/12 studies, there was a statistically significant albeit limited effect of medication. Meta-analyses on efficacy of pharmacotherapy for BN and BED support moderate effect sizes for medication, but generally low recovery rates. Treatment resistance is an inherent feature of AN, where treatment should focus on renourishment plus psychotherapy. For BN and BED, combined treatment with pharmacotherapy and cognitive behaviour therapy has been more effective than either alone. Data on the long-term efficacy of pharmacotherapy for EDs are scarce. Short- and long-term pharmacotherapy of EDs still remains a challenge for the clinician.
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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 | 0.009 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".