World Federation of Societies of Biological Psychiatry (WFSBP) guidelines update 2023 on the pharmacological treatment of eating disorders
Bibliographic record
Abstract
OBJECTIVES: This 2023 update of the WFSBP guidelines for the pharmacological treatment of eating disorders (EDs) reflects the latest diagnostic and psychopharmacological progress and the improved WFSBP recommendations for the assessment of the level of evidence (LoE) and the grade of recommendation (GoR). METHODS: The WFSBP Task Force EDs reviewed the relevant literature and provided a timely grading of the LoE and the GoR. RESULTS: In anorexia nervosa (AN), only a limited recommendation (LoE: A; GoR: 2) for olanzapine can be given, because the available evidence is restricted to weight gain, and its effect on psychopathology is less clear. In bulimia nervosa (BN), the current literature prompts a recommendation for fluoxetine (LoE: A; GoR: 1) or topiramate (LoE: A; GoR: 1). In binge-eating disorder (BED), lisdexamfetamine (LDX; LoE: A; GoR: 1) or topiramate (LoE: A; GoR: 1) can be recommended. There is only sparse evidence for the drug treatment of avoidant restrictive food intake disorder (ARFID), pica, and rumination disorder (RD). CONCLUSION: In BN, fluoxetine, and topiramate, and in BED, LDX and topiramate can be recommended. Despite the published evidence, olanzapine and topiramate have not received marketing authorisation for use in EDs from any medicine regulatory agency.
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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 | 0.031 | 0.077 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.008 |
| Bibliometrics | 0.010 | 0.007 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.010 | 0.011 |
| Insufficient payload (model declined to judge) | 0.011 | 0.009 |
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".