Evidence-based consensus guidelines for the management of catatonia: Recommendations from the British Association for Psychopharmacology
Bibliographic record
Abstract
The British Association for Psychopharmacology developed an evidence-based consensus guideline on the management of catatonia. A group of international experts from a wide range of disciplines was assembled. Evidence was gathered from existing systematic reviews and the primary literature. Recommendations were made on the basis of this evidence and were graded in terms of their strength. The guideline initially covers the diagnosis, aetiology, clinical features and descriptive epidemiology of catatonia. Clinical assessments, including history, physical examination and investigations are then considered. Treatment with benzodiazepines, electroconvulsive therapy and other pharmacological and neuromodulatory therapies is covered. Special regard is given to periodic catatonia, malignant catatonia, neuroleptic malignant syndrome and antipsychotic-induced catatonia. There is attention to the needs of particular groups, namely children and adolescents, older adults, women in the perinatal period, people with autism spectrum disorder and those with certain medical conditions. Clinical trials were uncommon, and the recommendations in this guideline are mainly informed by small observational studies, case series and case reports, which highlights the need for randomised controlled trials and prospective cohort studies in this area.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.040 | 0.076 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.011 |
| Bibliometrics | 0.015 | 0.010 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.012 | 0.005 |
| Research integrity | 0.012 | 0.011 |
| Insufficient payload (model declined to judge) | 0.007 | 0.006 |
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".