Methotrimeprazine in the treatment of agitation in acquired brain injury patients
Bibliographic record
Abstract
Medical management of the agitation associated with acquired brain injury (ABI) has been proble matic. At least 12 distinct drugs are currently recommended in the medical literature. In recent years, on the ABI in-patient rehabilitation unit, methotrimeprazine (MTZ) has come to be the preferred drug and is used routinely for effective treatment of agitation. The objective of this paper is to describe the use and safety of MTZ in the rehabilitation of ABI patients. A retrospective chart review of all patients discharged from the ABI unit over a course of 2 years was conducted. In addition to demographics such a aetiology of ABI, sex, age, length of stay, Glasgow Coma Scale, length of posttraumatic amnesia and others, a detailed analysis was made of the multidisciplinary progress notes to determine the daily agitation status and the daily use of psychotropic medication. All notes on side effects and adverse reactions were carefully documeneted. 120 first admission recent ABI patients were discharged in the 2 year study period. Of these, 69 (57%) had some level of agitation and 56 (48%) were treated with MTZ, in doses of 2-50 mg up to four times daily. Agitation was controlled in most cases. In only two cases were significant side effects noted. While MTZ has been used as a safe and effective neuroleptic in psychiatry for over 40 years, this is the first report of its use in treating agitation in ABI.
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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) | 0.000 | 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) | 0.000 | 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".