Ketamine for mental health - A naturalistic inventory of prescribing practices, safety, and adverse effects
Bibliographic record
Abstract
Ketamine is an NMDA receptor antagonist, long used for its anesthetic and pain reducing properties, but has more recently demonstrated efficacy for treating depression. Evidence is also emerging for other psychiatric indications including posttraumatic stress disorder, anxiety disorders, obsessive compulsive disorder, and to support psychotherapy. In this context, there is greater demand for its use in various forms including intravenous, intramuscular, subcutaneous, intranasal, oral, and sublingual administration. While intravenous administration typically requires administration and monitoring in a healthcare setting, the safety precautions for other forms of ketamine are unclear. Limited data in this regard may elicit controversy among prescribers, who wish to improve patient access, and among regulatory bodies, who may impose limitations based on IV ketamine data. This project aims to bridge the gap between current literature and the clinical experience and opinions of ketamine prescribers. This information was obtained in the form of a survey and answered: "How do prescribers of ketamine, with emphasis on psychiatric care providers, find its safety profile and in what ways have they prescribed ketamine?" Information was gathered on prescriber profiles, indications for ketamine use, doses and routes of ketamine prescribed, side effects and adverse events, and prescribers' opinions regarding monitoring requirements. Results were obtained from 45 providers with more than 1000 patient encounters over two countries. Non-IV forms of ketamine were commonly used, and the survey reported a favorable safety profile for ketamine. Non-IV Ketamine was reported to be safely utilized in a clinic setting with minimal monitoring and safety equipment, or at times, for home use. While survey results carry limitations, it appears that safety is dependent on dose and route, and strict universal regulations for all formulations may unnecessarily limit patient access.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 teacher head, 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".