Repurposing General Anesthetic Drugs to Treat Depression: A New Frontier for Anesthesiologists in Neuropsychiatric Care
Bibliographic record
Abstract
During the last 100 years, the role of anesthesiologists in psychiatry has focused primarily on facilitating electroconvulsive therapy and mitigating postoperative delirium and other perioperative neurocognitive disorders. The discovery of the rapid and sustained antidepressant properties of ketamine, and early results suggesting that other general anesthetic drugs (including nitrous oxide, propofol, and isoflurane) have antidepressant properties, has positioned anesthesiologists at a new frontier in the treatment of neuropsychiatric disorders. Moreover, shared interest in understanding the biologic underpinnings of anesthetic drugs as psychotropic agents is eroding traditional academic boundaries between anesthesiology and psychiatry. This article presents a brief overview of anesthetic drugs as novel antidepressants and identifies promising future candidates for the treatment of depression. The authors issue a call to action and outline strategies to foster collaborations between anesthesiologists and psychiatrists as they work toward the common goals of repurposing anesthetic drugs as antidepressants and addressing mood disorders in surgical patients.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.011 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".