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Record W4407369015 · doi:10.1097/aln.0000000000005311

Intersections of Anesthesiology and Psychiatry: Reply

2025· article· en· W4407369015 on OpenAlexaffabout
Connor T. A. Brenna, Benjamin I. Goldstein, Carlos A. Zarate, Beverley A. Orser

Bibliographic record

VenueAnesthesiology · 2025
Typearticle
Languageen
FieldMedicine
TopicTreatment of Major Depression
Canadian institutionsSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineAnesthesiologyPain medicinePsychiatryMedical education

Abstract

fetched live from OpenAlex

In Reply: We thank Espinoza et al.,1 and also Sartorius et al.,2 for their interest in our recent article on the repurposing of anesthetic drugs to treat depression.3 Further dialogue in academic forums shared by psychiatrists and anesthesiologists is essential to move this work forward, and we are grateful for the opportunity to respond to these letters to the editor. As Espinoza et al. point out,1 depression is an important perioperative variable, and we share their optimism that the ongoing collaborations of psychiatrists and anesthesiologists will result in meaningful strategies for both screening and tailored care of patients in the perioperative period. The authors criticize our interpretation of the ELEctroconvulsive therapy versus Ketamine in patients with Treatment-resistant Depression (ELEKT-D) trial,4 and we appreciate their commitment to precision in language. To clarify, our article does highlight that the main finding of ELEKT-D’s investigators was that ketamine is a noninferior treatment to electroconvulsive therapy for treatment-resistant depression. It is true that noninferiority trials such as ELEKT-D utilize one-sided inferential statistics that cannot evaluate hypotheses of superiority. As Espinoza et al. note, some other studies have reported higher rates of remission in response to electroconvulsive therapy.5 There are many potential explanations for this discrepancy—several of which are detailed by Espinoza et al.—but, ultimately, it is not our goal to review the ELEKT-D study or suggest that it was without limitations. Nonetheless, it does not necessarily follow from the trial’s low overall remission rate that recruitment was biased to favor ketamine. Rather, the ELEKT-D results detail a low rate of remission in a particular patient population and under specific experimental conditions; and illustrate that, in this setting, ketamine was a noninferior treatment. Finally, we wish to respond to the comment by Espinoza et al. that “recent high-profile adverse outcomes” should prompt the recognition of unregulated ketamine administration.1 Certainly, the administration of any general anesthetic drug requires careful consideration and substantial clinical expertise to ensure safety. If risks presented by unregulated use of a treatment were accepted as evidence that it should not be used in controlled settings, we expect that many treatments (perhaps even electroconvulsive therapy)6 would be forfeit. Rather, the potential adverse outcomes associated with the administration of anesthetic drugs must inspire conversations and collaborative studies about how, when, and for whom such drugs can be safely applied as therapeutic tools. We are pleased that Sartorius et al. agree with our proposal that there is great potential in collaborations between psychiatrists and anesthesiologists,2 and highlight that their letter is the product of such an interdepartmental collaboration. As the authors point out, several trials have compared electroconvulsive therapy with ketamine for the treatment of patients with depression.7 Indeed, we noted in our original publication that these trials have reported conflicting results, and have largely favored electroconvulsive therapy over ketamine in some patient populations.3,7 Also, we thank Sartorius et al. for expanding the list of the many contemporary mechanistic theories of depression beyond the canonical monoaminergic hypothesis.8 Finally, Sartorius et al. suggest that electroconvulsive therapy itself should be a joint research area where our specialties can work together2 as electroconvulsive therapy research has not traditionally been a shared venture. Notably, there is already a nascent body of work focused on whether the type of anesthetic used for electroconvulsive therapy is important to the mood-related outcomes of electroconvulsive therapy itself,9,10 which surely represents a starting point for further collaborations. Collectively, the two letters speak to an urgent need and enthusiasm for interdisciplinary collaboration between psychiatry and anesthesiology, and an exciting, shared future for our specialties. Research Support Dr. Brenna receives salary support from the Vanier Canada Graduate Scholarship as well as operating support from the Canadian Anesthesia Research Foundation (Toronto, Canada). Competing Interests Dr. Orser serves on the board of trustees of the International Anesthesia Research Society (San Francisco, California) and is codirector of the Perioperative Brain Health Centre (Toronto, Canada). She is a named inventor on a Canadian patent (No. 2,852,978) and two U.S. patents (Nos. 9,517,265 and 10,981,954). The patents, which are held by the University of Toronto (Toronto, Canada), are for new methods to prevent and treat delirium and persistent neurocognitive deficits after anesthesia and surgery, as well as to treat mood disorders. Dr. Orser collaborates on clinical studies that are supported by in-kind software donations from Cogstate Ltd. (New Haven, Connecticut). Dr. Zarate is listed as a coinventor on a patent for the use of ketamine in major depression and suicidal ideation; as a coinventor on a patent for the use of (2R,6R)-hydroxynorketamine, (S)-dehydronorketamine, and other stereoisomeric dehydroxylated and hydroxylated metabolites of (R,S)-ketamine metabolites in the treatment of depression and neuropathic pain; and as a coinventor on a patent application for the use of (2R,6R)-hydroxynorketamine and (2S,6S)-hydroxynorketamine in the treatment of depression, anxiety, anhedonia, suicidal ideation, and posttraumatic stress disorder. He has assigned his patent rights to the U.S. Government but will share a percentage of any royalties that may be received by the government. The other authors declare no competing interests.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.347

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.010
GPT teacher head0.281
Teacher spread0.271 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations1
Published2025
Admission routes2
Has abstractyes

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