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Record W4391324489 · doi:10.1089/psymed.2023.0021

Ketamine-Assisted Psychotherapy Provides Lasting and Effective Results in the Treatment of Depression, Anxiety, and Post-Traumatic Stress Disorder at 3 and 6 Months: Findings from a Large Retrospective Effectiveness Study

2024· article· en· W4391324489 on OpenAlexafffund
Ryan Yermus, John Bottos, Nathan Bryson, Joseph A. De Leo, Mitch Earleywine, Emily Hackenburg, Sidney H. Kennedy, Martha Kezemidis, Sarah Kratina, Robert McMaster, Ben Medrano, Monica Mina, Dominique Morisano, Michael V. Muench, Sabina Pillai, Randall Scharlach, Varun Setlur, Michael Verbora, Elizabeth Wolfson, Nabid Zaer, Christopher Lo

Bibliographic record

VenuePsychedelic Medicine · 2024
Typearticle
Languageen
FieldMedicine
TopicTreatment of Major Depression
Canadian institutionsMcMaster UniversityBrampton Civic HospitalUniversity of OttawaCentre for Addiction and Mental HealthUniversity of CalgaryUniversity of TorontoCentre for Global Health ResearchSeneca PolytechnicPublic Health OntarioFields Institute for Research in Mathematical Sciences
FundersCanadian Institutes of Health ResearchH. Lundbeck A/SPfizerFondation Brain CanadaServierSunovion
KeywordsAnxietyKetamineTraumatic stressDepression (economics)PsychotherapistPsychologyClinical psychologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

Importance: Ketamine-assisted psychotherapy (KAP) is an emerging treatment option to alleviate treatment-resistant affective disorders, but its long-term effectiveness remains unclear. Objective: To examine the treatment effects of KAP on anxiety, depression, and post-traumatic stress disorder (PTSD) at 1, 3, and 6 months post-treatment. Design Setting and Participants: This retrospective effectiveness study included self-reported outcomes from adults with a history of major depressive disorder, generalized anxiety disorder (GAD), or PTSD who had not responded to prior treatment interventions and received KAP administered across 11 Field Trip Health clinics in North America between March 13, 2020, and June 16, 2022. The evaluable sample sizes were 346 and 94 participants at 3 and 6 months, respectively, representing loss to follow-up rates of 82% and 95%. Intervention: KAP consists of 4-6 guided ketamine sessions (administered through intramuscular injection or sublingual lozenge) with psychotherapy-only integration visits after doses 1 and 2 and then after every 2 subsequent doses. Mean number of doses administered was 4, standard deviation (SD) = 3, and mean number of integration sessions was 3, SD = 2. Main Outcomes and Measures: Primary outcomes were changes in symptoms of depression, anxiety, and PTSD at 3 months relative to baseline, assessed, respectively, using the 9-item Patient Health Questionnaire, the 7-item GAD measure, and the 6-item PTSD checklist. Secondary outcomes were changes at 1 and 6 months relative to baseline. Results: s = 0.61-0.73). Case reductions (identified based on cutoff values) ranged from 39% to 41% at 3 months and 29% to 37% at 6 months. In total, 50-75% reported a minimal clinically important difference at 3 months and 48-70% at 6 months. Conclusions and Relevance: KAP produced sustained reductions in anxiety, depression, and PTSD, with symptom improvement lasting well beyond the duration of dosing and integration sessions. These effects extended to as much as 5 months after the last KAP session. However, the high rates of attrition may limit validity of the results. Given the growing mental health care crises and the need for effective therapies and models of care, especially for intractable psychiatric mood-related disorders, these data support the use of KAP as a viable alternative. Further prospective clinical research should be undertaken to provide evidence on the safety and effectiveness of ketamine within a psychotherapeutic context.

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 imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.326
Teacher spread0.309 · 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 source (direct Gemma or distilled Codex), 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".

Quick stats

Citations12
Published2024
Admission routes2
Has abstractyes

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