Intravenous ketamine for benzodiazepine deprescription and withdrawal management in treatment-resistant depression: a preliminary report
Bibliographic record
Abstract
We present the first evidence that sub-anesthetic ketamine infusions for treatment resistant depression (TRD) may facilitate deprescription of long-term benzodiazepine/z-drugs (BZDRs). Long-term BZDR prescriptions are potentially harmful yet common, partly because of challenging withdrawal symptoms. Few pharmacological interventions have evidence for facilitating BZDR discontinuation, and none in patients actively suffering from TRD. In this ambi-directional cohort study, discontinuation of long-term (>6 month) BZDRs was attempted in 22 patients with severe unipolar or bipolar TRD receiving a course of six subanesthetic ketamine infusions over four weeks. We investigated the rates of successful BZDRs deprescription, trajectories of acute psychological withdrawal symptoms, and subsequent BZDRs abstinence during a mean follow-up of 1 year (primary outcome). Clinically significant deteriorations in depression, anxiety, sleep, and/or suicidality during the acute BZDR discontinuation phase were measured by repeated standardized scales and analyzed by latent growth curve models and percent correct classification analysis. Of the 22 eligible patients, all enrolled in this study and 91% (20/22) successfully discontinued all BZDRs by the end of the 4-week intervention, confirmed by urinary analyses. Less than 25% of discontinuers experienced any significant worsening of anxiety, depression, sleep difficulties, or suicidality during treatment. During follow-up (mean [range] duration, 12 [3-24] months), 64% (14/22) of patients remained abstinent from any BZDRs. These preliminary results suggest that ketamine infusions for TRD may facilitate the deprescription of BZDRs, even in patients with active depressive symptoms and significant comorbidity. Further investigation is warranted into this potential novel application of ketamine.
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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 | 0.001 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".