Ketamine Versus Midazolam for Depression Relapse Prevention Following Successful Electroconvulsive Therapy
Bibliographic record
Abstract
OBJECTIVE: Depression relapse after electroconvulsive therapy (ECT) is common (40% at 6 months). Ketamine has a robust antidepressant effect, but there are no reported studies of ketamine for depression relapse prevention. This pilot trial (NCT02414932) was designed to assess feasibility of the proposed trial protocol, including examining reasons for nonrecruitment, nonrandomization, and dropout. METHODS: Patients with unipolar depression referred for ECT were monitored weekly for therapeutic response, using the 24-item Hamilton Rating Scale for Depression (monitoring phase). Those who met standard response criteria were invited to be randomized to a course of 4 once-weekly infusions of ketamine (0.5 mg/kg) or the active comparator, midazolam (0.045 mg/kg), over 40 minutes to examine trial processes (treatment phase). Participants were followed up for 6 months after ECT to assess for relapse. RESULTS: One hundred seventy-five referrals were screened over 18 months, and 68% of eligible participants (n = 43) were recruited to the monitoring phase; 60.5% of participants met ECT response criteria (n = 26), but only 26% (6) of these consented to take part in the treatment phase. These were randomized (3 to ketamine and 3 to midazolam), and no participant completed the 4-week treatment protocol. Information was gathered on reasons for nonrecruitment, nonrandomization, and dropout, which included practical aspects of infusions and lack of interest in further treatment after response to ECT. CONCLUSIONS: The proposed treatment protocol is not suitable for a definitive trial in our center. Information collected on reasons for dropout may inform future clinical trials of intravenous ketamine. TRIAL REGISTRATION: www.clinicaltrials.gov NCT02414932.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".