Non-improvement predicts subsequent non-response to repeated-dose intravenous ketamine for depression: a re-analysis of a 2-week open-label study in patients with unipolar and bipolar depression
Bibliographic record
Abstract
There is insufficient evidence to guide dose and frequency optimization with repeated-dose ketamine for depression. This study assessed the value of symptomatic non-improvement after the first few ketamine infusions as a predictor of overall non-response in depression for early decision-making to discontinue treatment. A total of 135 individuals with major depressive disorder or bipolar disorder experiencing a current major depressive episode were administered six repeated doses of intravenous ketamine. Depressive symptoms were assessed using the Montgomery-Åsberg Depression Rating Scale (MADRS) at baseline, 4 h after the first infusion, and 24 h after each infusion. Improvement, partial response, and response were defined as a reduction rate of ≥ 20%, 30%, and 50% in MADRS scores, respectively. This study examined the relationship between improvement (as opposed to non-improvement after each infusion or consecutive non-improvements after the first few infusions) and partial response and response after the sixth infusion. This analysis was summarized using sensitivity, specificity, and other diagnostic test parameters. The sensitivities of improvement at 24 h post-infusion 4 and improvement at 24 h post-infusion 3, vs. three consecutive non-improvements, as predictors for overall partial response and response exceeded 90%. No significant reduction in depressive symptoms was seen in non-improvers following the remaining infusions after the above-identified point. Our study suggests that non-improvement after four infusions, or more conservatively three consecutive non-improvements after three infusions, could serve as a signal of overall non-response to repeated-dose intravenous ketamine for depression and that subsequent treatments would not be warranted.
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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 | 0.003 | 0.006 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".