Brain-derived neurotrophic factor serum levels following ketamine and esketamine intervention for treatment-resistant depression: secondary analysis from a randomized trial
Bibliographic record
Abstract
OBJECTIVES: Evidence suggests that ketamine's influence on brain-derived neurotrophic factor (BDNF) might be involved in its mechanism of rapid antidepressant action. We aimed to evaluate the differential impact of ketamine and esketamine on serum BDNF levels and its association with response patterns in treatment-resistant depression (TRD). METHODS: Participants (n = 53) are from a randomized, double-blind clinical trial comparing the efficacy of single-dose ketamine (0.5mg/kg, n = 27) and esketamine (0.25mg/kg, n = 26) in TRD. Depression severity was assessed before and 24 hours, 72 hours, and 7 days after the intervention, using the Montgomery-Åsberg Depression Rating Scale (MADRS). Blood samples were collected before infusion, 24 hours, and 7 days afterwards. RESULTS: There were no significant changes in BDNF levels at post-infusion evaluation points, and no difference in BDNF levels comparing ketamine and esketamine. Both drugs exhibited similar therapeutic effect. There was no association between BDNF levels and response to treatment or severity of depressive symptoms. CONCLUSION: There was no significant treatment impact on BDNF serum levels - neither with ketamine nor esketamine - despite therapeutic response. These results suggest that ketamine or esketamine intervention for TRD has no impact on BDNF levels measured at 24 hours and 7 days after the infusion.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".