Predictors of antidepressant response in clinical trials of transcranial magnetic stimulation
Bibliographic record
Abstract
Although previous clinical trials have suggested that repetitive transcranial magnetic stimulation (rTMS) has a significant antidepressant effect, the results of these trials are heterogeneous. We hypothesized that individual patients' characteristics might contribute to such heterogeneity. Our aim was to identify predictors of antidepressant response to rTMS. We pooled data from six separate clinical trials conducted independently, which evaluated the effects of rapid rTMS of the left dorsolateral prefrontal cortex in patients with major depression. We investigated 195 patients with regard to demographic, depression and treatment characteristics, psychiatric and drug history. Results showed that age and treatment refractoriness were significant negative predictors of depression improvement when adjusting these variables to other significant predictors and confounders. These findings were not confounded by methodological differences from the six studies, as the results were adjusted for the study site. In conclusion TMS antidepressant therapy in younger and less treatment-resistant patients is associated with better outcome.
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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 | 0.010 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| 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) | 0.002 | 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".