Effect of antipsychotic pharmacotherapy on clinical outcomes of intermittent theta-burst stimulation for refractory depression
Bibliographic record
Abstract
Theta-burst stimulation is an emerging protocol for repetitive transcranial magnetic stimulation that takes 1-3 min to administer, yet offers equal/superior potency to conventional protocols lasting 30-60 min. However, preclinical evidence suggests that D2 receptor blockade may abolish the acute effects of theta-burst stimulation on synaptic facilitation or inhibition. As many patients presenting for repetitive transcranial magnetic stimulation are taking antipsychotic medications as augmentation for treatment-resistant depression, this finding is potentially concerning for the implementation of theta-burst stimulation in clinical settings. Here, we examined whether treatment-resistant depression patients taking antipsychotics have worse outcomes after a course of intermittent theta-burst stimulation. A chart review identified 105 treatment-resistant depression patients who underwent dorsomedial prefrontal-intermittent theta-burst stimulation; clinical outcomes on Hamilton Depression Rating Scale and Beck Depression Inventory were compared for those taking and not taking antipsychotics. The 29 of 105 patients who were taking antipsychotics showed non-significantly better response and remission rates, and non-significantly larger percentage improvements on both scales, with a positive but non-significant correlation between higher antipsychotic dose and larger percentage improvement. Contrary to expectations, outcomes were not significantly worse, and in some analyses trended towards being better, in patients taking antipsychotics. Future randomized controlled studies of repetitive transcranial magnetic stimulation combined with standardized dopaminergic manipulations may be justified and 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 | 0.001 | 0.003 |
| 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 | 0.000 | 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".