Transcranial Magnetic Stimulation in the Treatment of Depression
Bibliographic record
Abstract
BACKGROUND: High-frequency left-sided repetitive transcranial magnetic stimulation (HFL-TMS) has been shown to have antidepressant effects in double-blind trials. Low-frequency stimulation to the right prefrontal cortex (LFR-TMS) has also shown promise, although it has not been assessed in treatment-resistant depression and its effects have not been compared with those of HFL-TMS. OBJECTIVE: To prospectively evaluate the efficacy of HFL-TMS and LFR-TMS in treatment-resistant depression and compared with a sham-treated control group. DESIGN: A double-blind, randomized, sham-controlled trial. SETTING: Two general psychiatric services. PARTICIPANTS: Sixty patients with treatment-resistant depression who had failed to respond to therapy with multiple antidepressant medications were divided into 3 groups of 20 that did not differ in age, sex, or any clinical variables. All patients completed the double-blind phase of the study. INTERVENTIONS: Twenty 5-second HFL-TMS trains at 10 Hz and five 60-second LFR-TMS trains at 1 Hz were applied daily. Sham stimulation was applied with the coil angled at 45 degrees from the scalp, resting on the side of one wing of the coil. Main Outcome Measure Score on the Montgomery-Asberg Depression Rating Scale. RESULTS: There was a significant difference in response among the 3 groups (F56,2 = 6.2), with a significant difference between the HFL-TMS and sham groups and between the LFR-TMS and sham groups (P<.005 for all) but not between the 2 treatment groups. Baseline psychomotor agitation predicted successful response to treatment. CONCLUSIONS: Both HFL-TMS and LFR-TMS have treatment efficacy in patients with medication-resistant major depression. Treatment for at least 4 weeks is necessary for clinically meaningful benefits to be achieved. Treatment with LFR-TMS may prove to be an appropriate initial repetitive TMS strategy in depression taking into account safety, tolerability, and efficacy considerations.
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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 | 0.001 |
| 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 | 0.001 |
| 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".