A randomized trial of the anti-depressant effects of low- and high-frequency transcranial magnetic stimulation in treatment-resistant depression
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: The majority of studies investigating the effectiveness of repetitive transcranial magnetic stimulation (rTMS) as a treatment for major depression have focused on high-frequency rTMS to the left prefrontal cortex (HFL-rTMS). In addition, low-frequency right prefrontal rTMS (LFR-rTMS) has also been shown to have antidepressant properties. To date only a small number of studies have directly compared the efficacy of these two approaches. METHODS: The aim of this study, therefore, was to investigate further whether LFR-rTMS is as effective as HFL-rTMS in the treatment of major depression. Twenty-seven patients were randomized to one of two treatment arms (HFL-rTMS or LFR-rTMS) for 3 weeks with a possible 1-week extension. Non-responders were offered the opportunity of crossing over to the other treatment type. Stimulation parameters for HFL-rTMS were 30 stimulation trains of 5 s duration at 100% of the resting motor threshold (RMT); for LFR-rTMS, stimulation was applied in four trains of 180 s duration (30 s inter-train interval) at 110% of the RMT. Stimulation was provided 5-week days per week. RESULTS: There were significant improvements seen from baseline to end point irrespective of group and on all clinical outcome measures. In addition, there was no deterioration in any of the measures used to assess cognitive change, and significant improvements were seen on measures of immediate verbal memory and verbal fluency. CONCLUSIONS: HFL-rTMS and LFR-rTMS appear to be equally efficacious in treating major depression. This study adds to the growing literature supporting LFR-rTMS as an additional viable method of rTMS delivery in the treatment of depression.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it