Repetitive Transcranial Magnetic Stimulation over the Dorsolateral Prefrontal Cortex for Treating Posttraumatic Stress Disorder: An Exploratory Meta-Analysis of Randomized, Double-Blind and Sham-Controlled Trials
Bibliographic record
Abstract
OBJECTIVE: Repetitive transcranial magnetic stimulation (rTMS) applied to the dorsolateral prefrontal cortex (DLPFC) has yielded promising results as a treatment for posttraumatic stress disorder (PTSD). However, to date, no quantitative review of its clinical utility has been published. METHOD: We searched for randomized and sham-controlled trials from 1995 to March 2013 using MEDLINE, Embase, PsycINFO, CENTRAL, and SCOPUS. We then performed an exploratory random effects meta-analysis. RESULTS: Studies on rTMS applied to the right DLPFC included 64 adults with PTSD. The pooled Hedges g effect size for pre and post changes in clinician-rated and self-reported PTSD symptoms were, respectively, 1.65 (P < 0.001) and 1.91 (P < 0.001), indicating significant and large-sized differences in outcome favouring active rTMS. Also, there were significant pre and post decreases with active rTMS in overall anxiety (Hedges g = 1.24; P = 0.02) and depressive (Hedges g = 0.85; P < 0.001) symptoms. Dropout rates at study end did not differ between active and sham rTMS groups. Regarding rTMS applied to the left DLPFC, there is only one study published to date (using a high frequency protocol), and its results showed that active rTMS seems to be superior overall to sham rTMS. CONCLUSIONS: Our exploratory meta-analysis shows that active rTMS applied to the DLPFC seems to be effective and acceptable for treating PTSD. However, the small number of subjects included in the analyses limits the generalizability of these findings. Future studies should include larger samples and deliver optimized stimulation parameters.
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How this classification was reachedexpand
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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.011 | 0.007 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".