A Randomized Sham-controlled Trial of 1-Hz and 10-Hz Repetitive Transcranial Magnetic Stimulation (rTMS) of the Right Dorsolateral Prefrontal Cortex in Civilian Post-traumatic Stress Disorder: Un essai randomisé contrôlé simulé de stimulation magnétique transcrânienne repetitive (SMTr) de 1 Hz et 10 Hz du cortex préfrontal dorsolatéral droit dans le trouble de stress post-traumatique chez des civils
Bibliographic record
Abstract
OBJECTIVE: Despite effective psychological and pharmacological treatments, there is a large unmet burden of illness in post-traumatic stress disorder (PTSD). Repetitive transcranial magnetic stimulation (rTMS) is a noninvasive intervention and a putative treatment strategy for PTSD. The evidence base to date suggests that rTMS targeting the dorsolateral prefrontal cortex (DLPFC), in particular the right DLPFC, leads to improvements in PTSD symptoms. However, optimal stimulation parameters have yet to be determined. In this study, we examine the efficacy of high- and low-frequency rTMS of the right DLPFC using a randomized, double-blind, sham-controlled design in civilian PTSD. METHODS: We conducted a 2-week single-site randomized sham-controlled trial of rTMS targeting the right DLPFC. We recruited civilians aged 19 to 70 with PTSD and randomized subjects with allocation concealment to daily 1-Hz rTMS, 10-Hz rTMS, or sham rTMS. The primary outcome was improvement in Clinician Administered PTSD Scale-IV (CAPS-IV). Secondary outcomes included change in depressive and anxiety symptoms. RESULTS: = -1.07) but not in the 10-Hz group. This was not attributable to changes in anxious or depressive symptomatology. Ten-Hz stimulation appeared to improve depressive symptoms compared to sham. CONCLUSION: Low-frequency rTMS is efficacious in the treatment of civilian PTSD. Our data suggest that high-frequency rTMS of the right DLPFC is worthy of additional investigation for the treatment of depressive symptoms comorbid with PTSD.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".