Impact of Comorbid Posttraumatic Stress-Related Symptoms on Repetitive Transcranial Magnetic Stimulation for Depression in Civilians: Incidence des symptômes du trouble de stress post-traumatique (TSPT) comorbide sur la stimulation magnétique transcrânienne répétitive pour traiter la dépression
Bibliographic record
Abstract
OBJECTIVES: The impact of comorbid posttraumatic stress disorder (PTSD) symptoms on the anti-depressive outcomes of repetitive transcranial magnetic stimulation (rTMS) for civilians with major depressive disorder (MDD) is poorly studied. We aimed to understand whether proximal PTSD symptoms would interact with distal traumas in impacting depression outcomes from rTMS treatment. METHODS: A retrospective analysis was performed on 133 patients with MDD receiving open-label high-frequency rTMS to the left dorsolateral prefrontal cortex for 4 weeks. Probable PTSD was defined as scoring ≥ 4 on the Primary Care PTSD Screen for DSM-5. Distal traumas were quantified using the Adverse Childhood Experiences (ACE-10) questionnaire. Primary outcomes were improvement in Hamilton Rating Scale for Depression 17 item scale (HAMD-17) scores from baseline to 4 weeks as well as remission (HAMD-17 ≤ 7) and response (greater than 50% improvement from baseline). RESULTS: 29/133 had probable PTSD. Patients with probable PTSD had more ACEs, as well as higher depression, anxiety and medical comorbidity scores. Neither probable PTSD status nor its interaction with ACEs significantly impacted depression outcomes. However, having more ACEs was associated with greater odds of remission and response. CONCLUSIONS: Our findings suggest neither co-morbid PTSD symptoms nor distal childhood adversities should preclude patients with MDD from receiving rTMS for depression.Plain Language Summary TitleRepetitive transcranial magnetic stimulation for civilian patients with depression and posttraumatic stress symptoms.
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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 | 0.000 | 0.002 |
| 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".