CURRENT POST-TRAUMATIC STRESS-RELATED SYMPTOMS AND DEPRESSION OUTCOMES FROM REPETITIVE TRANSCRANIAL MAGNETIC STIMULATION IN CIVILIANS
Bibliographic record
Abstract
Abstract Background There are mixed results on the impact of co-morbid post-traumatic stress disorder (PTSD) on the effect of repetitive transcranial magnetic stimulation (rTMS) for major depressive disorder (MDD) in military veterans. Some find PTSD status does not affect improvement in depressive symptoms while others find PTSD predicts poorer response and remission [1–3]. The impact of PTSD symptoms on the anti-depressive effects of rTMS for civilians remains poorly studied. Aims & Objectives Our primary aim was to test the impact of current PTSD symptoms on depressive outcomes among civilians receiving rTMS for depression. A secondary aim was to explore potential interaction with adverse childhood experiences (ACEs). Method A retrospective analysis was performed on patients with MDD receiving open-label high frequency rTMS to the left dorsolateral prefrontal cortex. Primary outcomes were improvement in the Hamilton Depression Rating Scale (HAMD-17) from baseline and remission (HAMD-17 score 7 or less) at end-of-acute treatment (4 or 6 weeks) of rTMS. Probable PTSD status was defined as scoring 4 or 5 in the Primary Care PTSD Screen for DSM-5 (PC-PTSD-5). Categories of ACEs were quantified using the ACE-10 questionnaire. Baseline characteristics were compared using the t-test or the chi-square test. Multiple linear regression and multiple logistic regression were used to model the impact of PTSD status, ACEs, and their interaction on the primary outcomes while controlling for other variables. Covariates included in models were anxiety (subscale of the DSM-5 Self-rated Level 1 Cross- Cutting Measure), perceived social support, medical comorbidity (Cumulative Illness Rating Scale for Geriatrics) as well as age, gender, studying/working or not, antidepressant use count, TMS type (intermittent theta burst, iTBS or deep TMS) and number of treatment weeks (4 or 6). Results 24% (33/140) had probable PTSD. At baseline, those with probable PTSD had higher HAMD-17 (t = -3.5, p <0.001), higher anxiety (t = -2.6, p = 0.01), more ACEs (t = -5.8, p <0.0001), lower social support (t = 2.2, p = 0.03), and greater medical comorbidity (t = -3.6, p <0.001). In a linear regression model for HAMD-17 improvement, having more ACEs was associated with more improvement (t = 2.12, p = 0.036) whereas PTSD status had no significant effect (t = 1.86, p = 0.065) and there was no interaction between the two (t = -1.68, p = 0.096). In a logistic model for remission, higher ACE was associated with greater odds of remission (OR 1.4, z = 3.0, p = 0.003), whereas PTSD status had no effect (z = 0.08, p = 0.93) and no interaction was found (z = -1.14, p = 0.255). Discussion & Conclusion Though probable PTSD status was associated with higher baseline depression scores among civilians receiving rTMS for depression, it did not significantly impact improvement in depression symptoms or remission. These results suggest there is benefit to the use of rTMS (including iTBS and deep TMS) for civilians with depression even when there are concurrent PTSD symptoms and/or a history of childhood adversity. References [1]Yesavage JA, Fairchild JK, Mi Z, Biswas K, Davis-Karim A, Phibbs CS, et al. Effect of Repetitive Transcranial Magnetic Stimulation on Treatment-Resistant Major Depression in US Veterans: A Randomized Clinical Trial. JAMA Psychiatry 2018;75:884. https://doi.org/10.1001/jamapsychiatry.2018.1483. [2]Hernandez MJ, Reljic T, Van Trees K, Phillips S, Hashimie J, Bajor L, et al. Impact of Comorbid PTSD on Outcome of Repetitive Transcranial Magnetic Stimulation (TMS) for Veterans With Depression. J Clin Psychiatry 2020;81. https://doi.org/10.4088/JCP.19m13152. [3]Brigido S, Bozzay M, Philip NS. Posttraumatic Stress Disorder Symptom Severity Does Not Predict Depression Improvement, but May Impact Clinical Response and Remission. J Clin Psychiatry 2021;82. https://doi.org/10.4088/JCP.20l13751.
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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 | 0.002 |
| 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) | 0.002 | 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".