Electroconvulsive therapy with a memory reactivation intervention for post-traumatic stress disorder: A randomized controlled trial
Bibliographic record
Abstract
Background Post-traumatic Stress Disorder (PTSD) often does not respond to available treatments. Memories are vulnerable to disruption during reconsolidation, and electroconvulsive therapy (ECT) has amnestic effects Objective/hypothesis To test the use of ECT to disrupt the reconsolidation of traumatic memories as a potential treatment for PTSD Methods Participants were adults from the civilian population and were referred for ECT treatment for severe depression with comorbid PTSD symptoms. Twenty-eight participants were randomly assigned to reactivation of a traumatic or non-traumatic memory using audio script driven imagery prior to each ECT treatment. Primary outcomes were change in scores on the Modified PTSD Symptom Scale - Self Report (MPSS-SR) and the Clinician-Administered PTSD Scale for DSM-5 (CAPS-5). Secondary outcomes included a comparison of the change in heart rate while listening to the script Results Twenty-five female patients who completed a post-ECT assessment were included in the analysis. No significant group differences were found in the MPSS-SR or CAPS-5 scores from pre-ECT to post-ECT or 3-month follow-ups. However, both groups improved at post-ECT and 3-month follow up. Partial eta squared estimates of effect size showed large effect sizes for all outcomes (η 2 > 0.13). Changes in heart rate were not significantly different between groups or over time Conclusions ECT paired with pre-treatment traumatic memory reactivation was not more effective for treating PTSD symptoms than ECT with non-traumatic memory reactivation. While our primary hypothesis was not supported, our data provides further support for the efficacy of ECT for improving symptoms of PTSD with comorbid depression. ClinicalTrials.gov. https://clinicaltrials.gov/ct2/show/NCT04027452. Identifier NCT04027452.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".