Toward a definition of treatment-resistant posttraumatic stress disorder: A systematic review
Bibliographic record
Abstract
Introduction: Posttraumatic stress disorder (PTSD) is a complex disorder that often persists despite the use of evidence-based treatments. This systematic review aims to synthesize existing definitions of treatment-resistant PTSD (TR-PTSD) and examine the criteria used across studies to inform future research and clinical guidelines. Methods: A systematic search was conducted in four databases. Studies were included if they reported on adult participants with TR-PTSD, regardless of definition, or described non-response to one or more treatments. A narrative synthesis was used to categorize findings and suggest refinements to a working TR-PTSD definition. Results: Of 4,046 screened articles, 55 studies met the inclusion criteria. We found substantial variation in how TR-PTSD was defined across studies. Studies investigated pharmacological (n = 19), psychosocial (n = 16), psychedelic-assisted (n = 7), and emerging treatments (n = 13). Findings highlighted diverse intervention strategies. Some reduced PTSD symptoms significantly, and others showed mixed or limited efficacy. Discussion: This study consolidates existing research on TR-PTSD, revealing significant variability in its definitions across studies. The lack of standardized criteria underscores the need for a more consistent framework to guide research and clinical decision-making. The authors propose a dynamic reassessment of treatment resistance that considers adherence, treatment delivery, comorbidities, and mechanisms of action. Future research should incorporate a broader range of treatment response indicators, such as biomarkers and clinical subtypes, to establish a standardized model for TR-PTSD. A clearer definition will improve patient care, aid in therapy selection, and support the development of more effective treatments.
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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 | 0.056 | 0.163 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.010 |
| Bibliometrics | 0.026 | 0.020 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".