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Record W4307999330 · doi:10.3389/fpsyt.2022.939302

MDMA-assisted therapy is associated with a reduction in chronic pain among people with post-traumatic stress disorder

2022· article· en· W4307999330 on OpenAlexafffund
Devon Christie, Berra Yazar‐Klosinski, Ekaterina Nosova, Pam Kryskow, Will Siu, Danielle Lessor, Elena Argento

Bibliographic record

VenueFrontiers in Psychiatry · 2022
Typearticle
Languageen
FieldPsychology
TopicPsychedelics and Drug Studies
Canadian institutionsVancouver Island UniversityBritish Columbia Centre on Substance UseMemorial University of NewfoundlandUniversity of British Columbia
FundersCanadian Institutes of Health ResearchMichael Smith Health Research BC
KeywordsMDMAChronic painMedicineInterquartile rangeBrief Pain InventoryAnalysis of variancePsychiatryPhysical therapyClinical psychologyPsychologyInternal medicine

Abstract

fetched live from OpenAlex

Introduction Increasing evidence demonstrates 3,4-methylenedioxymethamphetamine (MDMA)-assisted therapy (MDMA-AT) may be a safe and effective treatment for post-traumatic stress disorder (PTSD). There is growing interest in MDMA-AT to address a range of other health challenges. Chronic pain and PTSD are frequently comorbid, reciprocally interdependent conditions, though the possible role of MDMA-AT in treating chronic pain remains under-investigated. The present analysis examined the impact of manualized MDMA-AT on chronic pain severity among participants with PTSD who were enrolled in a Phase 2 clinical trial investigating MDMA-AT for PTSD (NCT03282123). Materials and methods Exploratory data from a subset of participants who completed chronic pain measures ( n = 32) were drawn from a Phase 2 open-label study sponsored by the Multidisciplinary Association for Psychedelic Studies (MAPS). Multivariable analysis of variance (ANOVA) was utilized to compare pre- vs. post-treatment Chronic Pain Grade Scale (CPGS) values, adjusting for demographics (age, sex, and ethnicity). K-means clustering was then used to group the sample into three clusters to denote high ( n = 9), medium ( n = 11), and low ( n = 12) baseline pain severity, and the same analysis was repeated for each cluster. Results Among the 32 participants included in this analysis, 59% ( n = 19) were women, 72% ( n = 23) were white, and median age was 38 years [interquartile range (IQR) = 31–47]. Overall, 84% ( n = 27) reported having pain, and 75% ( n = 24) reported disability associated with their pain. Significant reductions in CPGS subscales for pain intensity and disability score , and overall CPGS severity grade were observed among participants in the highest pain cluster ( n = 9, p < 0.05), and for pain intensity in the medium pain cluster ( n = 11, p < 0.05) post- vs. pre-treatment. Discussion Findings demonstrate a high prevalence of chronic pain in this sample of people with severe PTSD and that chronic pain scores among medium and high pain subgroups were significantly lower following MDMA-AT. While these data are preliminary, when considered alongside the frequency of comorbid chronic pain and PTSD and promising efficacy of MDMA-AT for treating PTSD, these findings encourage further research exploring the role of MDMA-AT for chronic pain.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.009
GPT teacher head0.254
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2022
Admission routes2
Has abstractyes

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