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Record W2796894883 · doi:10.1093/jbcr/iry006.065

62 Pain and PTSD Severity are Reciprocally Related in Burn Survivors at 6 months Post-Discharge

2018· article· en· W2796894883 on OpenAlexaboutno aff
Amanda Gehrke, Emily K. Presseller, Luis Quiroga, Julie Caffrey, J. A. Fauerbach

Bibliographic record

VenueJournal of Burn Care & Research · 2018
Typearticle
Languageen
FieldMedicine
TopicBurn Injury Management and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineChronic painMcGill Pain QuestionnaireBurn injuryPhysical therapyBurn centerBayesian multivariate linear regressionPain catastrophizingInternal medicinePoison controlSurgeryLinear regressionEmergency medicineVisual analogue scale

Abstract

fetched live from OpenAlex

Following autograft, 28% of burn survivors report moderate-severe graft site pain at 6 weeks and 21% at 6 months. Additionally, an estimated 2–40% of burn survivors have posttraumatic stress disorder (PTSD) 3–6 months post-burn. While both pain and PTSD are common in burn survivors, examination of their impact on one another in these individuals is limited. The present study aimed to investigate this relationship in burn survivors, specifically evaluating the applicability of the Mutual Maintenance Model (MMM), which proposes that pain and PTSD are reciprocally related. Burn Model System data (1994 to 2014) were analyzed. Independent variables (IVs) included acute pain at discharge, or Acute Pain-DC (measured by McGill Pain Questionnaire-Short Form, or SF-MPQ), and PTSD at 6 months, or PTSD-6 (measured by Davidson Trauma Scale), and the outcome was chronic pain at 6 months post-discharge, or Chronic Pain-6 (measured by SF-MPQ). A linear regression was used to examine whether the IVs and their interaction (Acute Pain-DC X PTSD-6) were associated with Chronic Pain-6. Post-hoc multivariate linear regressions investigating the Chronic Pain-6 subscales, Affective Pain and Sensory Pain, were also completed. Sample characteristics (N= 166 with complete data) included: Caucasian (70%), male (69%), mean age 42 years (SD = 15). Injury severity descriptors included: mean TBSA burned 14.65% (SD = 15.6), and length of stay 21.5 days (SD = 23.4). The overall regression model for Chronic Pain-6 was significant (R2 = 0.45, p = 0.000); PTSD-6 was the only significant IV (β = 0.29, p = 0.019). The overall model for Chronic Pain-6 (Affective) was also significant (R2 = 0.42, p = 0.000), with PTSD-6 being the only significant IV (β = 0.48, p = 0.000). The overall model for the Chronic Pain-6 (Sensory) was significant (R2 = 0.42, p = 0.000), as well. Notably, the only significant IV in this model was the interaction between PTSD-6 and Acute Pain-DC (Sensory). See Figure 1 for detailed results. As hypothesized, the MMM was supported: chronic PTSD-6 was significantly associated with Chronic Pain-6. Results also indicate that the interaction of Acute Pain-DC (Sensory) and Chronic PTSD-6 was significantly related to Chronic Pain-6 (Sensory). PTSD and Pain are reciprocally related at 6 months; efforts to prevent or treat them in acute care and rehabilitation will likely reduce their chronicity. Potential mechanisms and possible interventions will be presented.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.036
GPT teacher head0.354
Teacher spread0.319 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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