A Mediational Analysis of Stress, Inflammation, Sleep, and Pain in Acute Musculoskeletal Trauma
Bibliographic record
Abstract
OBJECTIVES: Differences in pain severity among acutely injured people may be related to the perceived stress of the event and pre-existing vulnerabilities. In this study, we test the hypotheses that pretrauma life stress influences posttrauma pain severity, and 2 potential mediating pathways, 1 biological (C-reactive protein, CRP) and 1 contextual (sleep quality). MATERIALS AND METHODS: Data collected from participants within 3 weeks of a noncatastrophic musculoskeletal trauma were used in this observational cross-sectional mediation analysis. The primary outcome was pain severity as measured using the Brief Pain Inventory. Predictors were posttrauma CRP assayed from plasma, sleep interference measured by the Brief Pain Inventory, and a study-specific "General Life Stressors" scale. First, the sample was split into low and high life-stress groups, and mean differences in the pain and the predictor variables were explored by t test. Next, a mediation model was tested through a regression-based path analysis. The base model explored the predictive association between pretrauma life stress and posttrauma pain. Sleep quality and CRP concentration were then entered as possible mediators of the association. RESULTS: The sample of 112 participants was 54.6% female, and 52.7% reported high pretrauma life stress. Mean differences in pain severity, sleep interference, and CRP was significant between the high-stress and low-stress groups. In path analysis, life stress explained 8.0% of the variance in acute pain severity, 6.3% of the variance in sleep interference, and 8.0% of the variance in CRP concentration, all P-value <0.05. In mediation analysis, the association between life stress and pain severity was fully mediated by sleep interference. CRP did not mediate the association. DISCUSSION: Pretrauma life stress predicted pain severity, sleep interference, and plasma CRP. In mediation analysis, pretrauma stress was associated with pain severity only through its association with sleep interference, while CRP did not mediate the association. Implications of these results are discussed.
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 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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".