Early Factors Associated with the Development of Chronic Pain in Trauma Patients
Bibliographic record
Abstract
Objective: To identify factors, available at the time of trauma admission, associated with the development of chronic pain to allow testing of preventive approaches. Methods: In a retrospective observational cohort study, we included all patients ≥ 18 years old admitted for injury in 57 adult trauma centers in the province of Quebec (Canada) between 2004 and 2014. Chronic pain was defined as follows: treated in a chronic pain clinic, diagnosed with chronic pain, or received at least 2 prescriptions of chronic pain medications 3 to 12 months postinjury. Results: A total of 95,134 patients were retained for analysis. Mean age was 59.8 years (±21.7), and 52% were men. The causes of trauma were falls (63%) and motor vehicle accidents (22%). We identified 14,518 patients (15.3%; 95% CI: 15.1-15.5) who developed chronic pain. After controlling for confounding factors, the variables associated with chronic pain were spinal cord injury (OR = 3.9; 95% CI: 3.4-4.6), disc-vertebra trauma (OR = 1.6; 95% CI: 1.5-1.7), history of alcoholism (OR = 1.4; 95% CI: 1.2-1.7), history of anxiety (OR = 1.4; 95% CI: 1.2-1.5), history of depression (OR = 1.3; 95% CI: 1.1-1.4), and being female (OR = 1.3; 95% CI: 1.2-1.3). The area under the receiving operating characteristic curve derived from the model was 0.80. Conclusions: We identified risk factors present on hospital admission that can predict trauma patients who will develop chronic pain. These factors should be prospectively validated.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".