Estimating Risk of Chronic Pain and Disability Following Musculoskeletal Trauma in the United Kingdom
Bibliographic record
Abstract
Importance: Serious traumatic injury is a leading cause of death and disability globally, with most survivors known to develop chronic pain. Objective: To describe early variables associated with poor long-term outcome for posttrauma pain and create a clinical screening tool for this purpose. Design, Setting, and Participants: This was a prospective cohort study at a major trauma center hospital in England. Recruitment commenced in December 2018 and ceased in March 2020. Participants were followed up for 12 months. Patients aged 16 years or older who were hospitalized because of acute musculoskeletal trauma within the preceding 14 days were included. Data were analyzed from March to December 2021. Exposure: Acute musculoskeletal trauma requiring admittance to a major trauma center hospital. Main Outcomes and Measures: A poor outcome was defined as Chronic Pain Grade II or higher and measured at both 6 months (primary time point) and 12 months. A broad range of candidate variables potentially associated with outcomes were used, including surrogates for pain mechanisms, quantitative sensory testing, and psychosocial factors. Univariable models were used to identify the variables most likely to be associated with poor outcome, which were entered into multivariable models. A clinical screening tool (nomogram) was derived from 6-month results. Results: In total, 1590 consecutive patients were assessed for eligibility, of whom 772 were deemed eligible and 124 (80 male [64.5%]; mean [SD] age, 48.9 [18.8] years) were recruited. At 6 months, 19 of 82 respondents (23.2%) reported a good outcome, whereas at 12 months 27 of 44 respondents (61.4%) reported a good outcome. At 6 months on univariable analysis, an increase in total posttraumatic stress symptoms (odds ratio [OR], 2.09; 95% CI, 1.33-3.28), pain intensity average (OR, 2.87; 95% CI, 1.37-6.00), number of fractures (OR, 2.79; 95% CI, 1.02-7.64), and pain extent (OR, 4.67; 95% CI, 1.57-13.87) were associated with worse outcomes. A multivariable model including those variables had a sensitivity of 0.93, a specificity of 0.54, and C-index of 0.92. Conclusions and Relevance: A poor long-term pain outcome from musculoskeletal traumatic injuries may be estimated by measures recorded within days of injury. These findings suggest that posttraumatic stress symptoms, pain spatial distribution, perceived average pain intensity, and number of fractures are good candidates for a sensitive multivariable model and derived clinical screening tool.
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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 | 0.014 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".