Opioid use for a first-incident upper extremity fracture in 220,440 patients without recent prior use in Ontario, Canada: a retrospective cohort study
Bibliographic record
Abstract
Objective: To describe opioid use for a first upper extremity fracture in a cohort of patients who did not have recent opioid use. Design: Descriptive epidemiological study. Setting: Emergency Department, Hospital. Patients/Participants: We obtained health administrative data records of adults presenting with a first adult upper extremity fracture from 2013 to 2017 in Ontario, Canada. We excluded patients with previous fractures, opioid prescription in the past 6 months or hospitalization >5 days after the fracture. Intervention: Opioid prescription. Main Outcome Measurements: We identified the proportion of patients filling an opioid prescription within 7 days of fracture. We described this based on different upper extremity fractures (ICD-10), Demographics (age, sex, rurality), comorbidity (Charlson Comorbidity Index, Rheumatoid arthritis, Diabetes), season of injury, and social marginalization (Ontario Marginalization Index-a data algorithm that combines a wide range of demographic indicators into 4 distinct dimensions of marginalization). We considered statistical differences ( P < .01) that reached a standardized mean difference of 10% as being clinically important (standardized mean difference [SMD] ≥ 0.1). Results: From 220,440 patients with a first upper extremity fracture (50% female, mean age 50), opioids were used by 34% of cases overall (32% in males, 36% in females, P< .001, SMD ≥ 0.1). Use varied by body region, with those with multiple or proximal fractures having the highest use: multiple shoulder 64%, multiple regions 62%, shoulder 62%, elbow 38%, wrist 31%, and hand 21%; and was higher in patients who had a nerve/tendon injury or hospitalization (P< .01, SMD ≥ 0.1). Social marginalization, comorbidity, and season of injury had clinically insignificant effects on opioid use. Conclusions: More than one-third of patients who are recent-non-users will fill an opioid prescription within 7 days of a first upper extremity fracture, with usage highly influenced by fracture characteristics. Level of Evidence: Level II
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".