Elective Shoulder Surgery in the Opioid Naïve: Rates of and Risk Factors for Long-term Postoperative Opioid Use
Bibliographic record
Abstract
BACKGROUND: Little is known regarding the rates and risk factors for long-term postoperative opioid use among opioid-naïve patients undergoing elective shoulder surgery. PURPOSE: To identify (1) the proportion of opioid-naïve patients undergoing elective shoulder surgery, (2) the rates of postoperative opioid use among these patients, and (3) the risk factors associated with long-term postoperative opioid use. STUDY DESIGN: Cohort study; Level of evidence, 3. METHODS: A retrospective review of a private administrative claims database was performed to identify those individuals who underwent elective shoulder surgery between 2007 and 2015. "Opioid-naïve" patients were identified as those patients who had not filled an opioid prescription in the 180 days before the index surgery. Within this subgroup, we tracked postoperative opioid prescription refill rates and used a logistic regression to identify patient variables that were predictive for long-term opioid use, which we defined as continued opioid refills beyond 180 days after surgery. Results were reported as odds ratios (ORs). RESULTS: Over the study period, 79,287 patients were identified who underwent elective shoulder surgery, of whom 79.5% were opioid naïve. Among opioid-naïve patients, the rate of postoperative opioid use declined over time, and 14.6% of patients were still using opioids beyond 180 days. The greatest proportion of opioid-naïve patients still filling opioid prescriptions beyond 180 days postoperatively was seen after open rotator cuff repair (20.9%), whereas arthroscopic labral repair had the lowest proportion (9.8%). Overall, a history of alcohol abuse (OR 1.56), a history of depression (OR 1.46), a history of anxiety (OR, 1.31), female sex (OR, 1.11), and higher Charlson Comorbidity Index (OR 1.02) had the most significant influence on the risk for long-term opioid use among opioid naïve patients. CONCLUSIONS: Most patients were opioid naïve before elective shoulder surgery; however, among opioid-naïve patients, 1 in 7 patients were still using opioids beyond 180 days after surgery. Among all variables, a history of mental illness most significantly increased the risk of long-term opioid use after elective shoulder surgery.
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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 | 0.000 |
| 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 | 0.001 |
| 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".