Patterns of pre-operative opioid use affect the risk for complications after total joint replacement
Bibliographic record
Abstract
Preoperative opioid use has been shown to increase the risk for complications following total joint arthroplasty (TJA); however, these studies have not always accounted for differences in co-morbidities and socio-demographics between patients that use opioids and those that do not. They have also not accounted for the variation in degree of pre-operative use. The objective of this study was to determine if preoperative opioid use is associated with risk for surgical complications after TJA, and if this association varied by degree of use. Population-based retrospective cohort study. Older adult patients undergoing primary TJA of the hip, knee and shoulder for osteoarthritis between 2002 and 2015 in Ontario, Canada were identified. Using accepted definitions, patients were stratified into three groups according to their preoperative opioid use: no use, intermittent use and chronic use. The primary outcome was the occurrence of a composite surgical complication (surgical site infection, dislocation, revision arthroplasty) or death within a year of surgery. Intermittent and chronic users were matched separately to non-users in a 1:1 ratio, matching on TJA type plus a propensity score incorporating patient and provider factors. Overall, 108,067 patients were included in the study; 10% (N = 10,441) used opioids on a chronic basis before surgery and 35% (N = 37,668) used them intermittently. After matching, chronic pre-operative opioid use was associated with an increased risk for complications after TJA (HR 1.44, p = 0.001) relative to non-users. Overall, less than half of patients undergoing TJA used opioids in the year preceding surgery; the majority used them only intermittently. While chronic pre-operative opioid use is associated with an increased risk for complications after TJA, intermitted pre-operative use is not.
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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 | 0.000 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".