Chronic Opioid Use Prior to Total Knee Arthroplasty
Bibliographic record
Abstract
BACKGROUND: Chronic use of opioid medications may lead to dependence or hyperalgesia, both of which might adversely affect perioperative and postoperative pain management, rehabilitation, and clinical outcomes after total knee arthroplasty. The purpose of this study was to evaluate patients who underwent total knee arthroplasty following six or more weeks of chronic opioid use for pain control and to compare them with a matched group who did not use opioids preoperatively. METHODS: Forty-nine knees in patients who had a mean age of fifty-six years (range, thirty-seven to seventy-eight years) and who had regularly used opioid medications for pain control prior to total knee arthroplasty were compared with a group of patients who had not used them. Length of hospitalization, aseptic complications requiring reoperation, requirement for specialized pain management, and clinical outcomes were assessed for both groups. RESULTS: Knee Society scores were significantly lower in the patients who regularly used opioid medications at the time of final follow-up (mean, three years; range, two to seven years); the opioid group had a mean of 79 points (range, 45 to 100 points) as compared with a mean of 92 points (range, 59 to 100 points) in the non-opioid group. A significantly higher prevalence of complications was seen in the opioid group, with five arthroscopic evaluations and eight revisions for persistent stiffness and/or pain, compared with none in the matched group. Ten patients in the opioid group were referred for outpatient pain management, compared with one patient in the non-opioid group. CONCLUSIONS: Patients who chronically use opioid medications prior to total knee arthroplasty may be at a substantially greater risk for complications and painful prolonged recoveries. Alternative non-opioid pain medications and/or earlier referral to an orthopaedic surgeon prior to habitual opioid use should be considered for patients with painful degenerative disease of the knee.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".