Factors Predictive of Prolonged Postoperative Narcotic Usage Following Orthopaedic Surgery
Bibliographic record
Abstract
BACKGROUND: The purpose of this comprehensive review was to investigate risk factors associated with prolonged opioid use after orthopaedic procedures. A comprehensive review of the opioid literature may help to better guide preoperative management of expectations as well as opioid-prescribing practices. METHODS: A systematic review of all studies pertaining to opioid use in relation to orthopaedic procedures was conducted using the MEDLINE, Embase, and CINAHL databases. Data from studies reporting on postoperative opioid use at various time points were collected. Opioid use and risk of prolonged opioid use were subcategorized by subspecialty, and aggregate data for each category were calculated. RESULTS: There were a total of 1,445 eligible studies, of which 45 met inclusion criteria. Subspecialties included joint arthroplasty, spine, trauma, sports, and hand surgery. A total of 458,993 patients were included, including 353,330 (77%) prolonged postoperative opioid users and 105,663 (23%) non-opioid users. Factors associated with prolonged postoperative opioid use among all evaluated studies included body mass index (BMI) of ≥40 kg/m (relative risk [RR], 1.06 to 2.32), prior substance abuse (RR, 1.08 to 3.59), prior use of other medications (RR, 1.01 to 1.46), psychiatric comorbidities (RR, 1.08 to 1.54), and chronic pain conditions including chronic back pain (RR, 1.01 to 10.90), fibromyalgia (RR, 1.01 to 2.30), and migraines (RR, 1.01 to 5.11). Age cohorts associated with a decreased risk of prolonged postoperative opioid use were those ≥31 years of age for hand procedures (RR, 0.47 to 0.94), ≥50 years of age for total hip arthroplasty (RR, 0.70 to 0.80), and ≥70 years of age for total knee arthroplasty (RR, 0.40 to 0.80). Age cohorts associated with an increased risk of prolonged postoperative opioid use were those ≥50 years of age for sports procedures (RR, 1.11 to 2.57) or total shoulder arthroplasty (RR, 1.26 to 1.40) and those ≥70 years of age for spine procedures (RR, 1.61). Identified risk factors for postoperative use were similar across subspecialties. CONCLUSIONS: We provide a comprehensive review of the various preoperative and postoperative risk factors associated with prolonged opioid use after elective and nonelective orthopaedic procedures. Increased BMI, prior substance abuse, psychiatric comorbidities, and chronic pain conditions were most commonly associated with prolonged postoperative opioid use. Careful consideration of elective surgical intervention for painful conditions and perioperative identification of risk factors within each patient's biopsychosocial context will be essential for future modulation of physician opioid-prescribing patterns. LEVEL OF EVIDENCE: Prognostic Level IV. See Instructions for Authors for a complete description of levels of evidence.
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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 | 0.003 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".