ArticleThe archives of bone and joint surgery2022
The Opioid Risk Tool: Can This Validated Tool Predict Post-Operative Opioid Dependence Following Arthroscopic Rotator Cuff Repair?
Article in The archives of bone and joint surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed, 0 citations in OpenAlex.
- Opioid Risk Tool Scores are Not Associated With Opioid Misuse After Elective General Surgery: A Prospective Study.The Journal of surgical research · 2026Observational
- Explainable machine learning to predict prolonged post-operative opioid use in rotator cuff patients.BMC musculoskeletal disorders · 2025Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Numerous attempts have been made to decrease the incidence of opioid dependence after orthopedic surgeries. However, no effective means of preoperative risk stratification currently exists. The purpose of this study was to determine the ability of the Opioid Risk Tool (ORT) to predict the rate of opioid dependence 2 years after arthroscopic rotator cuff repair (ARCR). Methods: We prospectively evaluated all patients undergoing primary ARCR at a single institution over a 1.5 year period with a minimum of 2-year follow-up. All patients completed the ORT prior to surgery and were stratified into Low, Moderate, and High risk categories. The primary outcome was postoperative opioid dependence, defined as receiving a minimum of 6 opioid prescriptions within 2 years following surgery. Secondary outcomes included the total number of morphine milligram equivalents prescribed, total number of opioid prescriptions filled, and total number of opioid pills prescribed during this time interval. All outcome variables were compared amongst Low, Moderate, and High risk groups. Assessment of a statistical correlation between each outcome variable and individual numerical ORT scores (1-9) was performed. Results: A total of 137 patients were included for analysis. No statistically significant difference was noted in any primary or secondary outcome variable when compared between Low, Moderate, and High risk groups. The total cohort demonstrated a 19% rate of post-operative opioid dependence. No correlation was identified between any outcome variable and individual numerical ORT scores. A greater rate of dependence and quantity of opioids prescribed was noted amongst patients with a history of prior opioid use. Conclusion: The ORT was not predictive of the risk of opioid dependence or quantity of opioids prescribed after ARCR. Attention should be focused on alternative means of identification and management of patients at risk for opioid dependence after orthopedic procedures, including those with a history of prior opioid use.
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