Purpose
To develop a predictive machine learning model to identify prognostic factors for
continued opioid prescriptions after arthroscopic meniscus surgery.
Methods
Patients undergoing arthroscopic meniscal surgery, such as meniscus debridement, repair,
or revision at a single institution from 2013 to 2017 were retrospectively followed
up to 1 year postoperatively. Procedural details were recorded, including concomitant
procedures, primary versus revision, and whether a partial debridement or a repair
was performed. Intraoperative arthritis severity was measured using the Outerbridge
Classification. The number of opioid prescriptions in each month was recorded. Primary
analysis used was the multivariate Cox-Regression model. We then created a naïve Bayesian
model, a machine learning classifier that uses Bayes’ theorem with an assumption of
independence between variables.
Results
A total of 581 patients were reviewed. Postoperative opioid refills occurred in 98
patients (16.9%). Multivariate logistic modeling was used; independent risk factors
for opioid refills included male sex, larger body mass index, and chronic preoperative
opioid use, while meniscus resection demonstrated decreased likelihood of refills.
Concomitant procedures, revision procedures, and presence of arthritis graded by the
Outerbridge classification were not significant predictors of postoperative opioid
refills. The naïve Bayesian model for extended postoperative opioid use demonstrated
good fit with our cohort with an area under the curve of 0.79, sensitivity of 94.5%,
positive predictive value (PPV) of 83%, and a detection rate of 78.2%. The two most
important features in the model were preoperative opioid use and male sex.
Conclusion
After arthroscopic meniscus surgery, preoperative opioid consumption and male sex
were the most significant predictors for sustained opioid use beyond 1 month postoperatively.
Intraoperative arthritis was not an independent risk factor for continued refills.
A machine learning algorithm performed with high accuracy, although with a high false
positive rate, to function as a screening tool to identify patients filling additional
narcotic prescriptions after surgery.
Level of Evidence
III, retrospective comparative study.
To read this article in full you will need to make a payment
Purchase one-time access:
Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online accessOne-time access price info
- For academic or personal research use, select 'Academic and Personal'
- For corporate R&D use, select 'Corporate R&D Professionals'
Subscribe:
Subscribe to ArthroscopyAlready a print subscriber? Claim online access
Already an online subscriber? Sign in
Register: Create an account
Institutional Access: Sign in to ScienceDirect
References
- Trends in meniscus repair and meniscectomy in the United States, 2005-2011.Am J Sports Med. 2013; 41: 2333-2339
- Treatment of knee meniscus pathology: Rehabilitation, surgery, and orthobiologics.PMR. 2019; 11: 292-308
- Rehabilitation after arthroscopic meniscectomy: A critical review of the clinical trials.Int Orthop. 2001; 24: 350-353
- Using patient satisfaction as a basis for reimbursement: political, financial, and philosophical implications.Creat Nurs. 2012; 18: 118-123
- Impact of pain on patient satisfaction integration process: How patients with pain combine their health care attribute reactions.Health Serv Res Manag Epidemiol. 2015; 2 (2333392815615103)
- Opioid consumption after arthroscopic meniscal procedures and anterior cruciate ligament reconstruction.Orthop J Sports Med. 2020; 8 (2325967120913549)
- Opioid overdose.StatPearls Publishing, Treasure Island, FL2021
- The opioid crisis and the orthopedic surgeon.J Arthroplasty. 2018; 33: 3379-3382 e3371
- Machine learning in orthopedics: A literature review.Front Bioeng Biotechnol. 2018; 6: 75
- Development of a machine learning algorithm for early detection of opioid use disorder.Pharmacol Res Perspect. 2020; 8e00669
- Machine-learning model successfully predicts patients at risk for prolonged postoperative opioid use following elective knee arthroscopy.Knee Surg Sports Traumatol Arthrosc. 2022; 30: 762-772
- Preoperative opioid use is associated with persistent use, readmission and postoperative complications after arthroscopic knee surgery.Arthroscopy. 2021; 37: 1567-1572
- Machine learning algorithms predict prolonged opioid use in opioid-naive primary hip arthroscopy patients.J Am Acad Orthop Surg Glob Res Rev. 2021; 5e21.00093-00098
- Can predictive modeling tools identify patients at high risk of prolonged opioid use after ACL reconstruction?.Clin Orthop Relat Res. 2020; 478: 0-1618
- Risk factors for postoperative opioid use in arthroscopic meniscal surgery.Arthroscopy. 2019; 35: 575-580
- Machine learning applications in the neuro ICU: A solution to big data mayhem?.Front Neurol. 2020; 11: 554633
- Opioid demand before and after anterior cruciate ligament reconstruction.Am J Sports Med. 2017; 45: 3098-3103
- Classifications in brief: Outerbridge classification of chondral lesions.Clin Orthop Relat Res. 2018; 476: 2101-2104
- Predicting 30-day mortality after ST elevation myocardial infarction: Machine learning-based random forest and its external validation using two independent nationwide datasets.J Cardiol. 2021; 78: 439-446
- Machine learning in cardiology-ensuring clinical impact lives up to the hype.J Cardiovasc Pharmacol Ther. 2020; 25: 379-390
- Opioid prescription refills after osteochondral procedures of the knee.Arthroscopy. 2019; 35: 2083-2088
- Preoperative opioid use predicts prolonged postoperative opioid use and inferior patient outcomes following anterior cruciate ligament reconstruction.Arthroscopy. 2020; 36 (e2681): 2681-2688
- Risk factors for postoperative opioid use in arthroscopic shoulder labral surgery.Arthroscopy. 2020; 36: 1813-1820
- Preoperative opioid usage, male sex, and preexisting knee osteoarthritis impacts opioid refills after isolated arthroscopic meniscectomy: A population-based study.Arthroscopy. 2020; 36: 2478-2485
- Risk factors for opioid use after anterior cruciate ligament reconstruction.Am J Sports Med. 2019; 47: 2130-2137
- Narcotics and knee arthroscopy: Trends in use and factors asociated with prolonged use and postoperative complications.Arthroscopy. 2018; 34: 1931-1939
- Machine learning algorithms predict extended postoperative opioid use in primary total knee arthroplasty.Knee Surg Sports Traumatol Arthrosc. 2022; 30: 2573-2581
- A machine-learning algorithm to predict the likelihood of prolonged opioid use following arthroscopic hip surgery.Arthroscopy. 2022; 38: 839-847.e2
- Factors affecting long-term results after arthroscopic partial meniscectomy.Clin Orthop Relat Res. 2000; : 161-168
- A controlled trial of arthroscopic surgery for osteoarthritis of the knee.N Engl J Med. 2002; 347: 81-88
- Editorial commentary: Scoping knees with osteoarthritis and opioid dependence? Brace yourself for postop pain.Arthroscopy. 2019; 35: 581-582
- Meniscal repair results in inferior short-term outcomes compared with meniscal resection: A cohort study of 6398 patients with primary anterior cruciate ligament reconstruction.Knee Surg Sports Traumatol Arthrosc. 2018; 26: 2251-2258
- Why significant variables aren't automatically good predictors.Proc Natl Acad Sci USA. 2015; 112: 13892-13897
Article info
Publication history
Published online: December 28, 2022
Accepted:
December 13,
2022
Received:
April 11,
2022
Publication stage
In Press Journal Pre-ProofFootnotes
The authors report the following potential conflicts of interest or sources of funding: K.R.O. reports educational support and grants from Arthrex, educational support, lodging, and travel support from Smith & Nephew, educational support from Pinnacle and Medwest Associates, and travel support and lodging from Wright Medical Technology and Stryker. Full ICMJE author disclosure forms are available for this article online, as supplementary material.
Identification
Copyright
© 2023 by the Arthroscopy Association of North America
