Preoperative Opioid Usage, Male Sex, and Preexisting Knee Osteoarthritis Impacts Opioid Refills After Isolated Arthroscopic Meniscectomy: A Population-Based Study

Khazi, Zain; Baron, Jacqueline; Shamrock, Alan G.; Gulbrandsen, Trevor R.; Bedard, Nicholas A.; Wolf, Brian R.; Duchman, Kyle R.; Westermann, Robert W.

doi:10.1016/j.arthro.2020.04.039

Cited by 13 publications

(11 citation statements)

References 29 publications

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“…[2][3][4][5][6] The data from this study were obtained from a large national database with each risk factor designated as a binary value. 1 The severity of each medical condition (e.g., hypertension, congestive heart failure, or diabetes mellitus) was not reflected in the authors' findings.…”

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confidence: 66%

“…7 Similarly, patients who have been desensitized to the therapeutic effects of narcotics may benefit from non-narcotic pain control modalities and opioid cessation prior to surgery. Surgeons must be mindful of these modifiable and nonmodifiable risk factors provided by Khazi et al 1 and should spend extra time counseling these patients about their postoperative course. Recent studies have illustrated positive results when evaluating multimodal and/or nonopioid protocols in the context of arthroscopic surgery, and it is becoming apparent that to optimize therapeutic effects while mitigating adverse effects, the "one-size-fits-all" model of postoperative analgesia is no longer acceptable.…”

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confidence: 99%

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Editorial Commentary: Postoperative Analgesia After Arthroscopy: A Step Toward the Personalization of Pain Control

Jildeh

2020

Arthroscopy: The Journal of Arthroscopic & Related Surgery

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Identification of risk factors for prolonged opioid use is imperative as opioid misuse continues to plague society. Recent data suggest that many modifiable and nonmodifiable patient factors may be associated with prolonged opioid use after arthroscopic meniscal surgery. Surgeons and patients share the burden of the opioid epidemic and must collaborate to decrease the overall opioid burden on society. As the number of tools to treat pain and the knowledge of at-risk patients grow, standardized postoperative narcotic regimens to treat a diverse population of patients are no longer acceptable; narcotic regimens must be customized to each patient. To limit opioid use and enhance patient outcomes, it is apparent that the next frontier of postoperative pain control is upon us: the personalization of pain control.

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confidence: 66%

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confidence: 99%

Editorial Commentary: Postoperative Analgesia After Arthroscopy: A Step Toward the Personalization of Pain Control

Jildeh

2020

Arthroscopy: The Journal of Arthroscopic & Related Surgery

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“…Across multiple subspecialties in orthopaedic surgery, the literature has consistently demonstrated that preoperative opioid use strongly predicts prolonged opioid demand after surgery. 7,[10][11][12][13][14][15][16][17][18][19][20][21]25,26 Anthony et al 19 conducted a multicenter review of 4,946 ACL reconstructions and found that patients with preoperative prescriptions were 4.06 times (95% CI, relative risk 3.33-4.96) more likely to be refilling prescriptions at 2 months and 5.35 to 7.67 times more likely at all time points between 3 and 12 months after surgery. The majority of patients discontinued opioid use after the first postoperative month, with 10% or less refilling at 2 months and beyond.…”

Section: Discussionmentioning

confidence: 99%

“…Previous studies have similarly shown that preoperative knee osteoarthritis predicts prolonged opioid consumption in multiple arthroscopic procedures of the knee such as meniscectomy. 10 , 16 , 21 Surgeons should, however, exhibit caution in patient selection, as significant osteoarthritis at the time of surgery may confer opioid dependence and worse outcomes.…”

Section: Discussionmentioning

confidence: 99%

“… 9 Multiple studies have investigated risk factors leading to prolonged opioid use after common orthopaedic surgeries (e.g., arthritis, psych history, etc.). 7 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 Identifying predictive factors for prolonged opioid use is crucial for orthopaedic surgeons to tailor pain control for specific patients and practice opioid stewardship.…”

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confidence: 99%

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Older, Heavier, Arthritic, Psychiatrically Disordered, and Opioid-Familiar Patients Are at Risk for Opioid Use After Medial Patellofemoral Ligament Reconstruction

Castle

Jildeh

Buckley

et al. 2021

Arthroscopy, Sports Medicine, and Rehabilitation

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Purpose To investigate which factors predispose patients for prolonged opioid use after medial patellofemoral ligament (MPFL) reconstruction. Methods A retrospective review of all patients who underwent MPFL reconstruction at a single institution between January 2013 and June 2020 was conducted. Opioid consumption before and after surgery was recorded and confirmed using Michigan Automated Prescriptions System monitoring program. Patients were classified into preoperative opioid users and nonusers. Risk factors for continued opioid use were assessed by collecting patient demographic variables, psychiatric history, number of previous patellar dislocations, and operative factors. Results A total of 102 patients were included during the time frame of interest. Patients were on average 21.6 ± 8.5 years old with a mean body mass index of 28.2 ± 7.9. Thirty patients (29.0%) sustained >10 dislocations preoperatively. Preoperative opioid use was present in 13 (12.7%) patients. Greater than 10 dislocations (odds ratio [OR] 5.00, 95% confidence interval [CI] 1.12-20.92) and psychiatric history (OR 3.33, 95% CI, 1.2-9.1; P = .016) significantly predicted opioid refills the first month after surgery. Risk factors for opioid refills at 2 to 12 months postoperatively included smoking (OR 4.50, 95% CI 1.13-17.96), preoperative opioid use (OR 7.32, 95% CI 1.88-28.47), psychiatric disorder (OR 3.77, 95% CI 2.3-6.2; P < .001), age >30 years (OR 7.03, 95% CI 3.63-13.61; P < .001), and obesity (OR 2.68, 95% CI 1.40-5.14; P = .002). Compared with Outerbridge 0, a greater percentage of patients with Outerbridge 1 or 2 and 3 or 4 continued using opioids 2 to 12 months after surgery (OR 3.06, 95% CI 1.33-7.02; P = .006 and OR 2.86, 95% CI 1.24-6.59; P = .010, respectively). Conclusions For patients undergoing MPFL reconstruction, preoperative opioid use, cartilage damage, age >30 years, smoking history, body mass index >30, and history of psychiatric disorder were found to be significantly associated with prolonged opioid use after surgery. Postoperative opioid refills in this cohort declined after 1 month. Level of Evidence Level III, retrospective cohort study.

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Machine-learning model successfully predicts patients at risk for prolonged postoperative opioid use following elective knee arthroscopy

Forlenza

Wilbur

et al. 2021

Knee Surg Sports Traumatol Arthrosc

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PurposeRecovery following elective knee arthroscopy can be compromised by prolonged postoperative opioid utilization, yet an effective and validated risk calculator for this outcome remains elusive. The purpose of this study is to develop and validate a machine‐learning algorithm that can reliably and effectively predict prolonged opioid consumption in patients following elective knee arthroscopy. MethodsA retrospective review of an institutional outcome database was performed at a tertiary academic medical centre to identify adult patients who underwent knee arthroscopy between 2016 and 2018. Extended postoperative opioid consumption was defined as opioid consumption at least 150 days following surgery. Five machine‐learning algorithms were assessed for the ability to predict this outcome. Performances of the algorithms were assessed through discrimination, calibration, and decision curve analysis. ResultsOverall, of the 381 patients included, 60 (20.3%) demonstrated sustained postoperative opioid consumption. The factors determined for prediction of prolonged postoperative opioid prescriptions were reduced preoperative scores on the following patient‐reported outcomes: the IKDC, KOOS ADL, VR12 MCS, KOOS pain, and KOOS Sport and Activities. The ensemble model achieved the best performance based on discrimination (AUC = 0.74), calibration, and decision curve analysis. This model was integrated into a web‐based open‐access application able to provide both predictions and explanations. ConclusionFollowing appropriate external validation, the algorithm developed presently could augment timely identification of patients who are at risk of extended opioid use. Reduced scores on preoperative patient‐reported outcomes, symptom duration and perioperative oral morphine equivalents were identified as novel predictors of prolonged postoperative opioid use. The predictive model can be easily deployed in the clinical setting to identify at risk patients thus allowing providers to optimize modifiable risk factors and appropriately counsel patients preoperatively. Level of evidenceIII.

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Preoperative Opioid Usage, Male Sex, and Preexisting Knee Osteoarthritis Impacts Opioid Refills After Isolated Arthroscopic Meniscectomy: A Population-Based Study

Cited by 13 publications

References 29 publications

Editorial Commentary: Postoperative Analgesia After Arthroscopy: A Step Toward the Personalization of Pain Control

Editorial Commentary: Postoperative Analgesia After Arthroscopy: A Step Toward the Personalization of Pain Control

Older, Heavier, Arthritic, Psychiatrically Disordered, and Opioid-Familiar Patients Are at Risk for Opioid Use After Medial Patellofemoral Ligament Reconstruction

Machine-learning model successfully predicts patients at risk for prolonged postoperative opioid use following elective knee arthroscopy

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