{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T17:52:37Z","timestamp":1792000357213,"version":"4.4.0"},"reference-count":33,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T00:00:00Z","timestamp":1672185600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T00:00:00Z","timestamp":1672185600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"},{"start":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T00:00:00Z","timestamp":1672185600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T00:00:00Z","timestamp":1672185600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"}],"content-domain":{"domain":["arthroscopyjournal.org","clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Arthroscopy"],"published-print":{"date-parts":[[2023,6]]},"abstract":"<jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>To develop a predictive machine learning model to identify prognostic factors for continued opioid prescriptions after arthroscopic meniscus surgery.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>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\u2010Regression model. We then created a na\u00efve Bayesian model, a machine learning classifier that uses Bayes\u2019 theorem with an assumption of independence between variables.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>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 na\u00efve 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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Level of Evidence<\/jats:title>\n                    <jats:p>III, retrospective comparative study.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1016\/j.arthro.2022.12.025","type":"journal-article","created":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T20:11:44Z","timestamp":1672258304000},"page":"1505-1511","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":15,"title":["Machine Learning Model Identifies Preoperative Opioid Use, Male Sex, and Elevated Body Mass Index as Predictive Factors for Prolonged Opioid Consumption Following Arthroscopic Meniscal Surgery"],"prefix":"10.1002","volume":"39","author":[{"given":"Joshua P.","family":"Castle","sequence":"first","affiliation":[{"name":"Henry Ford Hospital Department of Orthopaedic Surgery Detroit Michigan U.S.A."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Toufic R.","family":"Jildeh","sequence":"additional","affiliation":[{"name":"The Steadman Clinic Vail Colorado U.S.A."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Farhan","family":"Chaudhry","sequence":"additional","affiliation":[{"name":"Detroit Medical Center Department of General Surgery Detroit Michigan U.S.A."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Elizabeth H.G.","family":"Turner","sequence":"additional","affiliation":[{"name":"Henry Ford Hospital Department of Orthopaedic Surgery Detroit Michigan U.S.A."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Muhammad J.","family":"Abbas","sequence":"additional","affiliation":[{"name":"Henry Ford Hospital Department of Orthopaedic Surgery Detroit Michigan U.S.A."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ossama","family":"Mahmoud","sequence":"additional","affiliation":[{"name":"Wayne State University School of Medicine Detroit Michigan U.S.A."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Meredith","family":"Hengy","sequence":"additional","affiliation":[{"name":"Wayne State University School of Medicine Detroit Michigan U.S.A."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kelechi R.","family":"Okoroha","sequence":"additional","affiliation":[{"name":"Mayo Clinic Department of Orthopedic Surgery Minneapolis Minnesota U.S.A."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"T. Sean","family":"Lynch","sequence":"additional","affiliation":[{"name":"Henry Ford Hospital Department of Orthopaedic Surgery Detroit Michigan U.S.A."}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2022,12,28]]},"reference":[{"key":"e_1_2_5_2_2","doi-asserted-by":"publisher","DOI":"10.1177\/0363546513495641"},{"key":"e_1_2_5_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.pmrj.2018.08.384"},{"key":"e_1_2_5_4_2","doi-asserted-by":"publisher","DOI":"10.1007\/s002640000204"},{"key":"e_1_2_5_5_2","doi-asserted-by":"publisher","DOI":"10.1891\/1078-4535.18.3.118"},{"key":"e_1_2_5_6_2","article-title":"Impact of pain on patient satisfaction integration process: How patients with pain combine their health care attribute reactions","volume":"2","author":"Otani K.","year":"2015","journal-title":"Health Serv Res Manag 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