{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,17]],"date-time":"2026-10-17T06:49:22Z","timestamp":1792219762988,"version":"4.4.0"},"reference-count":31,"publisher":"Wiley","issue":"9","license":[{"start":{"date-parts":[[2020,10,12]],"date-time":"2020-10-12T00:00:00Z","timestamp":1602460800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2020,10,12]],"date-time":"2020-10-12T00:00:00Z","timestamp":1602460800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,10,12]],"date-time":"2020-10-12T00:00:00Z","timestamp":1602460800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Knee surg. sports traumatol. arthrosc."],"published-print":{"date-parts":[[2021,9]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Purpose<\/jats:title><jats:p>Overnight admission following anterior cruciate ligament reconstruction has implications on clinical outcomes as well as cost benefit, yet there are few validated risk calculators for reliable identification of appropriate candidates. The purpose of this study is to develop and validate a machine learning algorithm that can effectively identify patients requiring admission following elective anterior cruciate ligament (ACL) reconstruction.\n<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>A retrospective review of a national surgical outcomes database was performed to identify patients who underwent elective ACL reconstruction from 2006 to 2018. Patients admitted overnight postoperatively were identified as those with length of stay of 1 or more days. Models were generated using random forest (RF), extreme gradient boosting (XGBoost), linear discriminant classifier (LDA), and adaptive boosting algorithms (AdaBoost), and an additional model was produced as a weighted ensemble of the four final algorithms.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Overall, of the 4,709 patients included, 531 patients (11.3%) required at least one overnight stay following ACL reconstruction. The factors determined most important for identification of candidates for inpatient admission were operative time, anesthesia type, age, gender, and BMI. Smoking history, history of COPD, and history of coagulopathy were identified as less important variables. The following factors supported overnight admission: operative time\u2009&gt;\u2009200\u00a0min, age\u2009&lt;\u200935.8 or\u2009&gt;\u200953.5 years, male gender, BMI\u2009&lt;\u200925 or\u2009&gt;\u200931.2\u00a0kg\/m<jats:sup>2<\/jats:sup>, positive smoking history, history of COPD and the presence of preoperative coagulopathy. The ensemble model achieved the best performance based on discrimination assessed via internal validation (AUC\u2009=\u20090.76), calibration, and decision curve analysis. The model was integrated into a web\u2010based open\u2010access application able to provide both predictions and explanations.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>Modifiable risk factors identified by the model such as increased BMI, operative time, anesthesia type, and comorbidities can help clinicians optimize preoperative status to prevent costs associated with unnecessary admissions. If externally validated in independent populations, this algorithm could use these inputs to guide preoperative screening and risk stratification to identify patients requiring overnight admission for observation following ACL reconstruction.<\/jats:p><\/jats:sec><jats:sec><jats:title>Level of evidence<\/jats:title><jats:p>IV.<\/jats:p><\/jats:sec>","DOI":"10.1007\/s00167-020-06321-w","type":"journal-article","created":{"date-parts":[[2020,10,12]],"date-time":"2020-10-12T13:03:24Z","timestamp":1602507804000},"page":"2958-2966","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["Machine learning can reliably identify patients at risk of overnight hospital admission following anterior cruciate ligament reconstruction"],"prefix":"10.1002","volume":"29","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3967-645X","authenticated-orcid":false,"given":"Yining","family":"Lu","sequence":"first","affiliation":[{"name":"<!--<label>1<\/label>--> Department of Orthopaedic Surgery Mayo Clinic Rochester MN USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Enrico","family":"Forlenza","sequence":"additional","affiliation":[{"name":"<!--<label>2<\/label>--> Department of Orthopaedic Surgery Rush University Medical Center Chicago IL USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matthew R.","family":"Cohn","sequence":"additional","affiliation":[{"name":"<!--<label>2<\/label>--> Department of Orthopaedic Surgery Rush University Medical Center Chicago IL USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ophelie","family":"Lavoie\u2010Gagne","sequence":"additional","affiliation":[{"name":"<!--<label>2<\/label>--> Department of Orthopaedic Surgery Rush University Medical Center Chicago IL USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ryan R.","family":"Wilbur","sequence":"additional","affiliation":[{"name":"<!--<label>1<\/label>--> Department of Orthopaedic Surgery Mayo Clinic Rochester MN USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bryant M.","family":"Song","sequence":"additional","affiliation":[{"name":"<!--<label>1<\/label>--> Department of Orthopaedic Surgery Mayo Clinic Rochester MN USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aaron J.","family":"Krych","sequence":"additional","affiliation":[{"name":"<!--<label>1<\/label>--> Department of Orthopaedic Surgery Mayo Clinic Rochester MN USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Brian","family":"Forsythe","sequence":"additional","affiliation":[{"name":"<!--<label>2<\/label>--> Department of Orthopaedic Surgery Rush University Medical Center Chicago IL 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July 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 October 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 October 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"A.J.K. reports personal fees from Aesculap\/B.Braun: research support; American Journal of Sports Medicine: editorial or governing board; Arthrex, Inc: IP royalties, paid consultant research support; Arthritis Foundation: research support; Ceterix: research support; Histogenics: research support; International Cartilage Repair Society: board or committee member; International Society of Arthroscopy, Knee Surgery, and Orthopaedic Sports Medicine: board or committee member; JRF Ortho: paid consultant; Minnesota Orthopedic Society: board or committee member; Musculoskeletal Transplantation Foundation: board or committee member; Vericel: paid consultant, outside the submitted work. B.F. reports research support from Arthrex and Stryker; educational support from Medwest, Smith and Nephew, and Ossur; consulting fees from Arthrex, DJO, Smith and Nephew, Ossur, Sonoma Orthopedics, and Stryker; speaking fees from Arthrex; honoraria from Arthrosurface; and royalties from Elsevier and Arthrex; and has stock options in Jace Medical.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}