{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T10:56:54Z","timestamp":1774004214585,"version":"3.50.1"},"reference-count":48,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,1,16]],"date-time":"2026-01-16T00:00:00Z","timestamp":1768521600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/100014434","name":"Columbia University Medical Center","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100014434","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100004334","name":"Merck","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100004334","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100002575","name":"American College of Obstetricians and Gynecologists","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100002575","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006474","name":"Columbia University","doi-asserted-by":"publisher","award":["KL2TR001874"],"award-info":[{"award-number":["KL2TR001874"]}],"id":[{"id":"10.13039\/100006474","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","surgopensci.org","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Surgery Open Science"],"published-print":{"date-parts":[[2026,3]]},"DOI":"10.1016\/j.sopen.2026.01.005","type":"journal-article","created":{"date-parts":[[2026,1,20]],"date-time":"2026-01-20T00:26:19Z","timestamp":1768868779000},"page":"14-22","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Development of prediction models for perioperative opioid needs in laparoscopic cholecystectomy patients: A machine-learning approach"],"prefix":"10.1016","volume":"30","author":[{"given":"Yongmei","family":"Huang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guohua","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Silvia S.","family":"Martins","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pia M.","family":"Mauro","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ana I.","family":"Tergas","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"June","family":"Hou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiao","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Elena B.","family":"Elkin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Judith S.","family":"Jacobson","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jason D.","family":"Wright","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"issue":"6","key":"10.1016\/j.sopen.2026.01.005_bb0005","doi-asserted-by":"crossref","DOI":"10.1001\/jamasurg.2017.0504","article-title":"New persistent opioid use after minor and major surgical procedures in US Adults","volume":"152","author":"Brummett","year":"2017","journal-title":"JAMA Surg"},{"issue":"4","key":"10.1016\/j.sopen.2026.01.005_bb0010","doi-asserted-by":"crossref","first-page":"743","DOI":"10.1097\/SLA.0000000000003549","article-title":"Postsurgical opioid prescriptions and risk of long-term use: an Observational Cohort Study Across the United States","volume":"273","author":"Young","year":"2021","journal-title":"Ann Surg"},{"issue":"6","key":"10.1016\/j.sopen.2026.01.005_bb0015","doi-asserted-by":"crossref","DOI":"10.1001\/jamanetworkopen.2020.7367","article-title":"Rate and risk factors associated with prolonged opioid use after surgery: a systematic review and meta-analysis","volume":"3","author":"Lawal","year":"2020","journal-title":"JAMA Netw Open"},{"issue":"6","key":"10.1016\/j.sopen.2026.01.005_bb0020","doi-asserted-by":"crossref","first-page":"1056","DOI":"10.1097\/SLA.0000000000002591","article-title":"Opioid use after discharge in postoperative patients: a systematic review","volume":"267","author":"Feinberg","year":"2018","journal-title":"Ann Surg"},{"issue":"1","key":"10.1016\/j.sopen.2026.01.005_bb0025","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1186\/s13643-020-01393-8","article-title":"Leftover opioids following adult surgical procedures: a systematic review and meta-analysis","volume":"9","author":"Schirle","year":"2020","journal-title":"Syst Rev"},{"issue":"4","key":"10.1016\/j.sopen.2026.01.005_bb0030","doi-asserted-by":"crossref","first-page":"557","DOI":"10.1016\/j.jopan.2021.10.017","article-title":"Compliance with opioid disposal following opioid disposal education in surgical patients: a systematic review","volume":"37","author":"Dollar","year":"2022","journal-title":"J Perianesth Nurs"},{"issue":"7","key":"10.1016\/j.sopen.2026.01.005_bb0035","doi-asserted-by":"crossref","first-page":"823","DOI":"10.1016\/j.jmig.2022.04.017","article-title":"Postoperative discharge opioid consumption, leftover, and disposal after obstetric and gynecologic procedures: a systematic review","volume":"29","author":"Raina","year":"2022","journal-title":"J Minim Invasive Gynecol"},{"issue":"15","key":"10.1016\/j.sopen.2026.01.005_bb0040","doi-asserted-by":"crossref","first-page":"1624","DOI":"10.1001\/jama.2016.1464","article-title":"CDC guideline for prescribing opioids for chronic pain--United States, 2016","volume":"315","author":"Dowell","year":"2016","journal-title":"JAMA"},{"issue":"11","key":"10.1016\/j.sopen.2026.01.005_bb0045","doi-asserted-by":"crossref","first-page":"1658","DOI":"10.1001\/jamaoncol.2022.3744","article-title":"Changes in opioid prescriptions and potential misuse and substance use disorders among childhood cancer survivors following the 2016 opioid prescribing guideline","volume":"8","author":"Hu","year":"2022","journal-title":"JAMA Oncol"},{"key":"10.1016\/j.sopen.2026.01.005_bb0050","author":"CDC"},{"key":"10.1016\/j.sopen.2026.01.005_bb0055","author":"Whitehead"},{"issue":"1","key":"10.1016\/j.sopen.2026.01.005_bb0060","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1037\/ser0000099","article-title":"Development and applications of the Veterans Health Administration's Stratification Tool for Opioid Risk Mitigation (STORM) to improve opioid safety and prevent overdose and suicide","volume":"14","author":"Oliva","year":"2017","journal-title":"Psychol Serv"},{"issue":"3","key":"10.1016\/j.sopen.2026.01.005_bb0065","doi-asserted-by":"crossref","DOI":"10.1001\/jamanetworkopen.2019.0968","article-title":"Evaluation of machine-learning algorithms for predicting opioid overdose risk among medicare beneficiaries with opioid prescriptions","volume":"2","author":"Lo-Ciganic","year":"2019","journal-title":"JAMA Netw Open"},{"issue":"10","key":"10.1016\/j.sopen.2026.01.005_bb0070","doi-asserted-by":"crossref","first-page":"2219","DOI":"10.1093\/pm\/pnaa026","article-title":"Independent validation in a large privately insured population of the risk index for serious prescription opioid-induced respiratory depression or overdose","volume":"21","author":"Metcalfe","year":"2020","journal-title":"Pain Med"},{"issue":"8","key":"10.1016\/j.sopen.2026.01.005_bb0075","doi-asserted-by":"crossref","first-page":"1184","DOI":"10.1016\/j.spinee.2020.05.098","article-title":"A predictive-modeling based screening tool for prolonged opioid use after surgical management of low back and lower extremity pain","volume":"20","author":"Zhang","year":"2020","journal-title":"Spine J"},{"issue":"5","key":"10.1016\/j.sopen.2026.01.005_bb0080","article-title":"Machine learning algorithms predict prolonged opioid use in opioid-naive primary hip arthroscopy patients","volume":"5","author":"Kunze","year":"2021","journal-title":"J Am Acad Orthop Surg Glob Res Rev"},{"issue":"12","key":"10.1016\/j.sopen.2026.01.005_bb0085","doi-asserted-by":"crossref","first-page":"1051","DOI":"10.1097\/MLR.0000000000001651","article-title":"A risk prediction model for long-term prescription opioid use","volume":"59","author":"Tseregounis","year":"2021","journal-title":"Med Care"},{"issue":"8","key":"10.1016\/j.sopen.2026.01.005_bb0090","doi-asserted-by":"crossref","first-page":"1566","DOI":"10.1111\/pme.12777","article-title":"Development of a risk index for serious prescription opioid-induced respiratory depression or overdose in veterans\u2019 health administration patients","volume":"16","author":"Zedler","year":"2015","journal-title":"Pain Med"},{"key":"10.1016\/j.sopen.2026.01.005_bb0095","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1016\/j.trsl.2021.03.012","article-title":"Assessing opioid overdose risk: a review of clinical prediction models utilizing patient-level data","volume":"234","author":"Tseregounis","year":"2021","journal-title":"Transl Res"},{"issue":"7","key":"10.1016\/j.sopen.2026.01.005_bb0100","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0236833","article-title":"Machine learning approach to predict postoperative opioid requirements in ambulatory surgery patients","volume":"15","author":"Nair","year":"2020","journal-title":"PloS One"},{"issue":"7","key":"10.1016\/j.sopen.2026.01.005_bb0105","doi-asserted-by":"crossref","DOI":"10.1001\/jamanetworkopen.2022.22973","article-title":"Development and validation of a model for opioid prescribing following gynecological surgery","volume":"5","author":"Rodriguez","year":"2022","journal-title":"JAMA Netw Open"},{"issue":"3","key":"10.1016\/j.sopen.2026.01.005_bb0110","doi-asserted-by":"crossref","first-page":"259 e1","DOI":"10.1016\/j.ajog.2018.10.022","article-title":"Opioid use after laparoscopic hysterectomy: prescriptions, patient use, and a predictive calculator","volume":"220","author":"Wong","year":"2019","journal-title":"Am J Obstet Gynecol"},{"issue":"2","key":"10.1016\/j.sopen.2026.01.005_bb0115","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1016\/j.surg.2024.03.054","article-title":"Deep learning predicts postoperative opioids refills in a multi-institutional cohort of surgical patients","volume":"176","author":"Salehinejad","year":"2024","journal-title":"Surgery"},{"key":"10.1016\/j.sopen.2026.01.005_bb0120","first-page":"81","article-title":"Laparoscopic cholecystectomy: past, present, and future","volume":"15","author":"Osborne","year":"2006","journal-title":"Surg Technol Int"},{"issue":"11","key":"10.1016\/j.sopen.2026.01.005_bb0125","doi-asserted-by":"crossref","first-page":"1275","DOI":"10.17219\/acem\/151995","article-title":"Pharmacotherapeutic pain management in patients undergoing laparoscopic cholecystectomy: a review","volume":"31","author":"Jiang","year":"2022","journal-title":"Adv Clin Exp Med"},{"issue":"6","key":"10.1016\/j.sopen.2026.01.005_bb0130","doi-asserted-by":"crossref","DOI":"10.1001\/jamanetworkopen.2024.17651","article-title":"Epidemiology of opioid prescribing after discharge from surgical procedures among adults","volume":"7","author":"Alessio-Bilowus","year":"2024","journal-title":"JAMA Netw Open"},{"key":"10.1016\/j.sopen.2026.01.005_bb0135","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1016\/j.jss.2023.06.056","article-title":"Opioid prescribing variation after laparoscopic cholecystectomy in the US Military Health System","volume":"297","author":"Cronin","year":"2024","journal-title":"J Surg Res"},{"key":"10.1016\/j.sopen.2026.01.005_bb0140","author":"Agency"},{"issue":"3","key":"10.1016\/j.sopen.2026.01.005_bb0145","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1001\/jamasurg.2017.4436","article-title":"Reduction in opioid prescribing through evidence-based prescribing guidelines","volume":"153","author":"Howard","year":"2018","journal-title":"JAMA Surg"},{"issue":"6","key":"10.1016\/j.sopen.2026.01.005_bb0155","doi-asserted-by":"crossref","DOI":"10.1001\/jamanetworkopen.2021.11826","article-title":"Association of the 2016 US Centers for Disease Control and Prevention opioid prescribing guideline with changes in opioid dispensing after surgery","volume":"4","author":"Sutherland","year":"2021","journal-title":"JAMA Netw Open"},{"issue":"1","key":"10.1016\/j.sopen.2026.01.005_bb0165","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1097\/j.pain.0000000000003023","article-title":"Development and internal validation of a prediction model for long-term opioid use-an analysis of insurance claims data","volume":"165","author":"Held","year":"2024","journal-title":"Pain"},{"key":"10.1016\/j.sopen.2026.01.005_bb0170","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/j.mbs.2018.06.004","article-title":"The Bayesian adaptive lasso regression","volume":"303","author":"Alhamzawi","year":"2018","journal-title":"Math Biosci"},{"issue":"14","key":"10.1016\/j.sopen.2026.01.005_bb0175","doi-asserted-by":"crossref","first-page":"1377","DOI":"10.1001\/jama.2017.12126","article-title":"Discrimination and calibration of clinical prediction models: users' guides to the medical literature","volume":"318","author":"Alba","year":"2017","journal-title":"JAMA"},{"issue":"2","key":"10.1016\/j.sopen.2026.01.005_bb0180","first-page":"16","article-title":"A simple generalisation of the area under the ROC curve for multiple class classification problems","volume":"45","author":"R.J., H.D.J.a.T","year":"2001","journal-title":"Machine Learning"},{"issue":"15","key":"10.1016\/j.sopen.2026.01.005_bb0185","doi-asserted-by":"crossref","first-page":"2585","DOI":"10.1002\/sim.6114","article-title":"Assessing calibration of multinomial risk prediction models","volume":"33","author":"Van Hoorde","year":"2014","journal-title":"Stat Med"},{"issue":"9","key":"10.1016\/j.sopen.2026.01.005_bb0190","doi-asserted-by":"crossref","first-page":"1601","DOI":"10.1002\/sim.8063","article-title":"Sample size considerations and predictive performance of multinomial logistic prediction models","volume":"38","author":"de Jong","year":"2019","journal-title":"Stat Med"},{"key":"10.1016\/j.sopen.2026.01.005_bb0195","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1016\/j.jclinepi.2015.10.016","article-title":"A nomogram was developed to enhance the use of multinomial logistic regression modeling in diagnostic research","volume":"71","author":"Bertens","year":"2016","journal-title":"J Clin Epidemiol"},{"key":"10.1016\/j.sopen.2026.01.005_bb0200","author":"Dalton, D.Y.a.J.E"},{"key":"10.1016\/j.sopen.2026.01.005_bb0205","doi-asserted-by":"crossref","DOI":"10.1136\/bmj.g7594","article-title":"Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement","volume":"350","author":"Collins","year":"2015","journal-title":"BMJ"},{"issue":"1","key":"10.1016\/j.sopen.2026.01.005_bb0210","doi-asserted-by":"crossref","first-page":"W1","DOI":"10.7326\/M14-0698","article-title":"Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): explanation and elaboration","volume":"162","author":"Moons","year":"2015","journal-title":"Ann Intern Med"},{"issue":"12","key":"10.1016\/j.sopen.2026.01.005_bb0215","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0294930","article-title":"Diagnostic accuracy of endocytoscopy via artificial intelligence in colorectal lesions: a systematic review and meta-analysis","volume":"18","author":"Zhang","year":"2023","journal-title":"PloS One"},{"key":"10.1016\/j.sopen.2026.01.005_bb0220","author":"Huang"},{"issue":"4","key":"10.1016\/j.sopen.2026.01.005_bb0225","doi-asserted-by":"crossref","DOI":"10.1007\/s11948-021-00319-4","article-title":"Ethics-based auditing of automated decision-making systems: nature, scope, and limitations","volume":"27","author":"M\u00f6kander","year":"2021","journal-title":"Sci Eng Ethics"},{"issue":"6","key":"10.1016\/j.sopen.2026.01.005_bb0230","doi-asserted-by":"crossref","first-page":"719","DOI":"10.1038\/s41551-023-01056-8","article-title":"Algorithmic fairness in artificial intelligence for medicine and healthcare","volume":"7","author":"Chen","year":"2023","journal-title":"Nat Biomed Eng"},{"issue":"8","key":"10.1016\/j.sopen.2026.01.005_bb0235","doi-asserted-by":"crossref","first-page":"1364","DOI":"10.1200\/JCO.2007.12.9791","article-title":"How to build and interpret a nomogram for cancer prognosis","volume":"26","author":"Iasonos","year":"2008","journal-title":"J Clin Oncol"},{"issue":"2","key":"10.1016\/j.sopen.2026.01.005_bb0240","doi-asserted-by":"crossref","first-page":"823","DOI":"10.1177\/0962280214560045","article-title":"Widen NomoGram for multinomial logistic regression: an application to staging liver fibrosis in chronic hepatitis C patients","volume":"26","author":"Ardoino","year":"2017","journal-title":"Stat Methods Med Res"},{"key":"10.1016\/j.sopen.2026.01.005_bb0245","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1186\/s41512-017-0010-5","article-title":"A generic nomogram for multinomial prediction models: theory and guidance for construction","volume":"1","author":"van Smeden","year":"2017","journal-title":"Diagn Progn Res"},{"issue":"4","key":"10.1016\/j.sopen.2026.01.005_bb0250","doi-asserted-by":"crossref","first-page":"1134","DOI":"10.1038\/s41591-024-02855-5","article-title":"Adapted large language models can outperform medical experts in clinical text summarization","volume":"30","author":"Van Veen","year":"2024","journal-title":"Nat Med"}],"container-title":["Surgery Open Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2589845026000060?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2589845026000060?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T08:41:34Z","timestamp":1773996094000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S2589845026000060"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3]]},"references-count":48,"alternative-id":["S2589845026000060"],"URL":"https:\/\/doi.org\/10.1016\/j.sopen.2026.01.005","relation":{},"ISSN":["2589-8450"],"issn-type":[{"value":"2589-8450","type":"print"}],"subject":[],"published":{"date-parts":[[2026,3]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Development of prediction models for perioperative opioid needs in laparoscopic cholecystectomy patients: A machine-learning approach","name":"articletitle","label":"Article Title"},{"value":"Surgery Open Science","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.sopen.2026.01.005","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Authors. Published by Elsevier Inc.","name":"copyright","label":"Copyright"}]}}