{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T04:20:36Z","timestamp":1783657236823,"version":"3.55.0"},"reference-count":76,"publisher":"Elsevier BV","issue":"2","license":[{"start":{"date-parts":[[2025,8,1]],"date-time":"2025-08-01T00:00:00Z","timestamp":1754006400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,8,1]],"date-time":"2025-08-01T00:00:00Z","timestamp":1754006400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T00:00:00Z","timestamp":1742947200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000226","name":"Ontario Ministry of Health","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000226","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000241","name":"Physicians' Services Inc Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000241","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003579","name":"University of Toronto","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003579","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000024","name":"Canadian Institutes of Health Research","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000024","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","jvascsurg.org","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Journal of Vascular Surgery"],"published-print":{"date-parts":[[2025,8]]},"DOI":"10.1016\/j.jvs.2025.03.198","type":"journal-article","created":{"date-parts":[[2025,6,4]],"date-time":"2025-06-04T06:40:01Z","timestamp":1749019201000},"page":"617-631.e8","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":6,"title":["Predicting mortality risk following major lower extremity amputation using machine learning"],"prefix":"10.1016","volume":"82","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7191-1034","authenticated-orcid":false,"given":"Ben","family":"Li","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Naomi","family":"Eisenberg","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Derek","family":"Beaton","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Douglas S.","family":"Lee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Leen","family":"Al-Omran","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Duminda N.","family":"Wijeysundera","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohamad A.","family":"Hussain","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ori D.","family":"Rotstein","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Charles","family":"de Mestral","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Muhammad","family":"Mamdani","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Graham","family":"Roche-Nagle","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohammed","family":"Al-Omran","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.jvs.2025.03.198_bib1","series-title":"StatPearls [Internet]","article-title":"Peripheral arterial disease","author":"Zemaitis","year":"2023"},{"key":"10.1016\/j.jvs.2025.03.198_bib2","doi-asserted-by":"crossref","first-page":"678","DOI":"10.4065\/mcp.2010.0133","article-title":"Peripheral artery disease: current insight into the disease and its diagnosis and management","volume":"85","author":"Olin","year":"2010","journal-title":"Mayo Clin Proc"},{"key":"10.1016\/j.jvs.2025.03.198_bib3","article-title":"Major lower limb amputations: recognizing pitfalls","volume":"13","author":"Pran","year":"2021","journal-title":"Cureus"},{"key":"10.1016\/j.jvs.2025.03.198_bib4","doi-asserted-by":"crossref","first-page":"1985","DOI":"10.2147\/CIA.S137570","article-title":"Mortality after major amputation in elderly patients with critical limb ischemia","volume":"12","author":"Klaphake","year":"2017","journal-title":"Clin Interv Aging"},{"key":"10.1016\/j.jvs.2025.03.198_bib5","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1053\/ejvs.1999.1052","article-title":"Non-operative treatment of advanced limb ischaemia: the decision for palliative care","volume":"19","author":"Campbell","year":"2000","journal-title":"Eur J Vasc Endovasc Surg"},{"key":"10.1016\/j.jvs.2025.03.198_bib6","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1002\/bjs.11367","article-title":"End-of-life care following leg amputation in patients with peripheral artery disease or diabetes","volume":"107","author":"de Mestral","year":"2020","journal-title":"Br J Surg"},{"key":"10.1016\/j.jvs.2025.03.198_bib7","doi-asserted-by":"crossref","first-page":"1411","DOI":"10.1016\/j.jvs.2016.04.045","article-title":"The vascular quality initiative cardiac risk index for prediction of myocardial infarction after vascular surgery","volume":"64","author":"Bertges","year":"2016","journal-title":"J Vasc Surg"},{"key":"10.1016\/j.jvs.2025.03.198_bib8","doi-asserted-by":"crossref","first-page":"833","DOI":"10.1016\/j.jamcollsurg.2013.07.385","article-title":"Development and evaluation of the Universal ACS NSQIP surgical risk calculator: a decision aid and informed consent tool for patients and surgeons","volume":"217","author":"Bilimoria","year":"2013","journal-title":"J Am Coll Surg"},{"key":"10.1016\/j.jvs.2025.03.198_bib9","doi-asserted-by":"crossref","DOI":"10.1136\/bmjhci-2020-100253","article-title":"Adoption of clinical risk prediction tools is limited by a lack of integration with electronic health records","volume":"28","author":"Sharma","year":"2021","journal-title":"BMJ Health Care Inform"},{"key":"10.1016\/j.jvs.2025.03.198_bib10","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1002\/bjs5.50233","article-title":"Systematic review and narrative synthesis of surgeons\u2019 perception of postoperative outcomes and risk","volume":"4","author":"Dilaver","year":"2020","journal-title":"BJS Open"},{"key":"10.1016\/j.jvs.2025.03.198_bib11","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1007\/978-1-62703-748-8_7","article-title":"Introduction to machine learning","volume":"1107","author":"Ba\u015ftanlar","year":"2014","journal-title":"Methods Mol Biol"},{"key":"10.1016\/j.jvs.2025.03.198_bib12","doi-asserted-by":"crossref","first-page":"e262","DOI":"10.1016\/S1470-2045(19)30149-4","article-title":"Big data and machine learning algorithms for health-care delivery","volume":"20","author":"Ngiam","year":"2019","journal-title":"Lancet Oncol"},{"key":"10.1016\/j.jvs.2025.03.198_bib13","doi-asserted-by":"crossref","first-page":"2082","DOI":"10.1007\/s00586-022-07188-w","article-title":"Machine learning versus logistic regression for prognostic modelling in individuals with non-specific neck pain","volume":"31","author":"Liew","year":"2022","journal-title":"Eur Spine J"},{"key":"10.1016\/j.jvs.2025.03.198_bib14","doi-asserted-by":"crossref","first-page":"e471","DOI":"10.1016\/S2589-7500(21)00084-4","article-title":"Assessing the utility of deep neural networks in predicting postoperative surgical complications: a retrospective study","volume":"3","author":"Bonde","year":"2021","journal-title":"Lancet Digit Health"},{"key":"10.1016\/j.jvs.2025.03.198_bib15","unstructured":"Society for Vascular Surgery Vascular Quality Initiative (VQI) [Internet]. Accessed June 16, 2023. https:\/\/www.vqi.org\/"},{"key":"10.1016\/j.jvs.2025.03.198_bib16","doi-asserted-by":"crossref","first-page":"593","DOI":"10.1016\/j.jvs.2023.09.037","article-title":"Using machine learning to predict outcomes following suprainguinal bypass","volume":"79","author":"Li","year":"2024","journal-title":"J Vasc Surg"},{"key":"10.1016\/j.jvs.2025.03.198_bib17","doi-asserted-by":"crossref","first-page":"705","DOI":"10.1097\/SLA.0000000000006181","article-title":"Using machine learning (XGBoost) to predict outcomes after infrainguinal bypass for peripheral artery disease","volume":"279","author":"Li","year":"2024","journal-title":"Ann Surg"},{"key":"10.1016\/j.jvs.2025.03.198_bib18","doi-asserted-by":"crossref","DOI":"10.1001\/jamanetworkopen.2024.2350","article-title":"Machine learning to predict outcomes of endovascular intervention for patients with PAD","volume":"7","author":"Li","year":"2024","journal-title":"JAMA Netw Open"},{"key":"10.1016\/j.jvs.2025.03.198_bib19","doi-asserted-by":"crossref","first-page":"2191","DOI":"10.1001\/jama.2013.281053","article-title":"World Medical Association Declaration of Helsinki: ethical principles for medical research involving human subjects","volume":"310","year":"2013","journal-title":"JAMA"},{"key":"10.1016\/j.jvs.2025.03.198_bib20","doi-asserted-by":"crossref","DOI":"10.1136\/bmj-2023-078378","article-title":"TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods","volume":"385","author":"Collins","year":"2024","journal-title":"BMJ"},{"key":"10.1016\/j.jvs.2025.03.198_bib22","doi-asserted-by":"crossref","first-page":"1529","DOI":"10.1016\/j.jvs.2012.03.016","article-title":"The Society for Vascular Surgery Vascular Quality Initiative","volume":"55","author":"Cronenwett","year":"2012","journal-title":"J Vasc Surg"},{"key":"10.1016\/j.jvs.2025.03.198_bib23","first-page":"6","article-title":"Validation of the Social Security Death Index (SSDI): an important readily-available outcomes database for researchers","volume":"9","author":"Quinn","year":"2008","journal-title":"West J Emerg Med"},{"key":"10.1016\/j.jvs.2025.03.198_bib24","doi-asserted-by":"crossref","first-page":"591","DOI":"10.1053\/j.jfas.2016.01.012","article-title":"Mortality after nontraumatic major amputation among patients with diabetes and peripheral vascular disease: a systematic review","volume":"55","author":"Thorud","year":"2016","journal-title":"J Foot Ankle Surg"},{"key":"10.1016\/j.jvs.2025.03.198_bib25","doi-asserted-by":"crossref","first-page":"346","DOI":"10.1016\/j.jss.2021.02.045","article-title":"Machine learning and surgical outcomes prediction: a systematic review","volume":"264","author":"Elfanagely","year":"2021","journal-title":"J Surg Res"},{"key":"10.1016\/j.jvs.2025.03.198_bib26","doi-asserted-by":"crossref","first-page":"3100","DOI":"10.1007\/s00268-022-06728-1","article-title":"Machine learning algorithms for predicting surgical outcomes after Colorectal surgery: a systematic review","volume":"46","author":"Bekta\u015f","year":"2022","journal-title":"World J Surg"},{"key":"10.1016\/j.jvs.2025.03.198_bib27","doi-asserted-by":"crossref","first-page":"476","DOI":"10.1016\/j.wneu.2017.09.149","article-title":"Machine learning and neurosurgical outcome prediction: a systematic review","volume":"109","author":"Senders","year":"2018","journal-title":"World Neurosurg"},{"key":"10.1016\/j.jvs.2025.03.198_bib28","doi-asserted-by":"crossref","first-page":"31","DOI":"10.17849\/insm-47-01-31-39.1","article-title":"Random forest","volume":"47","author":"Rigatti","year":"2017","journal-title":"J Insur Med"},{"key":"10.1016\/j.jvs.2025.03.198_bib29","doi-asserted-by":"crossref","first-page":"241","DOI":"10.21037\/atm.2016.03.38","article-title":"Na\u00efve Bayes classification in R","volume":"4","author":"Zhang","year":"2016","journal-title":"Ann Transl Med"},{"key":"10.1016\/j.jvs.2025.03.198_bib30","doi-asserted-by":"crossref","first-page":"1565","DOI":"10.1038\/nbt1206-1565","article-title":"What is a support vector machine?","volume":"24","author":"Noble","year":"2006","journal-title":"Nat Biotechnol"},{"key":"10.1016\/j.jvs.2025.03.198_bib31","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/j.neunet.2014.09.003","article-title":"Deep learning in neural networks: an overview","volume":"61","author":"Schmidhuber","year":"2015","journal-title":"Neural Netw"},{"key":"10.1016\/j.jvs.2025.03.198_bib32","doi-asserted-by":"crossref","first-page":"12","DOI":"10.11613\/BM.2014.003","article-title":"Understanding logistic regression analysis","volume":"24","author":"Sperandei","year":"2014","journal-title":"Biochem Med"},{"issue":"Suppl 4","key":"10.1016\/j.jvs.2025.03.198_bib33","doi-asserted-by":"crossref","first-page":"S574","DOI":"10.21037\/jtd.2019.01.25","article-title":"Developing prediction models for clinical use using logistic regression: an overview","volume":"11","author":"Shipe","year":"2019","journal-title":"J Thorac Dis"},{"key":"10.1016\/j.jvs.2025.03.198_bib34","series-title":"Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and data mining [Internet]","first-page":"785","article-title":"XGBoost: a scalable tree boosting system","author":"Chen","year":"2016"},{"key":"10.1016\/j.jvs.2025.03.198_bib35","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1080\/10485252.2015.1010532","article-title":"A K-fold Averaging cross-validation procedure","volume":"27","author":"Jung","year":"2015","journal-title":"J Nonparametric Stat"},{"key":"10.1016\/j.jvs.2025.03.198_bib36","doi-asserted-by":"crossref","DOI":"10.7717\/peerj-cs.803","article-title":"Utilizing grid search cross-validation with adaptive boosting for augmenting performance of machine learning models","volume":"8","author":"Adnan","year":"2022","journal-title":"PeerJ Comput Sci"},{"key":"10.1016\/j.jvs.2025.03.198_bib37","doi-asserted-by":"crossref","first-page":"7830","DOI":"10.1016\/j.jksuci.2021.09.021","article-title":"Pruning-based oversampling technique with smoothed bootstrap resampling for imbalanced clinical dataset of Covid-19","volume":"34","author":"Wibowo","year":"2022","journal-title":"J King Saud Univ Comput Inf Sci"},{"key":"10.1016\/j.jvs.2025.03.198_bib38","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1055\/s-0038-1677001","article-title":"Predicting and preventing postoperative outcomes","volume":"32","author":"Lee","year":"2019","journal-title":"Clin Colon Rectal Surg"},{"key":"10.1016\/j.jvs.2025.03.198_bib39","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0204161","article-title":"Preoperative and postoperative prediction of long-term meningioma outcomes","volume":"13","author":"Gennatas","year":"2018","journal-title":"PLoS One"},{"key":"10.1016\/j.jvs.2025.03.198_bib40","doi-asserted-by":"crossref","first-page":"461","DOI":"10.1089\/end.2016.0791","article-title":"Artificial neural network system to predict the postoperative outcome of Percutaneous Nephrolithotomy","volume":"31","author":"Aminsharifi","year":"2017","journal-title":"J Endourol"},{"key":"10.1016\/j.jvs.2025.03.198_bib41","first-page":"627","article-title":"Receiver operating characteristic (ROC) curve analysis for medical diagnostic test evaluation","volume":"4","author":"Hajian-Tilaki","year":"2013","journal-title":"Caspian J Intern Med"},{"key":"10.1016\/j.jvs.2025.03.198_bib42","doi-asserted-by":"crossref","first-page":"1141","DOI":"10.1016\/0895-4356(91)90146-Z","article-title":"Assessing predictive accuracy: how to compare Brier scores","volume":"44","author":"Redelmeier","year":"1991","journal-title":"J Clin Epidemiol"},{"key":"10.1016\/j.jvs.2025.03.198_bib43","doi-asserted-by":"crossref","first-page":"569","DOI":"10.6339\/21-JDS1023","article-title":"Variable importance scores","volume":"19","author":"Loh","year":"2021","journal-title":"J Data Sci"},{"key":"10.1016\/j.jvs.2025.03.198_bib44","doi-asserted-by":"crossref","first-page":"1013","DOI":"10.1007\/s10822-020-00314-0","article-title":"Interpretation of machine learning models using shapley values: application to compound potency and multi-target activity predictions","volume":"34","author":"Rodr\u00edguez-P\u00e9rez","year":"2020","journal-title":"J Comput Aided Mol Des"},{"key":"10.1016\/j.jvs.2025.03.198_bib45","article-title":"Calculating the sample size required for developing a clinical prediction model","volume":"18","author":"Riley","year":"2020","journal-title":"BMJ"},{"key":"10.1016\/j.jvs.2025.03.198_bib46","doi-asserted-by":"crossref","first-page":"1583","DOI":"10.1093\/aje\/kwaa124","article-title":"When is a complete-case approach to missing data valid? The importance of effect-measure modification","volume":"189","author":"Ross","year":"2020","journal-title":"Am J Epidemiol"},{"key":"10.1016\/j.jvs.2025.03.198_bib47","doi-asserted-by":"crossref","first-page":"1294","DOI":"10.1093\/ije\/dyz032","article-title":"Accounting for missing data in statistical analyses: multiple imputation is not always the answer","volume":"48","author":"Hughes","year":"2019","journal-title":"Int J Epidemiol"},{"key":"10.1016\/j.jvs.2025.03.198_bib49","author":"Kuhn"},{"key":"10.1016\/j.jvs.2025.03.198_bib50","author":"Wright"},{"key":"10.1016\/j.jvs.2025.03.198_bib53","author":"Ripley"},{"key":"10.1016\/j.jvs.2025.03.198_bib54","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1186\/1471-2105-12-77","article-title":"pROC: an open-source package for R and S+ to analyze and compare ROC curves","volume":"12","author":"Robin","year":"2011","journal-title":"BMC Bioinformatics"},{"key":"10.1016\/j.jvs.2025.03.198_bib55","doi-asserted-by":"crossref","first-page":"1300","DOI":"10.1093\/bjs\/znac309","article-title":"Short-term risk prediction after major lower limb amputation: PERCEIVE study","volume":"109","author":"Gwilym","year":"2022","journal-title":"Br J Surg"},{"key":"10.1016\/j.jvs.2025.03.198_bib56","doi-asserted-by":"crossref","first-page":"685","DOI":"10.1016\/j.surg.2012.07.017","article-title":"Preoperative factors predict mortality after major lower-extremity amputation","volume":"152","author":"Nelson","year":"2012","journal-title":"Surgery"},{"key":"10.1016\/j.jvs.2025.03.198_bib57","doi-asserted-by":"crossref","first-page":"1868","DOI":"10.1016\/j.jvs.2019.03.036","article-title":"Risk prediction of 30-day mortality after lower extremity major amputation","volume":"70","author":"Jolissaint","year":"2019","journal-title":"J Vasc Surg"},{"key":"10.1016\/j.jvs.2025.03.198_bib58","doi-asserted-by":"crossref","first-page":"5426","DOI":"10.3390\/jcm10225426","article-title":"Inaccurate risk assessment by the ACS NSQIP risk calculator in Aortic surgery","volume":"10","author":"Hers","year":"2021","journal-title":"J Clin Med"},{"key":"10.1016\/j.jvs.2025.03.198_bib59","series-title":"StatPearls [Internet]","article-title":"Lower extremity amputation","author":"Molina","year":"2024"},{"key":"10.1016\/j.jvs.2025.03.198_bib60","doi-asserted-by":"crossref","first-page":"3S","DOI":"10.1016\/j.jvs.2019.02.016","article-title":"Global vascular guidelines on the management of chronic limb-threatening ischemia","volume":"69","author":"Conte","year":"2019","journal-title":"J Vasc Surg"},{"key":"10.1016\/j.jvs.2025.03.198_bib61","doi-asserted-by":"crossref","first-page":"15","DOI":"10.14797\/mdcvj.846","article-title":"Community and social context: an important social determinant of cardiovascular disease","volume":"17","author":"Singh","year":"2021","journal-title":"Methodist Debakey Cardiovasc J"},{"key":"10.1016\/j.jvs.2025.03.198_bib62","doi-asserted-by":"crossref","first-page":"681","DOI":"10.1111\/anae.15187","article-title":"Pre-operative optimisation for chronic obstructive pulmonary disease: a narrative review","volume":"76","author":"Lee","year":"2021","journal-title":"Anaesthesia"},{"key":"10.1016\/j.jvs.2025.03.198_bib63","doi-asserted-by":"crossref","first-page":"1099","DOI":"10.1111\/j.1553-2712.2011.01185.x","article-title":"Logistic regression: a brief primer","volume":"18","author":"Stoltzfus","year":"2011","journal-title":"Acad Emerg Med"},{"key":"10.1016\/j.jvs.2025.03.198_bib64","article-title":"Nonlinear systems in healthcare towards intelligent disease prediction","volume":"1","author":"Chatterjee","year":"2019","journal-title":"Nonlinear Syst Theor Asp Recent Appl"},{"key":"10.1016\/j.jvs.2025.03.198_bib65","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41746-021-00394-8","article-title":"Predicting adverse outcomes due to diabetes complications with machine learning using administrative health data","volume":"4","author":"Ravaut","year":"2021","journal-title":"NPJ Digit Med"},{"key":"10.1016\/j.jvs.2025.03.198_bib66","doi-asserted-by":"crossref","first-page":"659","DOI":"10.2147\/NDT.S349956","article-title":"XGBoost machine learning algorithm for prediction of outcome in Aneurysmal Subarachnoid Hemorrhage","volume":"18","author":"Wang","year":"2022","journal-title":"Neuropsychiatr Dis Treat"},{"key":"10.1016\/j.jvs.2025.03.198_bib67","doi-asserted-by":"crossref","DOI":"10.1136\/bmjopen-2021-056685","article-title":"Application of a data-driven XGBoost model for the prediction of COVID-19 in the USA: a time-series study","volume":"12","author":"Fang","year":"2022","journal-title":"BMJ Open"},{"key":"10.1016\/j.jvs.2025.03.198_bib68","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1186\/s12942-022-00304-5","article-title":"A machine learning approach to small area estimation: predicting the health, housing and well-being of the population of Netherlands","volume":"21","author":"Viljanen","year":"2022","journal-title":"Int J Health Geogr"},{"key":"10.1016\/j.jvs.2025.03.198_bib69","doi-asserted-by":"crossref","first-page":"1544","DOI":"10.1001\/jamainternmed.2018.3763","article-title":"Potential biases in machine learning algorithms using electronic health record data","volume":"178","author":"Gianfrancesco","year":"2018","journal-title":"JAMA Intern Med"},{"key":"10.1016\/j.jvs.2025.03.198_bib70","series-title":"StatPearls [Internet]","article-title":"Operative risk","author":"Shaydakov","year":"2022"},{"key":"10.1016\/j.jvs.2025.03.198_bib71","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1097\/SLA.0000000000002014","article-title":"The clinical impact of cardiology consultation prior to major vascular surgery","volume":"267","author":"Davis","year":"2018","journal-title":"Ann Surg"},{"key":"10.1016\/j.jvs.2025.03.198_bib72","doi-asserted-by":"crossref","first-page":"787","DOI":"10.1016\/j.amjsurg.2012.02.018","article-title":"Preoperative medical consultation: maximizing its benefits","volume":"204","author":"Rivera","year":"2012","journal-title":"Am J Surg"},{"key":"10.1016\/j.jvs.2025.03.198_bib73","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1093\/bja\/aew396","article-title":"Intensive care utilization and outcomes after high-risk surgery in Scotland: a population-based cohort study","volume":"118","author":"Gillies","year":"2017","journal-title":"Br J Anaesth"},{"key":"10.1016\/j.jvs.2025.03.198_bib74","series-title":"StatPearls [Internet]","article-title":"Discharge planning","author":"Patel","year":"2022"},{"key":"10.1016\/j.jvs.2025.03.198_bib75","first-page":"66","article-title":"Utility of the vascular quality initiative in improving quality of care in Canadian patients undergoing vascular surgery","volume":"62","author":"Liao","year":"2019","journal-title":"Can J Surg J Can Chir"},{"key":"10.1016\/j.jvs.2025.03.198_bib76","unstructured":"Society for Vascular Surgery Vascular Quality Initiative (SVS VQI) Celebrates 1 Million Procedures [Internet]; 2022. Accessed September 15, 2022. https:\/\/www.vqi.org\/news\/society-for-vascular-surgery-vascular-quality-initiative-svs-vqi-celebrates-1-million-procedures\/"},{"key":"10.1016\/j.jvs.2025.03.198_bib77","doi-asserted-by":"crossref","first-page":"768","DOI":"10.1016\/j.jvs.2010.03.027","article-title":"Analysis of large databases in vascular surgery","volume":"52","author":"Nguyen","year":"2010","journal-title":"J Vasc Surg"},{"key":"10.1016\/j.jvs.2025.03.198_bib78","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1186\/s12961-016-0146-8","article-title":"Enhancing implementation science by applying best principles of systems science","volume":"14","author":"Northridge","year":"2016","journal-title":"Health Res Policy Syst"},{"key":"10.1016\/j.jvs.2025.03.198_bib79","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1186\/s40537-021-00553-4","article-title":"The use of big data analytics in healthcare","volume":"9","author":"Batko","year":"2022","journal-title":"J Big Data"},{"key":"10.1016\/j.jvs.2025.03.198_bib80","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1007\/s42979-021-00592-x","article-title":"Machine learning: algorithms, real-world applications and research directions","volume":"2","author":"Sarker","year":"2021","journal-title":"SN Comput Sci"}],"container-title":["Journal of Vascular Surgery"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0741521425006317?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0741521425006317?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T02:35:07Z","timestamp":1762310107000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0741521425006317"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8]]},"references-count":76,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2025,8]]}},"alternative-id":["S0741521425006317"],"URL":"https:\/\/doi.org\/10.1016\/j.jvs.2025.03.198","relation":{},"ISSN":["0741-5214"],"issn-type":[{"value":"0741-5214","type":"print"}],"subject":[],"published":{"date-parts":[[2025,8]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Predicting mortality risk following major lower extremity amputation using machine learning","name":"articletitle","label":"Article Title"},{"value":"Journal of Vascular Surgery","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.jvs.2025.03.198","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 THE AUTHOR(S). Published by Elsevier Inc. on behalf of the Society for Vascular Surgery.","name":"copyright","label":"Copyright"}]}}