{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T16:45:30Z","timestamp":1790095530419,"version":"4.0.1"},"reference-count":34,"publisher":"Springer Science and Business Media LLC","issue":"11","license":[{"start":{"date-parts":[[2023,9,21]],"date-time":"2023-09-21T00:00:00Z","timestamp":1695254400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,9,21]],"date-time":"2023-09-21T00:00:00Z","timestamp":1695254400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Aging Clin Exp Res"],"DOI":"10.1007\/s40520-023-02550-4","type":"journal-article","created":{"date-parts":[[2023,9,21]],"date-time":"2023-09-21T07:02:52Z","timestamp":1695279772000},"page":"2643-2656","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Application of machine learning model in predicting the likelihood of blood transfusion after hip fracture surgery"],"prefix":"10.1007","volume":"35","author":[{"given":"Xiao","family":"Chen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junpeng","family":"Pan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yi","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruixin","family":"Tang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2023,9,21]]},"reference":[{"key":"2550_CR1","doi-asserted-by":"publisher","first-page":"926745","DOI":"10.3389\/fsurg.2022.926745","volume":"9","author":"X Lu","year":"2022","unstructured":"Lu X, Wang Z, Chong F et al (2022) A new nomogram model for predicting 1-year all-cause mortality after hip arthroplasty in nonagenarians with hip fractures: a 20-year period retrospective cohort study. Front Surg 9:926745. https:\/\/doi.org\/10.3389\/fsurg.2022.926745","journal-title":"Front Surg"},{"key":"2550_CR2","doi-asserted-by":"publisher","first-page":"e1003180","DOI":"10.1371\/journal.pmed.1003180","volume":"17","author":"C Zhang","year":"2020","unstructured":"Zhang C, Feng J, Wang S et al (2020) Incidence of and trends in hip fracture among adults in urban China: a nationwide retrospective cohort study. PLoS Med 17:e1003180. https:\/\/doi.org\/10.1371\/journal.pmed.1003180","journal-title":"PLoS Med"},{"key":"2550_CR3","doi-asserted-by":"publisher","first-page":"696","DOI":"10.1177\/1120700020919332","volume":"31","author":"AV Christiano","year":"2021","unstructured":"Christiano AV, Elsevier HC, Sarker S et al (2021) Improving outcomes after hip fracture at a safety net hospital with a standardised hip fracture protocol. Hip Int 31:696\u2013699. https:\/\/doi.org\/10.1177\/1120700020919332","journal-title":"Hip Int"},{"key":"2550_CR4","doi-asserted-by":"publisher","first-page":"181","DOI":"10.2147\/cia.S399314","volume":"18","author":"L Pan","year":"2023","unstructured":"Pan L, Liu Z, Wu H et al (2023) Construction and validation of a nomogram for predicting acute kidney injury after hip fracture surgery. Clin Interv Aging 18:181\u2013191. https:\/\/doi.org\/10.2147\/cia.S399314","journal-title":"Clin Interv Aging"},{"key":"2550_CR5","doi-asserted-by":"publisher","first-page":"983","DOI":"10.1001\/jama.2019.0554","volume":"321","author":"MM Mueller","year":"2019","unstructured":"Mueller MM, Van Remoortel H, Meybohm P et al (2019) Patient blood management: recommendations from the 2018 Frankfurt consensus conference. JAMA 321:983\u2013997. https:\/\/doi.org\/10.1001\/jama.2019.0554","journal-title":"JAMA"},{"key":"2550_CR6","doi-asserted-by":"publisher","first-page":"383","DOI":"10.2450\/2011.0095-10","volume":"9","author":"F Verlicchi","year":"2011","unstructured":"Verlicchi F, Desalvo F, Zanotti G et al (2011) Red cell transfusion in orthopaedic surgery: a benchmark study performed combining data from different data sources. Blood Transfusion = Trasfusione del sangue 9:383\u2013387. https:\/\/doi.org\/10.2450\/2011.0095-10","journal-title":"Blood Transfusion = Trasfusione del sangue"},{"key":"2550_CR7","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1186\/s13018-020-02053-2","volume":"16","author":"H Wang","year":"2021","unstructured":"Wang H, Wang K, Lv B et al (2021) Establishment and assessment of a nomogram for predicting blood transfusion risk in posterior lumbar spinal fusion. J Orthop Surg Res 16:39. https:\/\/doi.org\/10.1186\/s13018-020-02053-2","journal-title":"J Orthop Surg Res"},{"key":"2550_CR8","doi-asserted-by":"publisher","first-page":"959","DOI":"10.1001\/jama.289.8.959","volume":"289","author":"MP Busch","year":"2003","unstructured":"Busch MP, Kleinman SH, Nemo GJ (2003) Current and emerging infectious risks of blood transfusions. JAMA 289:959\u2013962. https:\/\/doi.org\/10.1001\/jama.289.8.959","journal-title":"JAMA"},{"key":"2550_CR9","doi-asserted-by":"publisher","first-page":"1125875","DOI":"10.3389\/fsurg.2023.1125875","volume":"10","author":"Y Liu","year":"2023","unstructured":"Liu Y, Zhao S, Du W et al (2023) Applying interpretable machine learning algorithms to predict risk factors for permanent stoma in patients after TME. Front Surg 10:1125875. https:\/\/doi.org\/10.3389\/fsurg.2023.1125875","journal-title":"Front Surg"},{"key":"2550_CR10","doi-asserted-by":"publisher","first-page":"941349","DOI":"10.3389\/fonc.2022.941349","volume":"12","author":"S Chen","year":"2022","unstructured":"Chen S, Jian T, Chi C et al (2022) Machine learning-based models enhance the prediction of prostate cancer. Front Oncol 12:941349. https:\/\/doi.org\/10.3389\/fonc.2022.941349","journal-title":"Front Oncol"},{"key":"2550_CR11","doi-asserted-by":"publisher","first-page":"634629","DOI":"10.3389\/fsurg.2021.634629","volume":"8","author":"H Zhao","year":"2021","unstructured":"Zhao H, You J, Peng Y et al (2021) Machine learning algorithm using electronic chart-derived data to predict delirium after elderly hip fracture surgeries: a retrospective case-control study. Front Surg 8:634629. https:\/\/doi.org\/10.3389\/fsurg.2021.634629","journal-title":"Front Surg"},{"key":"2550_CR12","doi-asserted-by":"publisher","first-page":"912","DOI":"10.1186\/s12877-022-03631-1","volume":"22","author":"CB Huang","year":"2022","unstructured":"Huang CB, Tan K, Wu ZY et al (2022) Application of machine learning model to predict lacunar cerebral infarction in elderly patients with femoral neck fracture before surgery. BMC Geriatr 22:912. https:\/\/doi.org\/10.1186\/s12877-022-03631-1","journal-title":"BMC Geriatr"},{"key":"2550_CR13","doi-asserted-by":"publisher","first-page":"1487","DOI":"10.1016\/j.injury.2020.12.008","volume":"52","author":"Y Li","year":"2021","unstructured":"Li Y, Chen M, Lv H et al (2021) A novel machine-learning algorithm for predicting mortality risk after hip fracture surgery. Injury 52:1487\u20131493. https:\/\/doi.org\/10.1016\/j.injury.2020.12.008","journal-title":"Injury"},{"key":"2550_CR14","unstructured":"Lundberg SM, Lee SI (2017) A Unified Approach to Interpreting Model Predictions. In: 31st Annual Conference on Neural Information Processing Systems (NIPS): Dec 04\u201309 2017; Long Beach, CA. LA JOLLA: Neural Information Processing Systems (Nips)"},{"key":"2550_CR15","doi-asserted-by":"publisher","first-page":"749","DOI":"10.1038\/s41551-018-0304-0","volume":"2","author":"SM Lundberg","year":"2018","unstructured":"Lundberg SM, Nair B, Vavilala MS et al (2018) Explainable machine-learning predictions for the prevention of hypoxaemia during surgery. Nat Biomed Eng 2:749\u2013760. https:\/\/doi.org\/10.1038\/s41551-018-0304-0","journal-title":"Nat Biomed Eng"},{"key":"2550_CR16","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1038\/s42256-019-0048-x","volume":"1","author":"C Rudin","year":"2019","unstructured":"Rudin C (2019) Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead. Nat Mach Intell 1:206\u2013215. https:\/\/doi.org\/10.1038\/s42256-019-0048-x","journal-title":"Nat Mach Intell"},{"key":"2550_CR17","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1186\/s41747-018-0061-6","volume":"2","author":"F Pesapane","year":"2018","unstructured":"Pesapane F, Codari M, Sardanelli F (2018) Artificial intelligence in medical imaging: threat or opportunity? Radiologists again at the forefront of innovation in medicine. Eur Radiol Exp 2:35. https:\/\/doi.org\/10.1186\/s41747-018-0061-6","journal-title":"Eur Radiol Exp"},{"key":"2550_CR18","doi-asserted-by":"publisher","first-page":"812023","DOI":"10.3389\/fpubh.2021.812023","volume":"9","author":"W Li","year":"2021","unstructured":"Li W, Wang J, Liu W et al (2021) Machine learning applications for the prediction of bone cement leakage in percutaneous vertebroplasty. Front Public Health 9:812023. https:\/\/doi.org\/10.3389\/fpubh.2021.812023","journal-title":"Front Public Health"},{"key":"2550_CR19","doi-asserted-by":"publisher","first-page":"e2011768","DOI":"10.1001\/jamanetworkopen.2020.11768","volume":"3","author":"YJ Tseng","year":"2020","unstructured":"Tseng YJ, Wang HY, Lin TW et al (2020) Development of a machine learning model for survival risk stratification of patients with advanced oral cancer. JAMA NetW Open 3:e2011768. https:\/\/doi.org\/10.1001\/jamanetworkopen.2020.11768","journal-title":"JAMA NetW Open"},{"key":"2550_CR20","doi-asserted-by":"publisher","first-page":"1251","DOI":"10.2147\/ijgm.S409363","volume":"16","author":"Y Liu","year":"2023","unstructured":"Liu Y, Song C, Tian Z et al (2023) Identification of high-risk patients for postoperative myocardial injury after CME using machine learning: a 10-year multicenter retrospective study. Int J Gen Med 16:1251\u20131264. https:\/\/doi.org\/10.2147\/ijgm.S409363","journal-title":"Int J Gen Med"},{"key":"2550_CR21","doi-asserted-by":"publisher","first-page":"272","DOI":"10.1177\/1120700019897878","volume":"31","author":"A Arshi","year":"2021","unstructured":"Arshi A, Lai WC, Iglesias BC et al (2021) Blood transfusion rates and predictors following geriatric hip fracture surgery. Hip Int 31:272\u2013279. https:\/\/doi.org\/10.1177\/1120700019897878","journal-title":"Hip Int"},{"key":"2550_CR22","doi-asserted-by":"publisher","first-page":"1266","DOI":"10.1302\/0301-620x.104b11.Bjj-2022-0450.R1","volume":"104-b","author":"L Farrow","year":"2022","unstructured":"Farrow L, Brasnic L, Martin C et al (2022) A nationwide study of blood transfusion in hip fracture patients\u202f: linked analysis from the Scottish hip fracture audit and the scottish national blood transfusion service. Bone Jt J 104-b:1266\u20131272. https:\/\/doi.org\/10.1302\/0301-620x.104b11.Bjj-2022-0450.R1","journal-title":"Bone Jt J"},{"key":"2550_CR23","doi-asserted-by":"publisher","first-page":"695274","DOI":"10.3389\/fsurg.2021.695274","volume":"8","author":"B Liu","year":"2021","unstructured":"Liu B, Pan J, Zong H et al (2021) Establishment and verification of a perioperative blood transfusion model after posterior lumbar interbody fusion: a retrospective study based on data from a local hospital. Front Surg 8:695274. https:\/\/doi.org\/10.3389\/fsurg.2021.695274","journal-title":"Front Surg"},{"key":"2550_CR24","doi-asserted-by":"publisher","first-page":"406","DOI":"10.1186\/s13018-021-02557-5","volume":"16","author":"FC Bian","year":"2021","unstructured":"Bian FC, Cheng XK, An YS (2021) Preoperative risk factors for postoperative blood transfusion after hip fracture surgery: establishment of a nomogram. J Orthop Surg Res 16:406. https:\/\/doi.org\/10.1186\/s13018-021-02557-5","journal-title":"J Orthop Surg Res"},{"key":"2550_CR25","doi-asserted-by":"publisher","first-page":"30","DOI":"10.4055\/cios20070","volume":"13","author":"YS Suh","year":"2021","unstructured":"Suh YS, Nho JH, Seo J et al (2021) Hip fracture surgery without transfusion in patients with hemoglobin less than 10 g\/dL. Clin Orthop Surg 13:30\u201336. https:\/\/doi.org\/10.4055\/cios20070","journal-title":"Clin Orthop Surg"},{"key":"2550_CR26","doi-asserted-by":"publisher","first-page":"1","DOI":"10.2147\/cia.S253193","volume":"16","author":"J Wang","year":"2021","unstructured":"Wang J, Zhao Y, Jiang B et al (2021) Development of a nomogram to predict postoperative transfusion in the elderly after intramedullary nail fixation of femoral intertrochanteric fractures. Clin Interv Aging 16:1\u20137. https:\/\/doi.org\/10.2147\/cia.S253193","journal-title":"Clin Interv Aging"},{"key":"2550_CR27","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1016\/j.ijsu.2015.11.009","volume":"24","author":"G Karademir","year":"2015","unstructured":"Karademir G, Bilgin Y, Er\u015fen A et al (2015) Hip fractures in patients older than 75 years old: Retrospective analysis for prognostic factors. Int J Surg 24:101\u2013104. https:\/\/doi.org\/10.1016\/j.ijsu.2015.11.009","journal-title":"Int J Surg (Lond England)"},{"key":"2550_CR28","doi-asserted-by":"publisher","first-page":"CD009699","DOI":"10.1002\/14651858.CD009699.pub2","volume":"4","author":"SJ Brunskill","year":"2015","unstructured":"Brunskill SJ, Millette SL, Shokoohi A et al (2015) Red blood cell transfusion for people undergoing hip fracture surgery. Cochrane Database Syst Rev 4:CD009699. https:\/\/doi.org\/10.1002\/14651858.CD009699.pub2","journal-title":"Cochrane Database Syst Rev"},{"key":"2550_CR29","doi-asserted-by":"publisher","first-page":"225","DOI":"10.1016\/j.jse.2008.08.005","volume":"18","author":"KI Gruson","year":"2009","unstructured":"Gruson KI, Accousti KJ, Parsons BO et al (2009) Transfusion after shoulder arthroplasty: an analysis of rates and risk factors. J Shoulder Elbow Surg 18:225\u2013230. https:\/\/doi.org\/10.1016\/j.jse.2008.08.005","journal-title":"J Shoulder Elbow Surg"},{"key":"2550_CR30","doi-asserted-by":"publisher","first-page":"1025335","DOI":"10.3389\/fimmu.2022.1025335","volume":"13","author":"L Sun","year":"2022","unstructured":"Sun L, Liu W, Li C et al (2022) Construction and internal validation of a predictive model for risk of gastrointestinal bleeding in children with abdominal Henoch-Sch\u00f6nlein purpura: a single-center retrospective case-control study. Front Immunol 13:1025335. https:\/\/doi.org\/10.3389\/fimmu.2022.1025335","journal-title":"Front Immunol"},{"key":"2550_CR31","doi-asserted-by":"publisher","first-page":"74","DOI":"10.1016\/j.ijbiomac.2019.01.124","volume":"128","author":"N Gligorijevi\u0107","year":"2019","unstructured":"Gligorijevi\u0107 N, Mini\u0107 S, Robajac D et al (2019) Characterisation and the effects of bilirubin binding to human fibrinogen. Int J Biol Macromol 128:74\u201379. https:\/\/doi.org\/10.1016\/j.ijbiomac.2019.01.124","journal-title":"Int J Biol Macromol"},{"key":"2550_CR32","doi-asserted-by":"publisher","first-page":"903","DOI":"10.1007\/s10072-019-04182-x","volume":"41","author":"Y Jian","year":"2020","unstructured":"Jian Y, Zhao L, Wang H et al (2020) Bilirubin: a novel predictor of hemorrhagic transformation and symptomatic intracranial hemorrhage after mechanical thrombectomy. Neurol Sci 41:903\u2013909. https:\/\/doi.org\/10.1007\/s10072-019-04182-x","journal-title":"Neurol Sci"},{"key":"2550_CR33","doi-asserted-by":"publisher","first-page":"507","DOI":"10.6002\/ect.2016.0325","volume":"17","author":"MH Eghbal","year":"2019","unstructured":"Eghbal MH, Samadi K, Khosravi MB et al (2019) The impact of preoperative variables on intraoperative blood loss and transfusion requirements during orthotopic liver transplant. Exp Clin Transplant 17:507\u2013512. https:\/\/doi.org\/10.6002\/ect.2016.0325","journal-title":"Exp Clin Transplant"},{"key":"2550_CR34","doi-asserted-by":"publisher","first-page":"3196","DOI":"10.3748\/wjg.v22.i11.3196","volume":"22","author":"MH Lee","year":"2016","unstructured":"Lee MH, Tsou YK, Lin CH et al (2016) Predictors of re-bleeding after endoscopic hemostasis for delayed post-endoscopic sphincterotomy bleeding. World J Gastroenterol 22:3196\u20133201. https:\/\/doi.org\/10.3748\/wjg.v22.i11.3196","journal-title":"World J Gastroenterol"}],"container-title":["Aging Clinical and Experimental Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s40520-023-02550-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s40520-023-02550-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s40520-023-02550-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,6]],"date-time":"2023-11-06T17:38:20Z","timestamp":1699292300000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s40520-023-02550-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9,21]]},"references-count":34,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2023,11]]}},"alternative-id":["2550"],"URL":"https:\/\/doi.org\/10.1007\/s40520-023-02550-4","relation":{},"ISSN":["1720-8319"],"issn-type":[{"value":"1720-8319","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,9,21]]},"assertion":[{"value":"5 July 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 August 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 September 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"All authors declare that they have no conflict of interest to disclose.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"This study was conducted with approval from the Ethics Committee of the Affiliated Hospital of Qingdao University, with approval No. QYFY -WZLL-27908. Yes, this study was conducted in accordance with the declaration of Helsinki, and do compliance with Ethical Standards.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"ll procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and\/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Human and animal rights"}},{"value":"Written informed consent was obtained from the participants or their guardians.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}}]}}