Application of machine learning model in predicting the likelihood of blood transfusion after hip fracture surgery
Author:
Publisher
Springer Science and Business Media LLC
Subject
Geriatrics and Gerontology,Aging
Link
https://link.springer.com/content/pdf/10.1007/s40520-023-02550-4.pdf
Reference34 articles.
1. 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
2. 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
3. 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 31:696–699. https://doi.org/10.1177/1120700020919332
4. 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 18:181–191. https://doi.org/10.2147/cia.S399314
5. Mueller MM, Van Remoortel H, Meybohm P et al (2019) Patient blood management: recommendations from the 2018 Frankfurt consensus conference. JAMA 321:983–997. https://doi.org/10.1001/jama.2019.0554
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