Personalizing Short-term Fracture Prevention After Hip Fracture: CT-based AI Risk Stratification

医学 髋部骨折 梅德林 内科学 骨质疏松症 法学 政治学
作者
Matthew Li,Jacob L. Jaremko
出处
期刊:Radiology [Radiological Society of North America]
卷期号:310 (1)
标识
DOI:10.1148/radiol.233396
摘要

HomeRadiologyVol. 310, No. 1 PreviousNext Reviews and CommentaryEditorialPersonalizing Short-term Fracture Prevention After Hip Fracture: CT-based AI Risk StratificationMatthew D. Li , Jacob L. JaremkoMatthew D. Li , Jacob L. JaremkoAuthor AffiliationsFrom the Department of Radiology and Diagnostic Imaging, Faculty of Medicine and Dentistry, University of Alberta Hospital, 8440 112 St NW, 2A2.41 WMC, Edmonton, AB, Canada T6G 2B7.Address correspondence to M.D.L. (email: [email protected]).Matthew D. Li Jacob L. JaremkoPublished Online:Jan 30 2024https://doi.org/10.1148/radiol.233396MoreSectionsFull textPDF ToolsAdd to favoritesCiteTrack CitationsPermissionsReprints ShareShare onFacebookXLinked In References1. Dong Y, Zhang Y, Song K, Kang H, Ye D, Li F. What was the Epidemiology and Global Burden of Disease of Hip Fractures From 1990 to 2019? Results From and Additional Analysis of the Global Burden of Disease Study 2019. Clin Orthop Relat Res 2023;481(6):1209–1220. Crossref, Medline, Google Scholar2. Kanis JA, Johansson H, Harvey NC, et al. The effect on subsequent fracture risk of age, sex, and prior fracture site by recency of prior fracture. Osteoporos Int 2021;32(8):1547–1555. Crossref, Medline, Google Scholar3. Schemitsch E, Adachi JD, Brown JP, et al. Hip fracture predicts subsequent hip fracture: a retrospective observational study to support a call to early hip fracture prevention efforts in post-fracture patients. Osteoporos Int 2022;33(1):113–122. Crossref, Medline, Google Scholar4. Kim Y, Kim YG, Park JW, et al. A CT-based Deep Learning Model for Predicting Subsequent Fracture Risk in Patients with Hip Fracture. Radiology 2024;310(1):e230614. Google Scholar5. Yeam CT, Chia S, Tan HCC, Kwan YH, Fong W, Seng JJB. A systematic review of factors affecting medication adherence among patients with osteoporosis. Osteoporos Int 2018;29(12):2623–2637. Crossref, Medline, Google Scholar6. Therkildsen J, Nissen L, Jørgensen HS, et al. Thoracic Bone Mineral Density Derived from Cardiac CT Is Associated with Greater Fracture Rate. Radiology 2020;296(3):499–508. Link, Google Scholar7. Pickhardt PJ, Graffy PM, Zea R, et al. Automated Abdominal CT Imaging Biomarkers for Opportunistic Prediction of Future Major Osteoporotic Fractures in Asymptomatic Adults. Radiology 2020;297(1):64–72. Link, Google Scholar8. Bilbily A, Syme CA, Adachi JD, et al. Opportunistic screening of low bone mineral density from standard x-rays. J Am Coll Radiol 2023. https://doi.org/10.1016/j.jacr.2023.07.024. Published online October 5, 2023. Crossref, Medline, Google Scholar9. Chung CY, Hu R, Peterson RB, Allen JW. Automated Processing of Head CT Perfusion Imaging for Ischemic Stroke Triage: A Practical Guide to Quality Assurance and Interpretation. AJR Am J Roentgenol 2021;217(6):1401–1416. Crossref, Medline, Google Scholar10. Arun N, Gaw N, Singh P, et al. Assessing the Trustworthiness of Saliency Maps for Localizing Abnormalities in Medical Imaging. Radiol Artif Intell 2021;3(6):e200267. Link, Google ScholarArticle HistoryReceived: Dec 15 2023Revision requested: Jan 4 2024Revision received: Jan 7 2024Accepted: Jan 8 2024Published online: Jan 30 2024 FiguresReferencesRelatedDetailsRecommended Articles RSNA Education Exhibits RSNA Case Collection Vol. 310, No. 1 Metrics Altmetric Score PDF download
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