{"title":"Assessment of fracture risk in diabetic patients.","authors":"Zhenpeng Wang, Mei Zhang, Dan Jia","doi":"10.1007/s40200-024-01474-8","DOIUrl":null,"url":null,"abstract":"<p><p>Patients with diabetes often experience reduced bone strength, resulting in a higher fracture risk. This decline and increased susceptibility stem from intricate interactions within the bone microstructure. However, current gold standard methods for assessing bone strength, such as bone mineral density, and widely-used fracture risk assessment tools do not accurately predict fracture risk in diabetic patients. Therefore, it is crucial to incorporate additional indicators that evaluate bone quality and specific markers relevant to diabetes to enhance the accuracy of predictive models. Moreover, the selection of appropriate algorithms for model construction is essential. This review aims to introduce indicators from both imaging examinations and laboratory indicators that hold significant value for inclusion in fracture risk prediction models for diabetic patients. Additionally, this study provides an overview of the research progress in fracture risk prediction models for diabetic patients, serving as a valuable reference for clinical practice.</p>","PeriodicalId":15635,"journal":{"name":"Journal of Diabetes and Metabolic Disorders","volume":"23 2","pages":"1653-1663"},"PeriodicalIF":1.8000,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11599524/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Diabetes and Metabolic Disorders","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s40200-024-01474-8","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/12/1 0:00:00","PubModel":"eCollection","JCR":"Q4","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
引用次数: 0
Abstract
Patients with diabetes often experience reduced bone strength, resulting in a higher fracture risk. This decline and increased susceptibility stem from intricate interactions within the bone microstructure. However, current gold standard methods for assessing bone strength, such as bone mineral density, and widely-used fracture risk assessment tools do not accurately predict fracture risk in diabetic patients. Therefore, it is crucial to incorporate additional indicators that evaluate bone quality and specific markers relevant to diabetes to enhance the accuracy of predictive models. Moreover, the selection of appropriate algorithms for model construction is essential. This review aims to introduce indicators from both imaging examinations and laboratory indicators that hold significant value for inclusion in fracture risk prediction models for diabetic patients. Additionally, this study provides an overview of the research progress in fracture risk prediction models for diabetic patients, serving as a valuable reference for clinical practice.
期刊介绍:
Journal of Diabetes & Metabolic Disorders is a peer reviewed journal which publishes original clinical and translational articles and reviews in the field of endocrinology and provides a forum of debate of the highest quality on these issues. Topics of interest include, but are not limited to, diabetes, lipid disorders, metabolic disorders, osteoporosis, interdisciplinary practices in endocrinology, cardiovascular and metabolic risk, aging research, obesity, traditional medicine, pychosomatic research, behavioral medicine, ethics and evidence-based practices.As of Jan 2018 the journal is published by Springer as a hybrid journal with no article processing charges. All articles published before 2018 are available free of charge on springerlink.Unofficial 2017 2-year Impact Factor: 1.816.