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Will absolute fracture risk prediction facilitate treatment of osteoporosis?

机译:绝对骨折风险预测会有助于骨质疏松症的治疗吗?

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Development of valid risk prediction tools for osteoporosis could substantially improve patient care. These tools have the potential to identify individuals at increased fracture risk and specifically direct interventions towards them rather than low-risk individuals. In this Practice Point commentary, I discuss a study by Hans et al. that adds to our current understanding of fracture risk prediction. This large, prospective study aimed to develop a 10-year hip fracture risk prediction tool that combined quantitative ultrasound of the heel bone with clinical risk factors. The authors found that combined use of these parameters was highly predictive of future fracture risk in a cohort of almost 13,000 elderly, white, European women. Significant clinical risk factors included BMI, previous fracture, history of recent fall, current smoking, failed chair test, and diabetes mellitus; age was also found to be a significant risk factor. Before embracing such tools, however, we must acknowledge some important unknowns about their utility.
机译:开发有效的骨质疏松风险预测工具可以大大改善患者护理。这些工具有可能识别出骨折风险增加的人,并特别针对他们而不是低风险的人进行干预。在本《实践要点》评论中,我讨论了Hans等人的一项研究。这增加了我们对骨折风险预测的当前了解。这项大型的前瞻性研究旨在开发一种10年髋部骨折风险预测工具,该工具将脚跟骨的定量超声检查与临床风险因素相结合。作者发现,这些参数的综合使用可高度预测近13,000名欧洲白人老年女性队列中的未来骨折风险。重要的临床危险因素包括BMI,先前的骨折,近期跌倒史,当前吸烟,椅子测试失败和糖尿病。还发现年龄是重要的危险因素。但是,在使用此类工具之前,我们必须承认有关其实用性的一些重要未知因素。

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