Cheng Keith Yu-Kin, Chow Simon Kwoon-Ho, Hung Vivian Wing-Yin, Tsang Zoey Tsz-Lok, Yip Benjamin Hon-Kei, Wong Ronald Man Yeung, Zhang Ning, Qin Ling, Law Sheung-Wai, Cheung Wing-Hoi
Bone Quality and Health Centre, Department of Orthopaedics and Traumatology, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China.
JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China.
J Pers Med. 2024 Sep 2;14(9):935. doi: 10.3390/jpm14090935.
Osteosarcopenia is a prevalent geriatric disease with a significantly increased risk of adverse outcomes than osteoporosis or sarcopenia alone. Identification of older adults with osteosarcopenia using High-Resolution Peripheral Quantitative Computed Tomography (HR-pQCT) could allow better clinical decision making. This study aimed to explore the feasibility of HR-pQCT to differentiate osteoporosis, sarcopenia, and osteosarcopenia in older adults, with a primary outcome to derive a model to distinguish older adults with osteosarcopenia from those with low bone mineral density only, and to examine important HR-pQCT parameters associated with osteosarcopenia. This was a cross-sectional study involving 628 community-dwelling Chinese adults aged ≥ 40. Subjects were assessed by dual energy X-ray absorptiometry (DXA) for osteopenia/osteoporosis and sarcopenia using the Asian Working Group for Sarcopenia definition; then grouped into healthy, osteopenia/osteoporosis, sarcopenia, and osteosarcopenia groups. A series of regression analyses and other statistical tests were performed to derive the model. HR-pQCT showed the ability to discriminate older adults with osteosarcopenia from those with osteopenia/osteoporosis only. Cross-validation of our derived model correctly classified 77.0% of the cases with good diagnostic power and showed a sensitivity of 76.0% and specificity of 77.6% (Youden index = 0.54; AUC = 0.79, < 0.001). Analysis showed trabecular volumetric bone density and cortical periosteal perimeter were important and sensitive parameters in discriminating osteosarcopenia from osteopenia/osteoporosis subjects. These findings demonstrated that HR-pQCT is a viable and effective screening method for differentiating osteosarcopenia from low bone mineral density alone without the need to carry out multiple assessments for osteosarcopenia, especially for case-finding purposes. This could facilitate the decision of a follow-up and the management of these frail older adults to ensure they receive timely therapeutic interventions to minimise the associated risks.
骨少肌减少症是一种常见的老年疾病,与单独的骨质疏松症或肌少症相比,其不良后果风险显著增加。使用高分辨率外周定量计算机断层扫描(HR-pQCT)识别患有骨少肌减少症的老年人可以使临床决策更优。本研究旨在探讨HR-pQCT区分老年人骨质疏松症、肌少症和骨少肌减少症的可行性,主要结果是建立一个模型,以区分患有骨少肌减少症的老年人和仅患有低骨密度的老年人,并检查与骨少肌减少症相关的重要HR-pQCT参数。这是一项横断面研究,纳入了628名年龄≥40岁的社区居住中国成年人。通过双能X线吸收法(DXA)评估受试者的骨质减少/骨质疏松症,并根据亚洲肌少症工作组的定义评估肌少症;然后将其分为健康组、骨质减少/骨质疏松症组、肌少症组和骨少肌减少症组。进行了一系列回归分析和其他统计测试以建立模型。HR-pQCT显示出能够区分患有骨少肌减少症的老年人和仅患有骨质减少/骨质疏松症的老年人。我们推导模型的交叉验证正确分类了77.0%的病例,具有良好的诊断能力,敏感性为76.0%,特异性为77.6%(约登指数=0.54;AUC=0.79,<0.001)。分析表明,骨小梁体积骨密度和皮质骨膜周长是区分骨少肌减少症与骨质减少/骨质疏松症受试者的重要且敏感的参数。这些发现表明,HR-pQCT是一种可行且有效的筛查方法,可将骨少肌减少症与单纯低骨密度区分开来,而无需对骨少肌减少症进行多次评估,特别是用于病例发现目的。这有助于后续决策以及对这些体弱老年人的管理,以确保他们及时接受治疗干预,将相关风险降至最低。