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一种基于血清肌酐和胱抑素 C 的新指数可预测低骨密度老年患者发生肌少症、跌倒和骨折的风险。

A New Index Based on Serum Creatinine and Cystatin C Can Predict the Risks of Sarcopenia, Falls and Fractures in Old Patients with Low Bone Mineral Density.

机构信息

Department of Endocrinology and Metabolism, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai 200072, China.

Law Sau Fai Institute for Advancing Translational Medicine in Bone and Joint Diseases, School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tsai, Hong Kong 999077, China.

出版信息

Nutrients. 2022 Nov 25;14(23):5020. doi: 10.3390/nu14235020.

Abstract

As new screening tools for sarcopenia, the serum sarcopenia index (SI) and creatinine/cystatin C ratio (CCR) had not been confirmd in a population with a high fragility fracture risk. This study aimed to evaluate whether SI and CCR indicators are useful for diagnosing sarcopenia and to determine their prediction values for future falls and fractures. A total of 404 hospitalized older adults were enrolled in this longitudinal follow-up study (mean age = 66.43 ± 6.80 years). The receiver operating curve (ROC) was used to assess the diagnostic accuracy of SI and CCR. Backward-selection binary logistic regression was applied to develop the optimal models for the diagnosis of new falls and fractures. SI had a significantly higher area under the curve (AUC) than CCR for predicting sarcopenia. The optimal models had acceptable discriminative powers for predicting new falls and fractures. Lower SI and CCR are the independent risks for sarcopenia, new falls, and fractures in the low-BMD population. SI and CCR, as easily accessible biochemical markers, may be useful in the detection of sarcopenia and in predicting the occurrence of new falls and fractures in patients with low BMD who have not previously experienced falls or fractures. However, further external validations are required.

摘要

作为肌少症的新筛查工具,血清肌少症指数(SI)和肌酐/胱抑素 C 比值(CCR)尚未在高脆性骨折风险人群中得到证实。本研究旨在评估 SI 和 CCR 指标是否有助于诊断肌少症,并确定其对未来跌倒和骨折的预测价值。共有 404 名住院老年患者参与了这项纵向随访研究(平均年龄=66.43±6.80 岁)。采用受试者工作特征曲线(ROC)评估 SI 和 CCR 的诊断准确性。应用向后选择二元逻辑回归建立用于诊断新跌倒和骨折的最佳模型。SI 在预测肌少症方面的曲线下面积(AUC)显著高于 CCR。最佳模型对预测新跌倒和骨折具有可接受的判别能力。低 SI 和 CCR 是低骨密度人群肌少症、新跌倒和骨折的独立危险因素。SI 和 CCR 作为易于获得的生化标志物,可能有助于检测低骨密度且既往无跌倒或骨折史患者的肌少症,并预测新跌倒和骨折的发生。但是,需要进一步的外部验证。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3892/9738634/c68105849494/nutrients-14-05020-g001.jpg

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