Unveiling a hidden burden: exploring sarcopenia in hospitalized older patients through concordance and cluster analysis

揭示隐藏的负担:通过一致性和聚类分析探索住院老年患者的肌少症

阅读:1

Abstract

BACKGROUND: Sarcopenia has been shown to be an important condition with the ability to predict negative health outcomes, especially in hospitalized older adults; hence, its accurate identification has an important role in the prognosis of older patients. AIM: The prevalence of sarcopenia among hospitalized older adults was assessed by employing three distinct diagnostic methods. METHODS: Older adults who were hospitalized were recruited. Bioelectrical impedance analysis was used to assess muscle mass and body composition. Sarcopenia was diagnosed via the European and Asian criteria and via a modified approach in which the Colombian cutoff points for handgrip and gait speed were used. Finally, a cluster analysis was performed to classify the population. RESULTS: The prevalence rates of sarcopenia and severe sarcopenia ranged from 7.3 to 31.6%. The agreement between approaches revealed substantial or almost perfect agreement in 30% of the sarcopenia comparisons and 46.6% of the severe sarcopenia comparisons. The cluster analysis defined three different clusters. The first cluster was associated with increased age, BMI and body fat and poorer functional status and muscle. The second cluster was the healthiest, with high functional status and muscle mass. The third cluster had intermediate characteristics. DISCUSSION: This study highlights the requirements for standardized diagnostic criteria and precise body composition assessment tools in acute geriatric units and highlights the heterogeneity of older adults. Accurate assessment and well-defined diagnostic criteria will facilitate the implementation of appropriate management and interventions. CONCLUSION: Sarcopenia is highly prevalent in hospitalized older adults, but the adjusted criteria and the inclusion of other parameters must be considered in the assessment.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。