Akademik Veri Yönetim Sistemi
CLINICAL NUTRITION, sa.10, ss.2381-2387, 2024 (SCI-Expanded)
Objectives: Handgrip strength (HGS) is accepted as a predictor of overall health status and a biomarker of aging, besides negative health outcomes and mortality. While differences in HGS between the dominant and non-dominant hands are expected, substantial discrepancies may signal impaired muscle function. This study aims to investigate whether handgrip asymmetry can serve as a reliable indicator of frailty in a diverse population of older adults. Design: Cross-sectional study. Setting and participants: A total of 512 patients aged 65 years and older who were admitted to the geriatric medicine outpatient clinic of a university hospital were enrolled in the study. Methods: The Clinical Frailty Scale (CFS) was used to assess the overall level of frailty of the study population. The highest recorded HGS values from the non-dominant and dominant hand were used to calculate the HGS ratio. Those with a HGS ratio of dominant and non-dominant hand <0.90 or >1.10 were defined as HGS asymmetry. Results: Of the whole study group, 61.1% was female and the mean age was 73.2 +/- 6.1 years. The ratio of the participants living with frailty was 57.6% (n = 219). The number of patients with HGS asymmetry was 264 (51.6%), and 48.4% (n = 248) of the study population had symmetric HGS. The normal and symmetric HGS was found in 40.2% of the non-frail group, whereas it was 23.7% in patients living with frailty. Furthermore, the ratio of low and asymmetric HGS was 16.3% in the non-frail group, and 35.0% in the patients living with frailty (p < 0.001). The presence of asymmetric and low HGS increased the risk of frailty three times independently of other confounding factors (OR:3.08; 95% CI:1.48-6.43; p = 0.003). Conclusions and implications: Identifying HGS asymmetry along with low HGS as potential indicators of frailty may provide clinicians with a clear and quantifiable criterion for assessing older patients. (c) 2024 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights are reserved, including those for text and data mining, AI training, and similar technologies.