P.63 Sarcopenia and Atherosclerotic Occlusive Disease: How Much We Know and What We Need to Know About this Association?

Abstract

Purpose/BackgroundSarcopenia (decrease of muscle mass and function) has been linked with atherosclerosis [1]. The EWGSOP2 updated consensus, uses low muscle strength as the primary indicator of sarcopenia [2]. It is acknowledged that strength is better than mass for predicting adverse outcomes [2]. Handgrip strength (HGS) is a simple assessment to estimate overall muscular strength [3]. and is associated with cardiovascular mortality [4].ObjectiveAnalyze the relationship between HGS and atherosclerotic disease (carotid artery disease + lower extremity artery disease).MethodsProspective observation study was conducted from January to December 2019. The clinical and demographic data was recorded. Isometric HGS was measured with an adjustable handheld dynamometer (Jamar The higher value of each arm was used to classify the patient as sarcopenic or non-sarcopenic. Definition of sarcopenia: HGS <30 kgf in men and <20 kgf in women [5].Results94 patients (aged 44–86 years) were analyzed: 64 sarcopenic and 30 non sarcopenic. Groups differed in the prevalence of diabetes and smoking status (Table 1). No differences were found in the carotid parameters analyzed (Table 1). There was, a difference in the prevalence of chronic limb-threatening ischemia (CLTI) in sarcopenic versus non-sarcopenic group (23.44% versus 6.67% p = 0.046). Importantly, binary logistic regression showed that diabetes (p = 0.014), and HGS (p = 0.027) have a significant effect on CLTI (Table 2).ConclusionsNo relationship was found between sarcopenia (measured by HGS) and carotid atherosclerosis, differing from other authors [1,6]. In this study, sarcopenic had a higher incident of diabetes and CLTI. Sarcopenia and diabetes are reciprocally related and may share a similar pathogenetic pathway [7,8,9].Table 1Sarcopenia (n = 64)No Sarcopenia (n = 30)pAge (years)69.81 ± 8.7962.6 ± 8.61p = 0.889Male47 (73.44%)27 (90.00%)p = 0.067Hypertension51 (79.69%)21 (70.00%)p = 0.301Dyslipidemia47 (73.43%)18 (60.00%)p = 0.189Smoking load (UMA)24.42 ± 33.1437.76 ± 31.8p = 0.748Smoker/Ex-smoker33 (51.56%)24 (80.00%)p = 0.013*Diabetes28 (43.75%)7 (23.33%)p = 0.049*Coronary disease11 (17.19%)4 (13.33%)p = 0.613History of stroke11 (17.19%)3 (10.00%)p = 0.347Total cholesterol (mg/dL)158.16 ± 39.82159.6 ± 30.72p = 0.22LEAD43 (67.19%)17 (56.67%)p = 0.275Claudicants28 (43.75%)15 (50.00%)p = 0.615CLTI15 (23.44%)2 (6.67%)p = 0.046*ABI right0.83 ± 0.240.78 ± 0.29p = 0.287ABI left0.81 ± 0.280.77 ± 0.23p = 0.671Right carotid artery stenosis50–704 (6.25%)2 (6.67%)p = 0.952>70%58 (90.63%)27 (90.00%)p = 0.702Light carotid artery stenosis50–703 (4.79%)1 (3.33%)p = 0.787>70%4 (6.25%)2 (6.67%)p = 0.903Area right carotid plaque (mm2)21.22 ± 19.8120.01 ± 17.04p = 0.622Average IMT- right (mm)0.96 ± 0.410.88 ± 0.24p = 0.159Area left carotid plaque (mm2)21.46 ± 18.7321.47 ± 22.06p = 0.948Average IMT- left (mm)0.93 ± 0.250.88 ± 0.29p = 0.861Table 2Independent variablesCategoriesa95% CIpCLTIDiabetes1.4881.34–14.600.014Higher HGS−0.8880.846–0.9900.027