P.63 Sarcopenia and Atherosclerotic Occlusive Disease: How Much We Know and What We Need to Know About this Association?
Authors: Ferreira Joana , Carneiro Alexandre , Cunha Pedro , Mansilha Armando , Vila Isabel , Cunha Cristina , Silva Cristina , Longatto-Filho Adhemar , Correia-Neves Maria , Soutinho Gustavo , Meira-Machado Luís , Mesquita Amilcar , Cotter Jorge 
Published: December 2020

Abstract
Purpose/Background
Sarcopenia (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].

Objective
Analyze the relationship between HGS and atherosclerotic disease (carotid artery disease + lower extremity artery disease).

Methods
Prospective 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].

Results
94 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).

Conclusions
No 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 1

Sarcopenia (n = 64)
No Sarcopenia (n = 30)
p

Age (years)
69.81 ± 8.79
62.6 ± 8.61
p = 0.889

Male
47 (73.44%)
27 (90.00%)
p = 0.067

Hypertension
51 (79.69%)
21 (70.00%)
p = 0.301

Dyslipidemia
47 (73.43%)
18 (60.00%)
p = 0.189

Smoking load (UMA)
24.42 ± 33.14
37.76 ± 31.8
p = 0.748

Smoker/Ex-smoker
33 (51.56%)
24 (80.00%)
p = 0.013*

Diabetes
28 (43.75%)
7 (23.33%)
p = 0.049*

Coronary disease
11 (17.19%)
4 (13.33%)
p = 0.613

History of stroke
11 (17.19%)
3 (10.00%)
p = 0.347

Total cholesterol (mg/dL)
158.16 ± 39.82
159.6 ± 30.72
p = 0.22

LEAD
43 (67.19%)
17 (56.67%)
p = 0.275

Claudicants
28 (43.75%)
15 (50.00%)
p = 0.615

CLTI
15 (23.44%)
2 (6.67%)
p = 0.046*

ABI right
0.83 ± 0.24
0.78 ± 0.29
p = 0.287

ABI left
0.81 ± 0.28
0.77 ± 0.23
p = 0.671

Right carotid artery stenosis

50–70
4 (6.25%)
2 (6.67%)
p = 0.952

>70%
58 (90.63%)
27 (90.00%)
p = 0.702

Light carotid artery stenosis

50–70
3 (4.79%)
1 (3.33%)
p = 0.787

>70%
4 (6.25%)
2 (6.67%)
p = 0.903

Area right carotid plaque (mm2)
21.22 ± 19.81
20.01 ± 17.04
p = 0.622

Average IMT- right (mm)
0.96 ± 0.41
0.88 ± 0.24
p = 0.159

Area left carotid plaque (mm2)
21.46 ± 18.73
21.47 ± 22.06
p = 0.948

Average IMT- left (mm)
0.93 ± 0.25
0.88 ± 0.29
p = 0.861

Table 2

Independent variables
Categories
a
95% CI
p

CLTI
Diabetes
1.488
1.34–14.60
0.014

Higher HGS
−0.888
0.846–0.990
0.027