Association between frailty and the cardio-ankle vascular index

Frailty and atherosclerotic diseases are prevalent among the older people and usually present the same pathogenesis and risk factors. Therefore, the aim of this study was to determine the association between frailty and atherosclerosis.

The enrolled participants were 171 patients aged 60-96 years in Beijing Tongren Hospital. Data that were collected included sex, age, height, weight, calculated body mass index (BMI), past medical history, comorbidities (including hypertension, coronary heart disease [CHD], and diabetes), ability to perform activities of daily living (ADL) as measured using the Barthel index, handgrip strength, 15-feet (4.57 m) walking speed, body composition features determined by bioelectrical impedance analysis, the ankle-brachial index (ABI), and atherosclerosis determined by the cardio-ankle vascular index (CAVI). Patients were divided into frail, pre-frail, and non-frail groups using Fried's frailty index. ANOVA was used to assess the differences among these groups. Linear correlation analysis was used to examine the relationship between the CAVI and frailty phenotype. Ordinal multivariate logistic regression analysis was used to examine the factors affecting frailty and the relationship between frailty and atherosclerosis.

The population was categorized as 21.3% frail, 38.4% pre-frail, and 40.3% non-frail. Patients in the frail group were older, had lower handgrip strength, slower walking speed, and a lower ABI and a higher proportion of carotid intima-media thickening with values of at least 1 mm compared with those in the pre-frail and non-frail groups. The CAVI score was higher in the frail group than that in the other two groups. There were significant inverse linear correlations between grip strength, walking speed, and the CAVI. CAVI showed an independent risk factor for frailty (OR: 2.013, 95% CI 1.498-2.703, p<0.001).

Our study shows that arterial stiffness is associated with frailty in older patients, even when adjusting for multiple factors.