The alterations in multiple neurophysiological procedures are associated with frailty phenotype in older adults

Abstract

BackgroundOlder adults oftentimes suffer from the conditions in multiple physiologic systems, interfering with their daily function and thus contributing to physical frailty. The contributions of such multisystem conditions to physical frailty have not been well characterized.MethodsIn this study, 442 (mean age = 71.4 ± 8.1 years, 235 women) participants completed the assessment of frailty syndromes, including unintentional weight loss, exhaustion, slowness, low activity, and weakness, and were categorized into frail (≥3 conditions), pre-frail (1 or 2 conditions), and robust (no condition) status. Multisystem conditions including cardiovascular diseases, vascular function, hypertension, diabetes, sleep disorders, sarcopenia, cognitive impairment, and chronic pain were assessed. Structural equation modeling examined the interrelationships between these conditions and their associations with frailty syndromes.ResultsFifty (11.3%) participants were frail, 212 (48.0%) were pre-frail, and 180 (40.7%) were robust. We observed that worse vascular function was directly associated with higher risk of slowness [standardized coefficient (SC) = −0.419, p < 0.001], weakness (SC = −0.367, p < 0.001), and exhaustion (SC = −0.347, p < 0.001). Sarcopenia was associated with both slowness (SC = 0.132, p = 0.011) and weakness (SC = 0.217, p = 0.001). Chronic pain, poor sleep quality, and cognitive impairment were associated with exhaustion (SC = 0.263, p < 0.001; SC = 0.143, p = 0.016; SC = 0.178, p = 0.004, respectively). The multinomial logistic regression showed that greater number of these conditions were associated with increased probability of being frail (odds ratio>1.23, p < 0.032).ConclusionThese findings in this pilot study provide novel insights into how multisystem conditions are associated with each other and with frailty in older adults. Future longitudinal studies are warranted to explore how the changes in these health conditions alter frailty status.

Endothelial Dysfunction as a Key Link between Cardiovascular Disease and Frailty: A Systematic Review

“…The methods used to measure vascular endothelial function and physical fragility were inconsistent across the included studies, with some studies using multiple measures. Of the 29 studies included in the review, carotid intima-media thickness (CIMT; n = 7 [22,26,28,33,[36][37][38]), the ankle-brachial pressure index (ABPI; n = 4 [22,36,37,45]), carotid-femoral pulse wave velocity (cfPWV; n = 7 [25,[36][37][38]41,44,45]), ankle-brachial pulse wave velocity (baPWV; n = 4 [20,21,26,32]), carotid distensibility (CD; n = 3 [36][37][38]), nitrite/nitric oxide (NO; n = 2 [23,31]), flow-mediated brachial dilatation (FMD; n = 2 [19,32]), the reactive hyperaemia index (RHI; n = 2 [34,38]), blood pressure complexity (n = 2 [20,21]), the heart-ankle vascular index (CAVI; n = 3 [22,26,27]), aortic pulse wave velocity (aPWV; n = 2 [18,35]), the aortic augmentation index (aAIx; n = 1 [38]), asymmetric dimethylarginine (ADMA; n = 1 [40]), homocysteine (Hcy; n = 2 [24,39]), the von Willebrand factor (vWF; n = 1…”

“…The included studies were published between 2014 and 2024. The studies were conducted in Brazil (n = 2 [18,19]), China (n = 3 [20][21][22]), Egypt (n = 1 [23]), France (n = 2 [24,25]), India (n = 1 [26]), Japan (n = 2 [26,27]), Iceland (n = 1 [28]), Italy (n = 3 [29][30][31]), Korea (n = 3 [32- A summary of the characteristics of the selected studies is presented in Table S2. The included studies were published between 2014 and 2024.…”

“…The included studies were published between 2014 and 2024. The studies were conducted in Brazil (n = 2 [18,19]), China (n = 3 [20][21][22]), Egypt (n = 1 [23]), France (n = 2 [24,25]), India (n = 1 [26]), Japan (n = 2 [26,27]), Iceland (n = 1 [28]), Italy (n = 3 [29][30][31]), Korea (n = 3 [32][33][34]), the Netherlands (n = 1 [35]), the United Kingdom (n = 2 [36,37]), Singapore (n = 1 [38]), Spain (n = 4 [39][40][41][42]), and the United States of America (n = 4 [43][44][45][46]). All of the studies that were selected were conducted in clinical settings; the included works consisted primarily of studies with a descriptive cross-sectional design.…”

“…PWV is calculated by measuring the velocity of blood pressure waves travelling along the aorta and large arteries, usually by dividing the distance by the transit time of the pressure waves at the two points of arterial recording [50]. Other similar studies [18,20,21,26,36,38,41,44,45] support this observation, demonstrating a significant increase in PWV in frail or pre-frail patients and/or a correlation between a significant increase in PWV and one or more individual elements (e.g., grip force or gait velocity) belonging to the definition criteria of Fried's frailty phenotype [51]. In addition, an adjusted analysis in another study [44] demonstrated a significant association between the frailty level and the carotid-femoral pulse wave velocity (cfPWV), further highlighting the role of arterial stiffness in frailty.…”

“…BP complexity is quantified using multiscale entropy (MSE), which incorporates a coarse-grained process to assess the variability and irregularity of blood pressure patterns at different scales [20]. Two studies conducted by Jiang et al found that lower systolic or diastolic BP complexity correlates with a higher chance of being pre-frail or frail [21]; they also demonstrated an inverse correlation between arterial stiffness and cxPA [20]. Thus, cxPA is a mediator between arterial stiffness and frailty.…”