Autonomic Nervous System and Cognitive Impairment in Older Patients: Evidence From Long-Term Heart Rate Variability in Real-Life Setting

Abstract

Background: In geriatric age, cognitive impairment and cardiovascular disorders are frequent comorbidities. Age-related anatomical and functional cardiac changes, including the autonomic system, could interfere with the control of different cognitive domains. Therefore, we assess the relationship between long-term heart rate variability (HRV), as a measure of autonomic nervous system (ANS) functioning, and cognitive performance in elderly patients representative of outpatients in a real-life setting. Methods: Of 155 elderly outpatients (aged >65 years) screened, 117 enrolled patients underwent anthropometric evaluation, cardiac assessment by 12-lead electrocardiogram, 24-h ECG recording, and blood pressure (BP) measurement, as well as global cognitive evaluation by a standardized multidimensional assessment, including the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment test (MoCA). HRV analysis was performed on 24-h ECG recordings focusing on time-domain indices [Standard deviation of the NN intervals (SDNN), standard deviations of 5-min mean values of the NN intervals for each 5-min interval (SDANN), and root mean squares of successive differences of the NN intervals (RMSSD)] and on frequency-domain measurements [heart rate (HR), low frequency (LF), high frequency (HF), and LF/HF]. Multivariate linear analysis was used to explore the influence of the HRV significant variables on MMSE and MoCA test values. Results: The MMSE and MoCA scores were both significantly and positively correlated with the sympathetic system parameters (SDNN, SDANN, LF, and LF/HF ratio), but not with the parasympathetic system parameters (RMSSD and HF). Multivariate analysis confirms this relationship. Conclusions: Our results show that, in a representative real-life community elderly population, an increased sympathetic activity, but not decreased vagal activity, is

Association Between Postoperative Long-Term Heart Rate Variability and Postoperative Delirium in Elderly Patients Undergoing Orthopedic Surgery: A Prospective Cohort Study

“…Observed to be associated with cognitive function (Dalise et al, 2020), HF and LF were selected for logistic regression analyses. In addition, as SDNNI, VLF, and ULF were associated with POD at a significance level of less than 0.2, they were also included in the planned binary logistic regression analyses.…”

“…Although studies have shown that HRV is associated with cognitive function in older patients (Kim et al, 2018;Dalise et al, 2020), there are few studies concerning the correlation between long-term HRV parameters and POD. As is proved in previous researches, HRV decreases to varying degrees in elderly patients after surgery, indicating that ANS activity and circadian rhythm were impaired after surgery (Marsch et al, 1994;Amar et al, 1998;Kärkelä et al, 2002).…”

Heart Rate Variability as an Index of Differential Brain Dynamics at Rest and After Acute Stress Induction

“…Concurrent analyses of heart rate (HR) or heart rate variability (HRV) and blood-oxygen-level dependent (BOLD) signal at rest or during an emotional, cognitive, or motor task indicated that some additional cortical regions, such as dorsolateral PFC (dlPFC), exert influence on HRV in coordination with CAN, although they are not closely connected to the autonomic centers in the brain stem ( Napadow et al, 2008 ; Smith et al, 2014 ; Young et al, 2017 ). HRV corresponds to the variation in the time interval between two successive R waves and has been associated with the various cognitive ( Hansen et al, 2009 ; Dalise et al, 2020 ) and affective functions ( Melzig et al, 2009 ; Miller et al, 2019 ). Thayer and Lane (2000) put forward the neurovisceral integration (NVI) model centered on CAN regions and provided a framework for understanding the integration of cognitive, affective, and autonomic information.…”

Predicting cognitive impairment in outpatients with epilepsy using machine learning techniques

“…This could be due to two scales focusing on the different aspects of function. The MMSE focuses on memory, while the MoCA focuses on executive function 19 . It is possible that different factors may contribute to various aspects of cognitive function decline 20 .…”