Age-Related Changes in Cortical Connectivity During Surgical Anesthesia - Li, Duan; Puglia, Mike P.; Lapointe, Andrew P.; Ip, Ka I; Zierau, Mackenzie; McKinney, Amy; Vlisides, Phillip E. (Frontiers in Aging Neuroscience, 2020)
An advanced understanding of the neurophysiologic changes that occur with aging may help improve perioperative care for older, vulnerable patients. The objective of this study was to determine age-related changes in cortical connectivity patterns during surgical anesthesia. This was a substudy analysis of a prospective, observational study characterizing cortical connectivity during surgical anesthesia in adult patients (n=45) via whole-scalp (16-channel) electroencephalography. Functional connectivity was estimated using weighted phase lag index, which was classified into a discrete set of states through k-means analysis. Temporal dynamics were quantified by occurrence rate and state transition probabilities. The mean global, connectivity state transition probability (13.4% [±8.1]) was not correlated with age (ρ = 0.100, P=0.513). Increasing age was inversely correlated with prefrontal-frontal alpha-beta connectivity (ρ = -0.446, P=0.002) and positively correlated with frontal-parietal theta connectivity (ρ = 0.414, P=0.005). After adjusting for anesthetic-related confounders, prefrontal-frontal alpha-beta connectivity remained significantly associated with age (β = -0.625, 95% CI -0.99 to -0.26; P=0.001), while frontal-parietal theta connectivity was no longer significant (β = 0.436, 95% CI -0.03 to 0.90; P=0.066). Specific transition states were also examined. Between frontal-parietal connectivity states, transitioning from theta-alpha to theta-dominated connectivity positively correlated with age (ρ = 0.545, P=0.001). Exploratory analysis in subsets of relatively young and old patients also demonstrated an increased propensity for frontal-parietal theta connectivity with older age and reduced prefrontal-frontal alpha-beta connectivity. Dynamic connectivity states during surgical anesthesia, particularly involving alpha and theta bandwidths, may be an informative measure to assess neurophysiologic changes that occur with aging.