The objective of this study was to identify predictive factors of mortality in older adults with coronavirus disease 2019 (COVID‐19), including the level of clinical frailty by using the clinical frailty scale (CFS). We analyzed medical records of all patients aged of 75 and older with a confirmed diagnosis of COVID‐19 hospitalized in our Hospital between March 3 and April 25, 2020. Standardized variables were prospectively collected, and standardized care were provided to all patients. One hundred and eighty‐six patients were included (mean 85.3 ± 5.78 year). The all cause 30‐day mortality was 30% (56/186). At admission, dead patients were more dyspneic (57% vs. 38%, p = .014), had more often an oxygen saturation less than 94% (70% vs. 47%, p < .01) and had more often a heart rate faster than 90/min (70% vs. 42%, p < .001). Mortality increased in parallel with CFS score (p = .051) (20 deaths (36%) in 7–9 category). In multivariate analysis, CFS score (odds ratio [OR] = 1.49; confidence interval [CI] 95%, 1.01–2.19; p = .046), age (OR = 1.15; CI 95%, 1.01–1.31; p = .034), and dyspnea (OR = 5.37; CI 95%, 1.33–21.68; p = .018) were associated with all‐cause 30‐day mortality. It is necessary to integrate the assessment of frailty to determine care management plan of older patients with COVID‐19, rather than the only restrictive criterion of age.
Decision making is a complex cognitive phenomenon commonly used in everyday life. Studies have shown differences in behavioral strategies in risky decision-making tasks over the course of aging. The development of functional neuroimaging has gradually allowed the exploration of the neurofunctional bases of these behaviors. The purpose of our study was to carry out a meta-analysis on the neural networks underlying risky decision making in healthy older adults. Following the PRISMA guidelines, we systematically searched for fMRI studies of decision making in older adults using risky decision-making tasks. To perform the quantitative meta-analysis, we used the revised version of the activation likelihood estimation (ALE) algorithm. A total of 620 references were selected for initial screening. Among these, five studies with a total of 98 cognitively normal older participants (mean age: 69.5 years) were included. The meta-analysis yielded two clusters. Main activations were found in the right insula, bilateral dorsolateral prefrontal cortex (dlPFC) and left orbitofrontal cortex (OFC). Despite the limited number of studies included, our meta-analysis highlights the crucial involvement of circuits associated with both emotion regulation and the decision to act. However, in contrast to the literature on young adults, our results indicate a different pattern of hemispheric lateralization in older participants. These activations can be used as a minimum pattern of activation in the risky decision-making tasks of healthy older subjects.
A better understanding of gait disorders that are associated with aging is crucial to prevent adverse outcomes. The functional study of gait remains a thorny issue due to technical constraints inherent to neuroimaging procedures, as most of them require to stay supine and motionless. Using an MRI‐compatible system of boots reproducing gait‐like plantar stimulation, we investigated the correlation between age and brain fMRI activation during simulated gait in healthy adults. Sixty‐seven right‐handed healthy volunteers aged between 20 and 77 years old (49.2 ± 18.0 years; 35 women) were recruited. Two paradigms were assessed consecutively: (a) gait‐like plantar stimulation and (b) chaotic and not gait‐related plantar stimulation. Resulting statistical parametric maps were analyzed with a multiple‐factor regression that included age and a threshold determined by Monte‐Carlo simulation to fulfill a family‐wise error rate correction of p < .05. In the first paradigm, there was an age‐correlated activation of the right pallidum, thalamus and putamen. The second paradigm showed an age‐correlated deactivation of both primary visual areas (V1). The subtraction between results of the first and second paradigms showed age‐correlated activation of the right presupplementary motor area (Brodmann Area [BA] 6) and right mid‐dorsolateral prefrontal cortex (BA9‐10). Our results show age‐correlated activity in areas that have been associated with the control of gait, highlighting the relevance of this simulation model for functional gait study. The specific progressive activation of top hierarchical control areas in simulated gait and advancing age corroborate a progressive loss of automation in healthy older adults.
Key summary pointsAim The complexity of decision-making involves many neurological functions and structures which are potentially altered by cognitive aging. Findings Our systematic review shows a decrease in processing speed in normal aging, usually compensated by experience. Nevertheless, in the case of decisions that cannot be based on previous experience, decision-making will be more difficult for older adults. Compared to younger adults, older ones will be more inclined to maintain existing achievements than try to gain potential benefits.Message Decision-making supports should take into account age-related characteristics to facilitate informed decision-making. AbstractPurpose Aging is associated with increased needs related to complex decisions, particularly in medical and social issues. However, the complexity of decision-making involves many neurological functions and structures which are potentially altered by cognitive aging. Methodology A systematic review was conducted in accordance with PRISMA guidelines to examine changes in decisionmaking occurring in normal cognitive aging. The keywords "decision making" and "normal aging" were used to find the clinical studies and literature reviews focused on these changes. Results A total of 97 articles were considered in the review, and ultimately 40 articles were selected, including 30 studies and 10 literature reviews. The data from these studies were of uneven quality and too disparate to allow meta-analysis according to PRISMA criteria. Nevertheless, a key result of the analysis is the decrease of processing speed with aging. In ambiguous decision-making situations, the alteration of the ventromedial system is associated with changes in motivation profiles. These changes can be compensated by experience. However, difficulties arise for older adults in the case of one-off decisions, which are very common in the medical or medico-social domains. Conclusions Cognitive aging is associated with a slowdown in processing speed of decision-making, especially in ambiguous situations. However, decision-making processes which are based on experience and cases in which sufficient time is available are less affected by aging. These results highlight the relativity of decision-making capacities in cognitive aging.
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