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Background: While social distancing policies protect older adults with advanced chronic kidney disease (CKD) from exposure to COVID-19, reduced social interaction may also have unintended consequences.Methods: To identify subgroups of patients at risk for unintended health consequences of social distancing, we conducted a cross-sectional analysis of data from a national cohort study of older veterans with advanced CKD (n = 223). Characteristics included activities of daily living (ADLs), instrumental ADLs (IADLs), cognition score, depression score, social support, financial stress, symptom burden, and number of chronic conditions. Unintended consequences of social distancing included restricted Life Space mobility, low willingness for video telehealth, reduced in-person contact with caregivers, and food insecurity. We identified subgroups of patients at risk of unintended consequences using model-based recursive partitioning (MoB).Results: Participants had a mean age of 77.9 years, 64.6% were white, and 96.9% were male. Overall, 22.4% of participants had restricted Life Space, 33.9% reported low willingness for video telehealth, 19.0% reported reduced caregiver contact, and 3.2% reported food insecurity. For Life Space restriction, 4 subgroups partitioned (ie, split) by IADL difficulty, cognition score, and ADL difficulty were identified. The highest rate of restricted Life Space was 54.7% in the subgroup of participants with >3 IADL difficulties. For low willingness for telehealth and reduced caregiver contact, separate models identified 2 subgroups split by cognition score and depression score, respectively.Conclusions: Measures of function, cognition, and depressive symptoms may identify older adults with advanced CKD who are at higher risk for unintended health consequences of social distancing. [ABSTRACT FROM AUTHOR]

Background: Clinically similar older adults demonstrate variable responses to health stressors, heterogeneity attributable to differences in physical resilience. However, molecular mechanisms underlying physical resilience are unknown. We previously derived a measure of physical resilience after hip fracture-the expected recovery differential (ERD)-that captures the difference between actual recovery and predicted recovery. Starting with biomarkers associated with physical performance, morbidity, mortality, and hip fracture, we evaluated associations with the ERD to identify biomarkers of physical resilience after hip fracture.Methods: In the Baltimore Hip Studies (N = 304) sera, we quantified biomarkers of inflammation (TNFR-I, TNFR-II, sVCAM-1, and IL-6), metabolic and mitochondrial function (non-esterified fatty acids, lactate, ketones, acylcarnitines, free amino acids, and IGF-1), and epigenetic dysregulation (circulating microRNAs). We used principal component analysis, canonical correlation, and least absolute shrinkage and selection operator regression (LASSO) to identify biomarker associations with better-than-expected recovery (greater ERD) after hip fracture.Results: Participants with greater ERD were more likely to be women and less disabled at baseline. The complete biomarker set explained 37% of the variance in ERD (p < .001) by canonical correlation. LASSO regression identified a biomarker subset that accounted for 27% of the total variance in the ERD and included a metabolic factor (aspartate/asparagine, C22, C5:1, lactate, glutamate/mine), TNFR-I, miR-376a-3p, and miR-16-5p.Conclusions: We identified a set of biomarkers that explained 27% of the variance in ERD-a measure of physical resilience after hip fracture. These ERD-associated biomarkers may be useful in predicting physical resilience in older adults facing hip fracture and other acute health stressors. [ABSTRACT FROM AUTHOR]

There is limited research examining the impact of visual impairment (VI) on older adults while considering the complexities of aging, leaving gaps in our understanding of how health consequences of VI might be averted. We created a framework integrating concepts from disability, geriatrics, and ophthalmology that conceptualizes how VI challenges successful aging. Here, VI influences multiple functional domains, and increases the risk of negative health outcomes. This model acknowledges that common causes, such as risk factors that affect eyes and other systems simultaneously, may also drive the relationship between VI and health outcomes. Finally, the model highlights how the impact of VI on aging outcomes can be addressed at multiple intervention points. [ABSTRACT FROM AUTHOR]

Background: Approaches for quantifying physical resilience in older adults have not been described.Methods: We apply two conceptual approaches to defining physical resilience to existing longitudinal data sets in which outcomes are measured after an acute physical stressor. A "recovery phenotype" approach uses statistical methods to describe how quickly and completely a patient recovers. Statistical methods using a recovery phenotype approach can consider multiple outcomes simultaneously in a composite score (eg, factor analysis and principal components analysis) or identify groups of patients with similar recovery trajectories across multiple outcomes (eg, latent class profile analysis). An "expected recovery differential" approach quantifies how patients' actual outcomes are compared to their predicted outcome based on a population-derived model and their individual clinical characteristics at the time of the stressor.Results: Application of the approaches identified different participants as being the most or least physically resilient. In the viral respiratory cohort (n = 186) weighted kappa for agreement across resilience quartiles was 0.37 (0.27-0.47). The expected recovery differential approach identified a group with more comorbidities and lower baseline function as highly resilient. In the hip fracture cohort (n = 541), comparison of the expected recovery differentials across 10 outcome measures within individuals provided preliminary support for the hypothesis that there is a latent resilience trait at the whole-person level.Conclusions: We posit that recovery phenotypes may be useful in clinical applications such as prediction models because they summarize the observed outcomes across multiple measures. Expected recovery differentials offer insight into mechanisms behind physical resilience not captured by age and other comorbidities. [ABSTRACT FROM AUTHOR]

Background: Resilience has been described in the psychosocial literature as the capacity to maintain or regain well-being during or after adversity. Physical resilience is a newer concept that is highly relevant to successful aging. Our objective was to characterize the emerging construct of resilience as it pertains to physical health in older adults, and to identify gaps and opportunities to advance research in this area.Methods: We conducted a systematic review to identify English language papers published through January 2015 that apply the term "resilience" in relation to physical health in older adults. We applied a modified framework analysis to characterize themes in implicit or explicit definitions of physical resilience.Results: Of 1,078 abstracts identified, 49 articles met criteria for inclusion. Sixteen were letters or concept papers, and only one was an intervention study. Definitions of physical resilience spanned cellular to whole-person levels, incorporated many outcome measures, and represented three conceptual themes: resilience as a trait, trajectory, or characteristic/capacity.Conclusions: Current biomedical literature lacks consensus on how to define and measure physical resilience. We propose a working definition of physical resilience at the whole person level: a characteristic which determines one's ability to resist or recover from functional decline following health stressor(s). We present a conceptual framework that encompasses the related construct of physiologic reserve. We discuss gaps and opportunities in measurement, interactions across contributors to physical resilience, and points of intervention. [ABSTRACT FROM AUTHOR]

The article discusses the use of physical robustness and resilience as key components of measuring the ability of older people to resist or recover from functional decline following health stressors. Topics addressed include the difference between the terms resistance to and recovery from, the use of the term 'robustness' in the ability to resist the deviation from baseline and in a low risk of developing a particular disease, and the distinction between disease development and symptoms.

A response from the author of the article regarding the biological resilience and recovery of older patients who are hospitalized with acute illnesses, is presented.