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The objective of this study was to characterize frailty and resilience in people evaluated for Post-Acute COVID-19 Syndrome (PACS), in relation to quality of life (QoL) and Intrinsic Capacity (IC). This cross-sectional, observational, study included consecutive people previously hospitalized for severe COVID-19 pneumonia attending Modena (Italy) PACS Clinic from July 2020 to April 2021. Four frailty-resilience phenotypes were built: “fit/resilient”, “fit/non-resilient”, “frail/resilient” and “frail/non-resilient”. Frailty and resilience were defined according to frailty phenotype and Connor Davidson resilience scale (CD-RISC-25) respectively. Study outcomes were: QoL assessed by means of Symptoms Short form health survey (SF-36) and health-related quality of life (EQ-5D-5L) and IC by means of a dedicated questionnaire. Their predictors including frailty-resilience phenotypes were explored in logistic regressions. 232 patients were evaluated, median age was 58.0 years. PACS was diagnosed in 173 (74.6%) patients. Scarce resilience was documented in 114 (49.1%) and frailty in 72 (31.0%) individuals. Predictors for SF-36 score < 61.60 were the phenotypes “frail/non-resilient” (OR = 4.69, CI 2.08–10.55), “fit/non-resilient” (OR = 2.79, CI 1.00–7.73). Predictors for EQ-5D-5L < 89.7% were the phenotypes “frail/non-resilient” (OR = 5.93, CI 2.64–13.33) and “frail/resilient” (OR = 5.66, CI 1.93–16.54). Predictors of impaired IC (below the mean score value) were “frail/non-resilient” (OR = 7.39, CI 3.20–17.07), and “fit/non-resilient” (OR = 4.34, CI 2.16–8.71) phenotypes. Resilience and frailty phenotypes may have a different impact on wellness and QoL and may be evaluated in people with PACS to identify vulnerable individuals that require suitable interventions.
Background Elderly people living with HIV show a significant prevalence of multimorbidity, polypharmacy and frailty that increase the risk of disability. Telehealth has been suggested as a new tool to monitor people living with HIV in the COVID era, but its effectiveness in elderly is unknown. The aim of this study was two-fold: to explore feasibility of a telephone interview and its capability to collect relevant geriatric outcomes. Methods Assessed health domains included comorbidities, falls, urinary incontinence, antiretroviral drugs exposure and comedications (polypharmacy), and the following patient reported outcomes: quality of life, intrinsic capacity, and resilience. Results 214 (70.6%) answered and completed the interview. During confinement period, 57 (26.7%) of people switched antiretroviral therapy : 119 (55.4%) to dual therapy regimens and 95 (44.6%) to triple regimens. Prevalence of geriatric syndromes were falls in 31 cases (14.7%), urinary incontinence in 48 cases (22.7%) and polypharmacy 122 cases (57.2%). Mean Health-related Quality of Life score was mildly impaired (0,88%) with good concordance of Helath-related Quality of Life self-perception in a visual analogue scale (8/10) (r=+0.348; p <0.01). Intrinsic capacity depicted impaired functional ability in multiple domains (0.737 ) and Resilience (CD-RISC) was suboptimal (0.6). Conclusions A structured telephone call was feasible in elderly people living with HIV and allowed to collect clinically meaningful geriatric health domains when face-to-face visits are not needed or discouraged.
Background The objective of this study was to characterize frailty and resilience in people evaluated for Post-Acute COVID-19 Syndrome (PACS), in relation to quality of life (QoL) and Intrinsic Capacity (IC). Methods This cross-sectional, observational, study included consecutive people previously hospitalized for severe COVID-19 pneumonia attending Modena (Italy) PACS Clinic from July 2020 to April 2021. Four frailty-resilience phenotypes were built: “fit/resilient”, “fit/non-resilient”, “frail/resilient” and “frail/non-resilient”. Frailty and resilience were defined according to frailty phenotype and Connor Davidson resilience scale (CD-RISC-25) respectively. Study outcomes were: QoL assessed by means of Symptoms Short form health survey (SF-36) and health-related quality of life (EQ-5D-5L) and IC by means of a dedicated questionnaire. Their predictors including frailty-resilience phenotypes were explored in logistic regressions. Results 232 patients were evaluated, median age was 58.0 years. PACS was diagnosed in 173 (74.6%) patients. Scarce resilience was documented in 114 (49.1%) and frailty in 72 (31.0%) individuals. Table 1 shows demographic, anthropometric and clinical characteristics, comorbidities and patient-reported outcomes according to four frailty-resilience phenotypes. With regards to study outcomes, Figure 1 depicts in radar graphs, mean scores of each domain of SF-36 (1A), EQ-5D5L (1B) and IC (1C). Figures shows polygon areas for each frailty/resilience phenotypes. Progressive increase of mean scores of each domain are plotted in the vertices of polygons, from the lowest (near the center) in frail and non-resilient, to highest (towards periphery) in fit and resilient. Multivariate logistic analyses were used to identify predictors of the total scores of SF-36 (Figure 2A), EQ-5D5L (Figure 2B) and IC (Figure 2C). Conclusion Resilience is complementary to frailty in the identification of clinical phenotypes with different impact on wellness and QoL. Frailty and resilience should be evaluated in hospitalized COVID-19 patients to identify vulnerable individuals to prioritize urgent health interventions in people with PACS. Funding This study is supported by a Gilead Sciences Inc. unrestricted grant. Disclosures All Authors: No reported disclosures.
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