Quality of life and intrinsic capacity in patients with post-acute COVID-19 syndrome is in relation to frailty and resilience phenotypes

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.

1070. Quality of life and intrinsic capacity in patients with post-acute COVID-19 syndrome is in relation to frailty and resilience phenotypes

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.

Resilience and Frailty in People Living With HIV During the COVID Era: Two Complementary Constructs Associated With Health-Related Quality of Life

BACKGROUND

Resilience is defined as an individual's positive adaptation to stressors. The COVID-19 pandemic represents a generalized stressor which may affect differently people living with HIV (PLWH). The objective of this study was to characterize resilience in PLWH with particular regarding the identification of frailty-resilience phenotypes, which may differently affect health-related quality of life (HR-QoL).

METHODS

This was an observational study of PLWH attending Modena HIV Metabolic Clinic. Frailty was assessed in 2019, before the onset of the COVID-19 pandemic by using 37-Item frailty index ranging from 0 to 1. The frailty index score was categorized as fit (<0.25) or frail (>0.25). In January 2021, PLWH were offered to complete a set of electronic questionnaires including the CD-RISC-25 for resilience and EQ-5D5L and SF-36 for HR-QoL. Resilience was defined as CD-RISC-25 score >75.7 (ranging from 0 to 100).

RESULTS

Of 800 PLWH reached by mail, 575 (72%) completed the questionnaires. The median age and HIV duration were 54.5 and 24.3 years, respectively. Impaired resilience was associated with loneliness [odds ratio (OR = 2.39; 1.20 to 4.76, P < 0.001)]. Predictors for EQ-5D5L <89.7% were the phenotypes "frail/nonresilient" [OR = 5.21, 95% confidence interval (CI): 2.62 to 10.33] and "fit/nonresilient" (OR = 5.48, 95% CI: 2.8 to 10.74). Predictors for SF-36 <64.40 were the phenotypes "frail/nonresilient" (OR = 7.43, 95% CI: 2.57 to 21.22) and "fit/nonresilient" (OR = 6.27, 95% CI: 2.17 to 18.16). Both models were corrected for age, sex, HIV duration, and nadir CD4.

CONCLUSIONS

Resilience characterizes the well-being of PLWH during the COVID-19 crisis. This construct is complementary to frailty in the identification of clinical phenotypes with different impacts on HR-QoL.

Clinical Research Nurse involvement to foster a community based transcultural research in RODAM European study

BACKGROUND AND AIM OF THE WORK

The Clinical Research Nurse (CRN) can be considered the fulcrum of clinical studies, being a vital link between patient, principal investigator, study sponsor and administrative staff. The clinical research's way is still long and the contribution that CRNs can provide is crucial. In Italy, a CRN was employed in the study: Research on Obesity & Type 2 Diabetes among African Migrants (RODAM). The aim of the paper is to explore and describe the experience of this involvement.

METHODS

The CRN managed the project in order to gain a complete collaboration from the Ghanaian population. From the first contact, the CRN decided to adopt a transcultural approach with the aim to create a relationship of understanding, mutual trust respect for each other's cultural diversity. The CRN also used organizational, technical and linguistic skills.

RESULTS

The day-to-day trial management from CRN included the following activities: obtaining local Ethics Committee study approval; recruiting the study staff; planning the study activities; identifying potential study participants; collaborating with the mediators; managing contacts with other RODAM centers; conducting a follow-up of patients. The most important results of CRN involvement have been the empowerment of Ghanaian community and the effective healthcare promotion.

CONCLUSIONS

The project encouraged the Ghanaian community to increase their healthcare awareness and encouraged the Ghanaian population to create new strategies to face the hard health challenges.