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.

Comparison between first and second wave of COVID-19 outbreak in older people: the COPE multicentre European observational cohort study.

BACKGROUND: Effective shielding measures and virus mutations have progressively modified the disease between the waves, likewise healthcare systems have adapted to the outbreak. Our aim was to compare clinical outcomes for older people with COVID-19 in Wave 1 (W1) and Wave 2 (W2). METHODS: All data, including the Clinical Frailty Scale (CFS), were collected for COVID-19 consecutive patients, aged ≥65, from 13 hospitals, in W1 (February-June 2020) and W2 (October 2020-March 2021). The primary outcome was mortality (time to mortality and 28-day mortality). Data were analysed with multilevel Cox proportional hazards, linear and logistic regression models, adjusted for wave baseline demographic and clinical characteristics. RESULTS: Data from 611 people admitted in W2 were added to and compared with data collected during W1 (N = 1340). Patients admitted in W2 were of similar age, median (interquartile range), W2 = 79 (73-84); W1 = 80 (74-86); had a greater proportion of men (59.4% vs. 53.0%); had lower 28-day mortality (29.1% vs. 40.0%), compared to W1. For combined W1-W2 sample, W2 was independently associated with improved survival: time-to-mortality adjusted hazard ratio (aHR) = 0.78 [95% confidence interval (CI) 0.65-0.93], 28-day mortality adjusted odds ratio = 0.80 (95% CI 0.62-1.03). W2 was associated with increased length of hospital stay aHR = 0.69 (95% CI 0.59-0.81). Patients in W2 were less frail, CFS [adjusted mean difference (aMD) = -0.50, 95% CI -0.81, -0.18], as well as presented with lower C-reactive protein (aMD = -22.52, 95% CI -32.00, -13.04). CONCLUSIONS: COVID-19 older adults in W2 were less likely to die than during W1. Patients presented to hospital during W2 were less frail and with lower disease severity and less likely to have renal decline.

Frailty is associated with poor mental health 1 year after hospitalisation with COVID-19

Background Frailty is associated with long-term physical deterioration after COVID-19. Mental health recovery has been less well investigated. Early studies have shown minimal effect from the virus, although studies have not focused on whether people living with frailty may have different psychiatric outcomes. We aimed to examine the effect of living with frailty on mental health outcomes one year after hospital with COVID-19. Methods We undertook a multicentre cross-sectional study of people admitted with COVID-19. We assessed quality of life (ICECAP-O and MRC), psychiatric symptoms including: generalised anxiety (GAD-7), depression (Patient Health Questionnaire-9), and trauma (Trauma Screening Questionnaire). Frailty was measured using the Clinical Frailty Scale (CFS). We used a multivariable mixed-effects logistic and linear regression to examine the adjusted odds ratio (aOR) and adjusted mean difference (aMD). Results From eight hospitals 224 participants consented. Median follow-up time from admission 358 days (IQR 153–418), mean age 63.8 (SD = 13.7), 34.8% female (n = 78), and 43.7% living with frailty (n = 98 CFS 4–8). People living with frailty were significantly more likely to have symptoms of anxiety aOR = 5.72 (95% CI 1.71–19.13), depression aOR = 2.52 (95% CI 1.59–14.91), post-traumatic stress disorder aMD = 1.16 (95% CI 0.47, 1.85), and worse quality of life aMD = 1.06 (95% CI 0.76–1.36). Limitations Patient-rated symptoms were captured rather than formal mental health diagnoses. CFS has not been validated in under 65-year-olds. Conclusions Living with frailty is associated with significant psychiatric morbidity and reduced wellbeing one year after COVID-19 hospital admission. We recommend clinical follow-up after COVID-19 for people living with frailty should include a psychiatric assessment.

Metabolic-Associated Fatty Liver Disease Is Highly Prevalent in the Postacute COVID Syndrome.

BACKGROUND: A proposal has recently been advanced to change the traditional definition of nonalcoholic fatty liver disease to metabolic-associated fatty liver disease (MAFLD), to reflect the cluster of metabolic abnormalities that may be more closely associated with cardiovascular risk. Long coronavirus disease 2019 (COVID-19) is a smoldering inflammatory condition, characterized by several symptom clusters. This study aims to determine the prevalence of MAFLD in patients with postacute COVID syndrome (PACS) and its association with other PACS-cluster phenotypes. METHODS: We included 235 patients observed at a single university outpatient clinic. The diagnosis of PACS was based on ≥1 cluster of symptoms: respiratory, neurocognitive, musculoskeletal, psychological, sensory, and dermatological. The outcome was prevalence of MAFLD detected by transient elastography during the first postdischarge follow-up outpatient visit. The prevalence of MAFLD at the time of hospital admission was calculated retrospectively using the hepatic steatosis index. RESULTS: Of 235 patients, 162 (69%) were men (median age 61). The prevalence of MAFLD was 55.3% at follow-up and 37.3% on admission (P < .001). Insulin resistance (odds ratio [OR] = 1.5; 95% confidence interval [CI], 1.14-1.96), body mass index (OR = 1.14; 95% CI, 1.04-1.24), and the metabolic syndrome (OR = 2.54; 95% CI, 1.13-5.68) were independent predictors of MAFLD. The number of PACS clusters was inversely associated with MAFLD (OR = 0.86; 95% CI, .76-0.97). Thirty-one patients (13.2%) had MAFLD with no other associated PACS clusters. All correlations between MAFLD and other PACS clusters were weak. CONCLUSIONS: Metabolic-associated fatty liver disease was highly prevalent after hospital discharge and may represent a specific PACS-cluster phenotype, with potential long-term metabolic and cardiovascular health implications.

Multiple house occupancy is associated with mortality in hospitalized patients with COVID-19.

BACKGROUND: In response to the COVID-19 pandemic, many countries mandated staying at home to reduce transmission. This study examined the association between living arrangements (house occupancy numbers) and outcomes in COVID-19. METHODS: Study population was drawn from the COPE study, a multicentre cohort study. House occupancy was defined as: living alone; living with one other person; living with multiple other people; or living in a nursing/residential home. Outcomes were time from admission to mortality and discharge (Cox regression), and Day 28 mortality (logistic regression) analyses were adjusted for key comorbidities and covariates including admission: age, sex, smoking, heart failure, admission C-reactive protein (CRP), chronic obstructive pulmonary disease, estimated glomerular filtration rate, frailty and others. RESULTS: A total of 1584 patients were included from 13 hospitals across UK and Italy: 676 (42.7%) were female, 907 (57.3%) were male, median age was 74 years (range: 19-101). At 28 days, 502 (31.7%) had died. Median admission CRP was 67, 82, 79.5 and 83 mg/l for those living alone, with someone else, in a house of multiple occupancy and in a nursing/residential home, respectively. Compared to living alone, living with anyone was associated with increased mortality: within a couple [adjusted hazard ratios (aHR) = 1.39, 95% confidence intervals (CI) 1.09-1.77, P = 0.007]; living in a house of multiple occupancy (aHR = 1.67, 95% CI 1.17-2.38, P = 0.005); and living in a residential home (aHR = 1.36, 95% CI 1.03-1.80, P = 0.031). CONCLUSION: For patients hospitalized with COVID-19, those living with one or more people had an increased association with mortality, they also exhibited higher CRP indicating increased disease severity suggesting they delayed seeking care.

The role of C-reactive protein as a prognostic marker in COVID-19.

BACKGROUND: C-reactive protein (CRP) is a non-specific acute phase reactant elevated in infection or inflammation. Higher levels indicate more severe infection and have been used as an indicator of COVID-19 disease severity. However, the evidence for CRP as a prognostic marker is yet to be determined. The aim of this study is to examine the CRP response in patients hospitalized with COVID-19 and to determine the utility of CRP on admission for predicting inpatient mortality. METHODS: Data were collected between 27 February and 10 June 2020, incorporating two cohorts: the COPE (COVID-19 in Older People) study of 1564 adult patients with a diagnosis of COVID-19 admitted to 11 hospital sites (test cohort) and a later validation cohort of 271 patients. Admission CRP was investigated, and finite mixture models were fit to assess the likely underlying distribution. Further, different prognostic thresholds of CRP were analysed in a time-to-mortality Cox regression to determine a cut-off. Bootstrapping was used to compare model performance [Harrell's C statistic and Akaike information criterion (AIC)]. RESULTS: The test and validation cohort distribution of CRP was not affected by age, and mixture models indicated a bimodal distribution. A threshold cut-off of CRP ≥40 mg/L performed well to predict mortality (and performed similarly to treating CRP as a linear variable). CONCLUSIONS: The distributional characteristics of CRP indicated an optimal cut-off of ≥40 mg/L was associated with mortality. This threshold may assist clinicians in using CRP as an early trigger for enhanced observation, treatment decisions and advanced care planning.

Routine use of immunosuppressants is associated with mortality in hospitalised patients with COVID-19.

BACKGROUND: Whilst there is literature on the impact of SARS viruses in the severely immunosuppressed, less is known about the link between routine immunosuppressant use and outcome in COVID-19. Consequently, guidelines on their use vary depending on specific patient populations. METHODS: The study population was drawn from the COPE Study (COVID-19 in Older People), a multicentre observational cohort study, across the UK and Italy. Data were collected between 27 February and 28 April 2020 by trained data-collectors and included all unselected consecutive admissions with COVID-19. Load (name/number of medications) and dosage of immunosuppressant were collected along with other covariate data. Primary outcome was time-to-mortality from the date of admission (or) date of diagnosis, if diagnosis was five or more days after admission. Secondary outcomes were Day-14 mortality and time-to-discharge. Data were analysed with mixed-effects, Cox proportional hazards and logistic regression models using non-users of immunosuppressants as the reference group. RESULTS: In total 1184 patients were eligible for inclusion. The median (IQR) age was 74 (62-83), 676 (57%) were male, and 299 (25.3%) died in hospital (total person follow-up 15,540 days). Most patients exhibited at least one comorbidity, and 113 (~10%) were on immunosuppressants. Any immunosuppressant use was associated with increased mortality: aHR 1.87, 95% CI: 1.30, 2.69 (time to mortality) and aOR 1.71, 95% CI: 1.01-2.88 (14-day mortality). There also appeared to be a dose-response relationship. CONCLUSION: Despite possible indication bias, until further evidence emerges we recommend adhering to public health measures, a low threshold to seek medical advice and close monitoring of symptoms in those who take immunosuppressants routinely regardless of their indication. However, it should be noted that the inability to control for the underlying condition requiring immunosuppressants is a major limitation, and hence caution should be exercised in interpretation of the results. PLAIN LANGUAGE SUMMARY: Regular Use of Immune Suppressing Drugs is Associated with Increased Risk of Death in Hospitalised Patients with COVID-19 Background: We do not have much information on how the COVID-19 virus affects patients who use immunosuppressants, drugs which inhibit or reduce the activity of the immune system. There are various conflicting views on whether immune-suppressing drugs are beneficial or detrimental in patients with the disease. Methods: This study collected data from 10 hospitals in the UK and one in Italy between February and April 2020 in order to identify any association between the regular use of immunosuppressant medicines and survival in patients who were admitted to hospital with COVID-19. Results: 1184 patients were included in the study, and 10% of them were using immunosuppressants. Any immunosuppressant use was associated with increased risk of death, and the risk appeared to increase if the dose of the medicine was higher. Conclusion: We therefore recommend that patients who take immunosuppressant medicines routinely should carefully adhere to social distancing measures, and seek medical attention early during the COVID-19 pandemic.

The Clinical Frailty Scale: Estimating the Prevalence of Frailty in Older Patients Hospitalised with COVID-19. The COPE Study.

Frailty assessed using Clinical Frailty Scale (CFS) is a good predictor of adverse clinical events including mortality in older people. CFS is also an essential criterion for determining ceilings of care in people with COVID-19. Our aims were to assess the prevalence of frailty in older patients hospitalised with COVID-19, their sex and age distribution, and the completion rate of the CFS tool in evaluating frailty. Methods: Data were collected from thirteen sites. CFS was assessed routinely at the time of admission to hospital and ranged from 1 (very fit) to 9 (terminally ill). The completion rate of the CFS was assessed. The presence of major comorbidities such as diabetes and cardiovascular disease was noted. Results: A total of 1277 older patients with COVID-19, aged ≥ 65 (79.9 ± 8.1) years were included in the study, with 98.5% having fully completed CFS. The total prevalence of frailty (CFS ≥ 5) was 66.9%, being higher in women than men (75.2% vs. 59.4%, p < 0.001). Frailty was found in 161 (44%) patients aged 65-74 years, 352 (69%) in 75-84 years, and 341 (85%) in ≥85 years groups, and increased across the age groups (<0.0001, test for trend). Conclusion: Frailty was prevalent in our cohort of older people admitted to hospital with COVID-19. This indicates that older people who are also frail, who go on to contract COVID-19 may have disease severity significant enough to warrant hospitalization. These data may help inform health care planners and targeted interventions and appropriate management for the frail older person.

The influence of ACE inhibitors and ARBs on hospital length of stay and survival in people with COVID-19.

OBJECTIVE: During the COVID-19 pandemic the continuation or cessation of angiotensin-converting enzyme inhibitors (ACEi) and angiotensin receptor blockers (ARBs) has been contentious. Mechanisms have been proposed for both beneficial and detrimental effects. Recent studies have focused on mortality with no literature having examined length of hospital stay. The aim of this study was to determine the influence of ACEi and ARBs on COVID-19 mortality and length of hospital stay. METHODS: COPE (COVID-19 in Older People) is a multicenter observational study including adults of all ages admitted with either laboratory or clinically confirmed COVID-19. Routinely generated hospital data were collected. Primary outcome: mortality; secondary outcomes: Day-7 mortality and length of hospital stay. A mixed-effects multivariable Cox's proportional baseline hazards model and logistic equivalent were used. RESULTS: 1371 patients were included from eleven centres between 27th February to 25th April 2020. Median age was 74 years [IQR 61-83]. 28.6% of patients were taking an ACEi or ARB. There was no effect of ACEi or ARB on inpatient mortality (aHR = 0.85, 95%CI 0.65-1.11). For those prescribed an ACEi or ARB, hospital stay was significantly reduced (aHR = 1.25, 95%CI 1.02-1.54, p = 0.03) and in those with hypertension the effect was stronger (aHR = 1.39, 95%CI 1.09-1.77, p = 0.007). CONCLUSIONS: Patients and clinicians can be reassured that prescription of an ACEi or ARB at the time of COVID-19 diagnosis is not harmful. The benefit of prescription of an ACEi or ARB in reducing hospital stay is a new finding.

Study protocol for the COPE study: COVID-19 in Older PEople: the influence of frailty and multimorbidity on survival. A multicentre, European observational study.

INTRODUCTION: This protocol describes an observational study which set out to assess whether frailty and/or multimorbidity correlates with short-term and medium-term outcomes in patients diagnosed with COVID-19 in a European, multicentre setting. METHODS AND ANALYSIS: Over a 3-month period we aim to recruit a minimum of 500 patients across 10 hospital sites, collecting baseline data including: patient demographics; presence of comorbidities; relevant blood tests on admission; prescription of ACE inhibitors/angiotensin receptor blockers/non-steroidal anti-inflammatory drugs/immunosuppressants; smoking status; Clinical Frailty Score (CFS); length of hospital stay; mortality and readmission. All patients receiving inpatient hospital care >18 years who receive a diagnosis of COVID-19 are eligible for inclusion. Long-term follow-up at 6 and 12 months is planned. This will assess frailty, quality of life and medical complications.Our primary analysis will be short-term and long-term mortality by CFS, adjusted for age (18-64, 65-80 and >80) and gender. We will carry out a secondary analysis of the primary outcome by including additional clinical mediators which are determined statistically important using a likelihood ratio test. All analyses will be presented as crude and adjusted HR and OR with associated 95% CIs and p values. ETHICS AND DISSEMINATION: This study has been registered, reviewed and approved by the following: Health Research Authority (20/HRA1898); Ethics Committee of Hospital Policlinico Modena, Italy (369/2020/OSS/AOUMO); Health and Care Research Permissions Service, Wales; and NHS Research Scotland Permissions Co-ordinating Centre, Scotland. All participating units obtained approval from their local Research and Development department consistent with the guidance from their relevant national organisation.Data will be reported as a whole cohort. This project will be submitted for presentation at a national or international surgical and geriatric conference. Manuscript(s) will be prepared following the close of the project.

The Clinical Frailty Scale: Estimating the Prevalence of Frailty in Older Patients Hospitalised with COVID-19. The COPE Study

Frailty assessed using Clinical Frailty Scale (CFS) is a good predictor of adverse clinical events including mortality in older people. CFS is also an essential criterion for determining ceilings of care in people with COVID-19. Our aims were to assess the prevalence of frailty in older patients hospitalised with COVID-19, their sex and age distribution, and the completion rate of the CFS tool in evaluating frailty. Methods: Data were collected from thirteen sites. CFS was assessed routinely at the time of admission to hospital and ranged from 1 (very fit) to 9 (terminally ill). The completion rate of the CFS was assessed. The presence of major comorbidities such as diabetes and cardiovascular disease was noted. Results: A total of 1277 older patients with COVID-19, aged ≥65 (79.9 ±8.1) years were included in the study, with 98.5% having fully completed CFS. The total prevalence of frailty (CFS ≥5) was 66.9%, being higher in women than men (75.2% vs. 59.4%, p <0.001). Frailty was found in 161 (44%) patients aged 65-74 years, 352 (69%) in 75-84 years, and 341 (85%) in ≥85 years groups, and increased across the age groups (<0.0001, test for trend). Conclusion: Frailty was prevalent in our cohort of older people admitted to hospital with COVID-19. This indicates that older people who are also frail, who go on to contract COVID-19 may have disease severity significant enough to warrant hospitalization. These data may help inform health care planners and targeted interventions and appropriate management for the frail older person.

The effect of frailty on survival in patients with COVID-19 (COPE): a multicentre, European, observational cohort study.

BACKGROUND: The COVID-19 pandemic has placed unprecedented strain on health-care systems. Frailty is being used in clinical decision making for patients with COVID-19, yet the prevalence and effect of frailty in people with COVID-19 is not known. In the COVID-19 in Older PEople (COPE) study we aimed to establish the prevalence of frailty in patients with COVID-19 who were admitted to hospital and investigate its association with mortality and duration of hospital stay. METHODS: This was an observational cohort study conducted at ten hospitals in the UK and one in Italy. All adults (≥18 years) admitted to participating hospitals with COVID-19 were included. Patients with incomplete hospital records were excluded. The study analysed routinely generated hospital data for patients with COVID-19. Frailty was assessed by specialist COVID-19 teams using the clinical frailty scale (CFS) and patients were grouped according to their score (1-2=fit; 3-4=vulnerable, but not frail; 5-6=initial signs of frailty but with some degree of independence; and 7-9=severe or very severe frailty). The primary outcome was in-hospital mortality (time from hospital admission to mortality and day-7 mortality). FINDINGS: Between Feb 27, and April 28, 2020, we enrolled 1564 patients with COVID-19. The median age was 74 years (IQR 61-83); 903 (57·7%) were men and 661 (42·3%) were women; 425 (27·2%) had died at data cutoff (April 28, 2020). 772 (49·4%) were classed as frail (CFS 5-8) and 27 (1·7%) were classed as terminally ill (CFS 9). Compared with CFS 1-2, the adjusted hazard ratios for time from hospital admission to death were 1·55 (95% CI 1·00-2·41) for CFS 3-4, 1·83 (1·15-2·91) for CFS 5-6, and 2·39 (1·50-3·81) for CFS 7-9, and adjusted odds ratios for day-7 mortality were 1·22 (95% CI 0·63-2·38) for CFS 3-4, 1·62 (0·81-3·26) for CFS 5-6, and 3·12 (1·56-6·24) for CFS 7-9. INTERPRETATION: In a large population of patients admitted to hospital with COVID-19, disease outcomes were better predicted by frailty than either age or comorbidity. Our results support the use of CFS to inform decision making about medical care in adult patients admitted to hospital with COVID-19. FUNDING: None.