Rationing care in COVID-19: if we must do it, can we do better?

COVID-19-Associated Outcomes of Critical Illness in Patients with Frailty: a Cohort Study

Background

Pre-admission frailty has been associated with higher hospital mortality in patients with critical illness. We aimed to measure the prevalence of frailty and its associated outcomes in patients with COVID-19 critical illness.

Methods

A historical cohort study of all adults admitted to ICU with a pneumonia diagnosis in Alberta, Canada between May 1, 2020, and October 31, 2020. At ICU admission patients were routinely assessed for frailty using the Clinical Frailty Scale (CFS). Frailty was defined as a CFS score ≥5. Primary outcomes were pre-admission frailty prevalence and hospital mortality.

Results

The cohort (n=521) prevalence of frailty was 34.2% (n=178), mean (SD) age was 58.8 (14.9) years, APACHE II 22.8 (8.0), and 39.5% (n=206) were female. COVID-19 pneumonia was diagnosed in (19.0%; n=99) admissions; pre-admission frailty was present in 20.2% (n=20) vs. 79.8% (n=79) non-frail (p<.001). Among ICU patients admitted with COVID-19, hospital mortality in frail patients was 35.4% (n=63) vs. 14.0% (n=48) in non-frail (p<.001).

Conclusion

Pre-admission frailty was present in 20.2% of COVID-19 ICU admissions and was associated with higher risk of hospital mortality. Frailty assessment may yield valuable prognostic information when considering COVID-19 ICU admission; however, further study is needed to identify effect on patient-centred outcomes in this heterogeneous population.

Family Caregiving during the COVID-19 Pandemic in Canada: A Mediation Analysis

Family caregiving is a public health issue because of caregivers' significant contribution to the health and social care systems, as well as the substantial impact that giving and receiving care has on the health and quality of life of care receivers and caregivers. While there have been many studies that associate caregivers' care work, financial difficulty, navigation, and other caregiving factors with family caregivers' psychological distress, we were interested not only in the factors related to family caregiver anxiety but also in hypothesizing how those effects occur. In this study, we used Andrew Hayes' PROCESS moderation analysis to explore the link between caregiver frailty, weekly care hours, and perceptions of financial difficulty, social support, and anxiety. In this analysis, we included 474 caregivers with relatively complete data on all of the variables. In regression analysis after controlling for gender and age, social loneliness (β = 0.245), frailty (β = 0.199), financial difficulty (β = 0.196), care time (β = 0.143), and navigation confidence (β = 0.131) were all significant. We then used PROCESS Model 6 to determine the significance of the direct, indirect, and total effects through the serial mediation model. The model pathway from frailty to care time to financial difficulty to social loneliness to anxiety was significant. The proportions of family caregivers who were moderately frail, anxious, and experiencing social loneliness after eighteen months of the COVID-19 pandemic found in this survey should be of concern to policymakers and healthcare providers.

Rural Family Caregiving: A Closer Look at the Impacts of Health, Care Work, Financial Distress, and Social Loneliness on Anxiety

Even before the COVID-19 pandemic, earlier acute care patient discharges, restricted admissions to long-term care, and reduced home care services increased the amount and complexity of family caregivers’ care work. However, much less is known about rural caregivers’ experiences. Thus, our aim in this sequential mixed-methods study was to understand how COVID-19 affected rural family caregivers. Thematically analyzed interviews and linear regression on survey data were used to understand family caregiver stress. Fourteen rural caregivers participated in interviews. They acknowledged that they benefitted from the circle of support in rural communities; however, they all reported having to cope with fewer healthcare and social services. 126 rural caregivers participated in the online survey. About a third (31%) of these caregivers had moderate frailty, indicating that they could benefit from support to improve their health. In linear regression, frailty, social loneliness, financial hardship, and younger age were associated with caregiver anxiety. Contrary to the qualitative reports that people in rural communities are supportive, over two-thirds of the rural caregivers completing the survey were socially lonely. Rural family caregivers are vulnerable to anxiety and social loneliness due to the nature of caregiving and the lack of healthcare and social service supports in rural areas. Primary healthcare and home care teams are well-positioned to assess caregivers’ health and care situation as well as to signpost them to needed supports that are available in their areas.

Clinical frailty, and not features of acute infection, is associated with late mortality in COVID-19: a retrospective cohort study

BACKGROUND

Coronavirus disease 2019 (COVID-19) is associated with excess mortality after hospital discharge. Identification of patients at increased risk of death following hospital discharge is needed to guide clinical monitoring and early intervention. Herein, we aimed to identify predictors of early vs. late mortality in COVID-19 patients.

METHODS

A total of 471 patients with polymerase chain reaction-confirmed COVID-19 were followed up for 9 months [median (inter-quartile range) of follow-up time: 271 (14) days] after hospital admission. COVID-19-related signs and symptoms, laboratory features, co-morbidities, Coronavirus Clinical Characterisation Consortium (4C) mortality and Clinical Frailty Scale (CFS) scores were analysed by logistic regression for association with early (28 day) vs. late mortality. Receiver operating characteristic (ROC) analysis was used to determine the discriminative value of 4C and CFS scores for early vs. late mortality.

RESULTS

A total of 120 patients died within 28 days from hospital admission. Of the remaining 351 patients, 41 died within the next 8 months. Respiratory failure, systemic inflammation, and renal impairment were associated with early mortality, while active cancer and dementia were associated with late mortality, after adjustment for age and sex. 4C mortality score and CFS were associated with both early [odds ratio (OR) (95% confidence interval-CI): 4C: 1.34 (1.25-1.45); CFS: 1.49 (1.33-1.66)] and late [OR (95% CI): 4C: 1.23 (1.12-1.36); CFS: 2.04 (1.62-2.56)] mortality. After adjustment for CFS, the association between 4C and late mortality was lost. By ROC analysis, 4C mortality score was superior to CFS for 28 day mortality [area under the curve (AUC) (95% CI): 0.779 (0.732-0.825) vs. 0.723 (0.673-0.773), respectively; P = 0.039]. In contrast, CFS had higher predictive value for late mortality compared with 4C mortality score [AUC (95% CI): 0.830 (0.776-0.883) vs. 0.724 (0.650-0.798), respectively; P = 0.007].

CONCLUSIONS

In our cohort, late mortality in COVID-19 patients is more strongly associated with premorbid clinical frailty than with severity of the acute infection phase.

The value of qualitative data in Quality Improvement Projects in the care of older adults: the case of frailty scores in the emergency department

This commentary discusses the role and value of qualitative data when undertaking quality improvement (QI) focussing on the care of older adults. To illustrate this, we reflect on our own experiences of planning a QI project to improve the documentation of Clinical Frailty Scale (CFS) scores in the emergency department (ED) during the coronavirus disease of 2019 (COVID-19) pandemic. National clinical guidance for COVID-19 states that all adults over the age of 65 should be given a CFS at the first point of contact during hospital admission. Therefore, there is a need to improve CFS documentation, specifically in acute care settings.

We describe how qualitative methods facilitated an understanding of the barriers to CFS documentation in ED. Staff see the CFS as a useful tool for inter-professional communication, though there are tensions between clinical guidance and their beliefs. Staff had moral concerns about how an ED-allocated CFS might limit available treatment options for older adults. Our findings demonstrate how qualitative methods can illuminate the important social and moral dimensions of why improvement does or does not occur.

A classification tree to assist with routine scoring of the Clinical Frailty Scale

Background

the Clinical Frailty Scale (CFS) was originally developed to summarise a Comprehensive Geriatric Assessment and yield a care plan. Especially since COVID-19, the CFS is being used widely by health care professionals without training in frailty care as a resource allocation tool and for care rationing. CFS scoring by inexperienced raters might not always reflect expert judgement. For these raters, we developed a new classification tree to assist with routine CFS scoring. Here, we test that tree against clinical scoring.

Objective/Methods

we examined agreement between the CFS classification tree and CFS scoring by novice raters (clerks/residents), and the CFS classification tree and CFS scoring by experienced raters (geriatricians) in 115 older adults (mean age 78.0 ± 7.3; 47% females) from a single centre.

Results

the intraclass correlation coefficient (ICC) for the CFS classification tree was 0.833 (95% CI: 0.768–0.882) when compared with the geriatricians’ CFS scoring. In 93%, the classification tree rating was the same or differed by at most one level with the expert geriatrician ratings. The ICC was 0.805 (0.685–0.883) when CFS scores from the classification tree were compared with the clerk/resident scores; 88.5% of the ratings were the same or ±1 level.

Conclusions

a classification tree for scoring the CFS can help with reliable scoring by relatively inexperienced raters. Though an incomplete remedy, a classification tree is a useful support to decision-making and could be used to aid routine scoring of the CFS.

Baseline Frailty as a Predictor of Survival After Critical Care: A Retrospective Cohort Study of Older Adults Receiving Home Care in Ontario, Canada

BACKGROUND

The extent to which the degree of baseline frailty, as measured using standardized multidimensional health assessments before hospital admission, predicts survival among older adults after admission to an ICU, remains unclear.

RESEARCH QUESTION

Is baseline frailty an independent predictor of survival among older adults receiving care in an ICU?

STUDY DESIGN AND METHODS

Retrospective cohort study of community-dwelling older adults (age, ≥ 65 years) receiving public home services who were admitted to any ICU in Ontario, Canada, between April 1, 2009, and March 31, 2015. All individuals underwent an inter-Resident Assessment Instrument-Home Care (RAI-HC) assessment completed within 180 days of ICU admission. These assessments were linked to hospital discharge abstract records. Patients were categorized using frailty measures each calculated from the RAI-HC: a classification tree version of the Clinical Frailty Scale; the Frailty Index-Acute Care; and the Changes in Health, End-Stage Disease, Signs, and Symptoms Scale. One-year survival models were used to compare their performance. Patients were stratified based on the receipt of mechanical ventilation in the ICU.

RESULTS

Of 24,499 individuals admitted to an ICU within 180 days of a RAI-HC assessment, 26.4% (n = 6,467) received mechanical ventilation. Overall, 43.0% (95% CI, 42.4%-43.6%) survived 365 days after ICU admission. In general, among the overall cohort and both mechanical ventilation subgroups, mortality hazards increased with the severity of baseline frailty. Models predicting survival 30, 90, and 365 days after admission to an ICU that adjusted for one of the frailty measures were more discriminant than reference models that adjusted only for age, sex, major clinical category, and area income quintile.

INTERPRETATION

Severity of baseline frailty is associated independently with survival after ICU admission and should be considered when determining goals of care and treatment plans for people with critical illness.

COVID-19 is not over and age is not enough: Using frailty for prognostication in hospitalized patients

Background

Frailty screening using the Clinical Frailty Scale (CFS) has been proposed to guide resource allocation in acute care settings during the pandemic. However, the association between frailty and coronavirus disease 2019 (COVID‐19) prognosis remains unclear.

Objectives

To investigate the association between frailty and mortality over 6 months in middle‐aged and older patients hospitalized with COVID‐19 and the association between acute morbidity severity and mortality across frailty strata.

Design

Observational cohort study.

Setting

Large academic medical center in Brazil.

Participants

A total of 1830 patients aged ≥50 years hospitalized with COVID‐19 (March–July 2020).

Measurements

We screened baseline frailty using the CFS (1–9) and classified patients as fit to managing well (1–3), vulnerable (4), mildly (5), moderately (6), or severely frail to terminally ill (7–9). We also computed a frailty index (0–1; frail >0.25), a well‐known frailty measure. We used Cox proportional hazards models to estimate the association between frailty and time to death within 30 days and 6 months of admission. We also examined whether frailty identified different mortality risk levels within strata of similar age and acute morbidity as measured by the Sequential Organ Failure Assessment (SOFA) score.

Results

Median age was 66 years, 58% were male, and 27% were frail to some degree. Compared with fit‐to‐managing‐well patients, the adjusted hazard ratios (95% confidence interval [CI]) for 30‐day and 6‐month mortality were, respectively, 1.4 (1.1–1.7) and 1.4 (1.1–1.7) for vulnerable patients; 1.5 (1.1–1.9) and 1.5 (1.1–1.8) for mild frailty; 1.8 (1.4–2.3) and 1.9 (1.5–2.4) for moderate frailty; and 2.1 (1.6–2.7) and 2.3 (1.8–2.9) for severe frailty to terminally ill. The CFS achieved outstanding accuracy to identify frailty compared with the Frailty Index (area under the curve = 0.94; 95% CI = 0.93–0.95) and predicted different mortality risks within age and acute morbidity groups.

Conclusions

Our results encourage the use of frailty, alongside measures of acute morbidity, to guide clinicians in prognostication and resource allocation in hospitalized patients with COVID‐19.

Association between Clinical Frailty Scale score and hospital mortality in adult patients with COVID-19 (COMET): an international, multicentre, retrospective, observational cohort study

Background

During the COVID-19 pandemic, the scarcity of resources has necessitated triage of critical care for patients with the disease. In patients aged 65 years and older, triage decisions are regularly based on degree of frailty measured by the Clinical Frailty Scale (CFS). However, the CFS could also be useful in patients younger than 65 years. We aimed to examine the association between CFS score and hospital mortality and between CFS score and admission to intensive care in adult patients of all ages with COVID-19 across Europe.

Methods

This analysis was part of the COVID Medication (COMET) study, an international, multicentre, retrospective observational cohort study in 63 hospitals in 11 countries in Europe. Eligible patients were aged 18 years and older, had been admitted to hospital, and either tested positive by PCR for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or were judged to have a high clinical likelihood of having SARS-CoV-2 infection by the local COVID-19 expert team. CFS was used to assess level of frailty: fit (CFS_1–3), mildly frail (CFS_4–5), or frail (CFS_6–9). The primary outcome was hospital mortality. The secondary outcome was admission to intensive care. Data were analysed using a multivariable binary logistic regression model adjusted for covariates (age, sex, number of drugs prescribed, and type of drug class as a proxy for comorbidities).

Findings

Between March 30 and July 15, 2020, 2434 patients (median age 68 years [IQR 55–77]; 1480 [61%] men, 954 [30%] women) had CFS scores available and were included in the analyses. In the total sample and in patients aged 65 years and older, frail patients and mildly frail patients had a significantly higher risk of hospital mortality than fit patients (total sample: CFS_6–9vs CFS_1–3 odds ratio [OR] 2·71 [95% CI 2·04–3·60], p<0·0001 and CFS_4–5vs CFS_1–3 OR 1·54 [1·16–2·06], p=0·0030; age ≥65 years: CFS_6–9vs CFS_1–3 OR 2·90 [2·12–3·97], p<0·0001 and CFS_4–5vs CFS_1–3 OR 1·64 [1·20–2·25], p=0·0020). In patients younger than 65 years, an increased hospital mortality risk was only observed in frail patients (CFS_6–9vs CFS_1–3 OR 2·22 [1·08–4·57], p=0·030; CFS_4–5vs CFS_1–3 OR 1·08 [0·48–2·39], p=0·86). Frail patients had a higher incidence of admission to intensive care than fit patients (CFS_6–9vs CFS_1–3 OR 1·54 [1·21–1·97], p=0·0010), whereas mildly frail patients had a lower incidence than fit patients (CFS_4–5vs CFS_1–3 OR 0·71 [0·55–0·92], p=0·0090). Among patients younger than 65 years, frail patients had an increased incidence of admission to intensive care (CFS_6–9vs CFS_1–3 OR 2·96 [1·98–4·43], p<0·0001), whereas mildly frail patients had no significant difference in incidence compared with fit patients (CFS_4–5vs CFS_1–3 OR 0·93 [0·63–1·38], p=0·72). Among patients aged 65 years and older, frail patients had no significant difference in the incidence of admission to intensive care compared with fit patients (CFS_6–9vs CFS_1–3 OR 1·27 [0·92–1·75], p=0·14), whereas mildly frail patients had a lower incidence than fit patients (CFS_4–5vs CFS_1–3 OR 0·66 [0·47–0·93], p=0·018).

Interpretation

The results of this study suggest that CFS score is a suitable risk marker for hospital mortality in adult patients with COVID-19. However, treatment decisions based on the CFS in patients younger than 65 years should be made with caution.

Funding

LOEY Foundation.