Methods of Assessing Frailty in the Critically Ill: A Systematic Review of the Current Literature

Implications of frailty before and after intensive care unit admission

PURPOSE OF REVIEW

In the decade since the first publications related to frailty in those with critical illness, the study of frailty has rapidly increased. The purpose of this review is to update the reader on recent advances across several important areas of frailty research: how best to identify frailty in those with critical illness, studies describing the relationship between frailty and delirium, and how frailty affects outcomes for those with coronavirus disease 2019 (COVID-19), which, despite rates and severity of acute infection declining, still tremendously impacts patients long after the acute infection, resulting in symptoms of long COVID-19.

RECENT FINDINGS

A number of frailty assessment tools exist, to date, the Clinical Frailty Scale based on the deficit accumulation approach to defining frailty, is the most commonly used in ICU studies. Several novel frailty instruments for the ICU are being developed. Because tools assessing frailty by the phenotypic and deficit accumulation approaches identify different populations, careful choice of a frailty assessment tool is warranted.Frailty and delirium are hypothesized to represent different clinical expressions of a similar underlying vulnerability, thus identifying frailty may be a useful means by which to identify patients at high risk of becoming delirious. Recent studies show that frailty at ICU admission is a predictor of the development of delirium.Finally, frailty and its outcomes were studied in patients with COVID-19. As with other causes of critical illness, frailty was highly prevalent in those admitted to the ICU and is associated with greater mortality. Frailty was also associated with increased decisions to limit life support treatments, but these decisions were not different among those admitted with COVID-19 or for other reasons.

SUMMARY

Frailty in those with critical illness is an emerging field of study. Future work to define the optimal means by which to identify this syndrome and how best to manage critically ill patients with frailty are needed.

Association between frailty index based on laboratory tests and all-cause mortality in critically ill patients with heart failure

BACKGROUND

The frailty index based on laboratory tests (FI-lab) can identify individuals at increased risk for adverse health outcomes. The association between the FI-lab and all-cause mortality in patients with heart failure (HF) in the intensive care unit (ICU) remains unknown. This study aimed to determine the correlation between FI-lab and all-cause mortality to evaluate the impact of FI-lab on the prognosis of critically ill patients with HF.

METHODS

This retrospective observational study utilized data extracted from the Medical Information Mart for Intensive Care IV database. The FI-lab, which consists of 33 laboratory tests, was constructed. Patients were then grouped into quartiles (Q1-Q4) based on their FI-lab scores. Kaplan-Meier analysis was used to compare all-cause mortality among the four groups. A Cox proportional hazard analysis was conducted to examine the association between the FI-lab score and all-cause mortality. The incremental predictive value of adding FI-lab to classical disease severity scores was assessed using Harrell's C statistic, integrated discrimination improvement (IDI) and net reclassification improvement (NRI).

RESULTS

Among 3021 patients, 838 (27.74%) died within 28 days, and 1400 (46.34%) died within a 360 day follow-up period. Kaplan-Meier analysis indicated that patients with higher FI-lab scores had significantly higher risks of all-cause mortality (log-rank P < 0.001). Multivariable Cox regression suggested that FI-lab, evaluated as a continuous variable (for each 0.01 increase), was associated with increased 28 day mortality [hazard ratio (HR) 1.02, 95% confidence interval (CI) (1.01-1.03), P < 0.001] and 360 day mortality [HR 1.02, 95% CI (1.01-1.02), P < 0.001]. When assessed in quartiles, the 28 day mortality risk [HR 1.66, 95% CI (1.28-2.15), P < 0.001] and 360 day mortality risk [HR 1.48, 95% CI (1.23-1.8), P < 0.001] were significantly higher for FI-lab Q4 compared with FI-lab Q1. FI-lab significantly improved the predictive capability of classical disease severity scores for 28 and 360 day mortality.

CONCLUSIONS

In ICU patients diagnosed with HF, the FI-lab is a potent predictor of short-term and long-term mortality in critically ill patients with HF. The active use of FI-lab to identify high-risk groups among critically ill HF patients and initiate timely interventions may have significant value in improving the prognosis of critically ill patients with HF.

Frailty, Outcomes, Recovery and Care Steps of Critically Ill Patients (FORECAST): a prospective, multi-centre, cohort study

PURPOSE

Frailty is common in critically ill patients but the timing and optimal method of frailty ascertainment, trajectory and relationship with care processes remain uncertain. We sought to elucidate the trajectory and care processes of frailty in critically ill patients as measured by the Clinical Frailty Scale (CFS) and Frailty Index (FI).

METHODS

This is a multi-centre prospective cohort study enrolling patients ≥ 50 years old receiving life support > 24 h. Frailty severity was assessed with a CFS, and a FI based on the elements of a comprehensive geriatric assessment (CGA) at intensive care unit (ICU) admission, hospital discharge and 6 months. For the primary outcome of frailty prevalence, it was a priori dichotomously defined as a CFS ≥ 5 or FI ≥ 0.2. Processes of care, adverse events were collected during ICU and ward stays while outcomes were determined for ICU, hospital, and 6 months.

RESULTS

In 687 patients, whose age (mean ± standard deviation) was 68.8 ± 9.2 years, frailty prevalence was higher when measured with the FI (CFS, FI %): ICU admission (29.8, 44.8), hospital discharge (54.6, 67.9), 6 months (34.1, 42.6). Compared to ICU admission, aggregate frailty severity increased to hospital discharge but improved by 6 months; individually, CFS and FI were higher in 45.3% and 50.6% patients, respectively at 6 months. Compared to hospital discharge, 18.7% (CFS) and 20% (FI) were higher at 6 months. Mortality was higher in frail patients. Processes of care and adverse events were similar except for worse ICU/ward mobility and more frequent delirium in frail patients.

CONCLUSIONS

Frailty severity was dynamic, can be measured during recovery from critical illness using the CFS and FI which were both associated with worse outcomes. Although the CFS is a global measure, a CGA FI based may have advantages of being able to measure frailty levels, identify deficits, and potential targets for intervention.

Nutrition determinants of acute skeletal muscle loss in critically ill patients: A prospective observational cohort study

BACKGROUND

Skeletal muscle loss is associated with adverse outcomes in critically ill patients and risk factors of acute skeletal muscle loss are not well described. This study aims to determine the factors associated with acute skeletal muscle loss in critically ill patients.

METHODS

This prospective observational cohort study was conducted with patients who were expected to stay in the intensive care unit (ICU) for at least a week. Rectus femoris cross-sectional area (RFCSA) measurements were performed within 48 h of ICU admission and on study day 7. The percentage change in RFCSA and variables associated with this change were evaluated by univariate and multivariate regression analysis.

RESULTS

Over a 12-month period, 518 patients were assessed for eligibility and 44 critically ill patients with a mean age of 59.3 ± 10.9 years were enrolled; 52.3% of them were female. There were significant reductions in RFCSA (16.8 ± 16.5%; P < 0.001). The mean amounts of protein and energy consumed compared with those prescribed were 67.0 ± 28.8% and 71.5 ± 38.3%, respectively. Multivariate regression analysis revealed that frailty was independently associated with acute skeletal muscle loss after adjusting for confounding factors in our cohort of patients.

CONCLUSION

Frailty status before ICU admission is associated with acute skeletal muscle loss and may be important for identifying critically ill patients at high risk of muscle wasting.

Ethical issues surrounding appropriate care for older persons in the Intensive Care Unit

Increasing numbers of older patients are being admitted to the Intensive Care Unit (ICU) as the world's population ages. The biological process of ageing, senescence, results in altered ability to maintain normal homeostasis and organ function, including of the cardiovascular, immune, and neuromuscular systems. This contributes towards increased frailty in older patients, associated with functional limitations and increased vulnerability. Although widely defined using chronological age, the concept of "old age" is thus multifactorial, including biological, but also psychological and sociocultural aspects, which should all be taken into account when considering what is appropriate in terms of ICU admission and management. As for all patients, but perhaps particularly in this subgroup, decisions regarding ICU admission and treatment and the withdrawing and withholding of life support must be individualized.

Associations between body mass index, biological age and frailty in the critically ill

BACKGROUND

The relationship between body mass index (BMI) and outcomes in the acute care setting is controversial, with evidence suggesting that obesity is either protective - which is also called obesity paradox - or associated with worse outcomes. The purpose of this study was to assess whether BMI was related to frailty and biological age, and whether BMI remained predictive of mortality after adjusting for frailty and biological age.

SUBJECTS

Of the 2950 patients who had a biological age estimated on admission to the intensive care unit, 877 (30 %) also had BMI and frailty data available for further analysis in this retrospective cohort study.

METHODS

Biological age of each patient was estimated using the Levine PhenoAge model based on results of nine blood tests that were reflective of DNA methylation. Biological age in excess of chronological age was then indexed to the local study context by a linear regression to generate the residuals. The associations between BMI, clinical frailty scale, and the residuals were first analyzed using univariable analyses. Their associations with mortality were then assessed by multivariable analysis, including the use of a 3-knot restricted cubic spline function to allow non-linearity.

RESULTS

Both frailty (p = 0.003) and the residuals of the biological age (p = 0.001) were related to BMI in a U-shaped fashion. BMI was not related to hospital mortality, but both frailty (p = 0.015) and the residuals of biological age (OR per decade older than chronological age 1.50, 95 % confidence interval [CI] 1.04-2.18; p = 0.031) were predictive of mortality after adjusting for chronological age, diabetes mellitus and severity of acute illness.

CONCLUSIONS

BMI was significantly associated with both frailty and biological age in a U-shaped fashion but only the latter two were related to mortality. These results may, in part, explain why obesity paradox could be observed in some studies.

Prevalence of frailty and association with patient centered outcomes: A prospective registry-embedded cohort study from India

PURPOSE

We aimed to study the prevalence of frailty, evaluate risk factors, and understand impact on outcomes in India.

METHODS

This was a prospective registry-embedded cohort study across 7 intensive care units (ICUs) and included adult patients anticipated to stay for at least 48 h. Primary exposure was frailty, as defined by a score ≥ 5 on the Clinical Frailty Scale and primary outcome was ICU mortality. Secondary outcomes included in-hospital mortality and resource utilization. We used generalized linear models to evaluate risk factors and model association between frailty and outcomes.

RESULTS

838 patients were included, with median (IQR) age 57 (42,68) yrs.; 64.8% were male. Prevalence of frailty was 19.8%. Charlson comorbidity index (OR:1.73 (95%CI:1.39,2.15)), Subjective Global Assessment categories mild/moderate malnourishment (OR:1.90 (95%CI:1.29, 2.80)) and severe malnourishment (OR:4.76 (95% CI:2.10,10.77)) were associated with frailty. Frailty was associated with higher odds of ICU mortality (adjusted OR:2.04 (95% CI:1.25,3.33)), hospital mortality (adjusted OR:2.36 (95%CI:1.45,3.84)), development of stage2/3 AKI (unadjusted OR:2.35 (95%CI:1.60, 3.43)), receipt of non-invasive ventilation (unadjusted OR:2.68 (95%CI:1.77, 4.03)), receipt of vasopressors (unadjusted OR:1.47 (95%CI:1.04, 2.07)), and receipt of kidney replacement therapy (unadjusted OR:3.15 (95%CI:1.90, 5.17)).

CONCLUSIONS

Frailty is common among critically ill patients in India and is associated with worse outcomes.

STUDY REGISTRATION

CTRI/2021/02/031503.

Age- and sex-specific associations of frailty with mortality and healthcare utilization in community-dwelling adults from ontario, Canada

BACKGROUND

Understanding how health trajectories are related to the likelihood of adverse outcomes and healthcare utilization is key to planning effective strategies for improving health span and the delivery of care to older adults. Frailty measures are useful tools for risk stratification in community-based and primary care settings, although their effectiveness in adults younger than 60 is not well described.

METHODS

We performed a 10-year retrospective analysis of secondary data from the Ontario Health Study, which included 161,149 adults aged ≥ 18. Outcomes including all-cause mortality and hospital admissions were obtained through linkage to ICES administrative databases with a median follow-up of 7.1-years. Frailty was characterized using a 30-item frailty index.

RESULTS

Frailty increased linearly with age and was higher for women at all ages. A 0.1-increase in frailty was significantly associated with mortality (HR = 1.47), the total number of outpatient (IRR = 1.35) and inpatient (IRR = 1.60) admissions over time, and length of stay (IRR = 1.12). However, with exception to length of stay, these estimates differed depending on age and sex. The hazard of death associated with frailty was greater at younger ages, particularly in women. Associations with admissions also decreased with age, similarly between sexes for outpatient visits and more so in men for inpatient.

CONCLUSIONS

These findings suggest that frailty is an important health construct for both younger and older adults. Hence targeted interventions to reduce the impact of frailty before the age of 60 would likely have important economic and social implications in both the short- and long-term.

Assessment of quality of life for frail, elderly patients post-ICU discharge: a protocol for a scoping review

INTRODUCTION

Rises in average life expectancy, increased comorbidities and frailty among older patients lead to higher admission rates to intensive care units (ICU). During an ICU stay, loss of physical and cognitive functions may occur, causing prolonged rehabilitation. Some functions may be lost permanently, affecting quality of life (QoL). There is a lack of understanding regarding how many variables are relevant to health-related outcomes and which outcomes are significant for the QoL of frail, elderly patients following discharge from the ICU. Therefore, this scoping review aims to identify reported variables for health-related outcomes and explore perspectives regarding QoL for this patient group.

METHODS AND ANALYSIS

The Joanna Briggs Institute guidelines for scoping reviews will be employed and original, peer-reviewed studies in English and Scandinavian languages published from 2013 to 2023 will be included. The search will be conducted from July 2023 to December 2023, according to the inclusion criteria in Embase, MEDLINE, PsycINFO and CINAHL. References to identified studies will be hand-searched, along with backward and forward citation searching for systematic reviews. A librarian will support and qualify the search strategy. Two reviewers will independently screen eligible studies and perform data extraction according to predefined headings. In the event of disagreements, a third reviewer will adjudicate until consensus is achieved. Results will be presented narratively and in table form and discussed in relation to relevant literature.

ETHICS AND DISSEMINATION

Ethical approval is unnecessary, as the review synthesises existing research. The results will be disseminated through a peer-reviewed publication in a scientific journal.

Long-term functional disabilities in intensive care unit survivors: A prospective cohort study

BACKGROUND

Functional disabilities are common in intensive care unit (ICU) survivors and may affect their ability to live independently. Few previous studies have investigated long-term functional outcomes with health status before ICU admission (pre-ICU health), and they are limited to specific patient groups.

OBJECTIVES

The objective of this study was to investigate the prevalence of functional disabilities and examine pre-ICU health variables as possible predictive factors of functional disabilities 12 months after ICU admission in a mixed population of ICU survivors.

METHODS

This prospective cohort study was conducted in six ICUs in Norway. Data on pre-ICU health were collected as soon as possible after ICU admission using patients, proxies, and patient electronic health records and at 12 months after ICU admission. Self-reported functional status was assessed using the Katz Index of independence in personal activities of daily living (P-ADL) and the Lawton instrumental activities of daily living scale (I-ADL).

RESULTS

A total of 220 of 343 (64%) ICU survivors with data on pre-ICU health completed the questionnaires at 12 months and reported the following functional disabilities at 12 months: 31 patients (14.4%) reported P-ADL dependencies (new in 16 and persisting in 15), and 80 patients (36.4%) reported I-ADL dependencies (new in 41 and persisting in 39). In a multivariate analysis, worse baseline P-ADL and I-ADL scores were associated with dependencies in P-ADLs (odds ratio [OR]: 1.87; 95% confidence interval [CI]: 1.14-3.06) and I-ADLs (OR: 1.52; 95% CI: 1.03-2.23), respectively, at 12 months. Patients who were employed were less likely to report I-ADL dependencies at 12 months (OR: 0.34; 95% CI: 0.12-0.95).

CONCLUSION

In a subsample of ICU survivors, patients reported functional disabilities 12 months after ICU admission, which was significantly associated with their pre-ICU functional status. Early screening of pre-ICU functional status may help identify patients at risk of long-term functional disabilities. ICU survivors with pre-ICU functional disabilities may find it difficult to improve their functional status.

Impact of First Wave of COVID-19 Pandemic on Mortality at Emergency Department in Older Patients with COVID and Non-COVID Diagnoses

INTRODUCTION

Mortality in emergency departments (EDs) is not well known. This study aimed to assess the impact of the first-wave pandemic on deaths accounted in the ED of older patients with COVID and non-COVID diseases.

METHODS

We used data from the Emergency Department and Elderly Needs (EDEN) cohort (pre-COVID period) and from the EDEN-COVID cohort (COVID period) that included all patients ≥65 years seen in 52 Spanish EDs from April 1 to 7, 2019, and March 30 to April 5, 2020, respectively. We recorded patient characteristics and final destination at ED. We compared older patients in the pre-COVID period, with older patients with non-COVID and with COVID-19. ED-mortality (before discharge or hospitalization) is the prior outcome and is expressed as an adjusted odds ratio (aOR) with 95% interval confidence.

RESULTS

We included 23,338 older patients from the pre-COVID period (aged 78.3 [8.1] years), 6,715 patients with non-COVID conditions (aged 78.9 [8.2] years) and 3,055 with COVID (aged 78.3 [8.3] years) from the COVID period. Compared to the older patients, pre-COVID period, patients with non-COVID and with COVID-19 were more often male, referred by a doctor and by ambulance, with more comorbidity and disability, dementia, nursing home, and more risk according to qSOFA, respectively (p < 0.001). Compared to the pre-COVID period, patients with non-COVID and with COVID-19 were more often to be hospitalized from ED (24.8% vs. 44.3% vs. 79.1%) and were more often to die in ED (0.6% vs. 1.2% vs. 2.2%), respectively (p < 0.001). Compared to the pre-COVID period, aOR for age, sex, comorbidity and disability, ED mortality in elderly patients cared in ED during the COVID period was 2.31 (95% confidence interval [CI]: 1.76-3.06), and 3.75 (95% CI: 2.77-5.07) for patients with COVID. By adding the variable qSOFA to the model, such OR were 1.59 (95% CI: 1.11-2.30) and 2.16 (95% CI: 1.47-3.17), respectively.

CONCLUSIONS

During the early first pandemic wave of COVID-19, more complex and life-threatening older with COVID and non-COVID diseases were seen compared to the pre-COVID period. In addition, the need for hospitalization and the ED mortality doubled in non-COVID and tripled in COVID diagnosis. This increase in ED mortality is not only explained by the complexity or severity of the elderly patients but also because of the system's overload.

Quality of life after acute kidney injury

PURPOSE OF REVIEW

Deciphering the effect of acute kidney injury (AKI) during critical illness on long-term quality of life versus the impact of conditions that brought on critical illness is difficult.

RECENT FINDINGS

Reports on patient-centred outcomes such as health-related quality of life (HRQOL) have provided insight into the long-lasting impact of critical illness complicated by AKI. However, these data stem from observational studies and randomized controlled trials, which have been heterogeneous in their patient population, timing, instruments used for assessment and reporting. Recent studies have corroborated these findings including lack of effect of renal replacement therapy compared to severe AKI on outcomes and worse physical compared to cognitive dysfunction.

SUMMARY

In adults, more deficits in physical than mental health domains are found in survivors of AKI in critical care, whereas memory deficits and learning impairments have been noted in children. Further study is needed to understand and develop interventions that preserve or enhance the quality of life for individual patients who survive AKI following critical illness, across all ages.

Liver transplantation in the patient with physical frailty

Frailty is a decline in functional reserve across multiple physiological systems. A key component of frailty is sarcopenia, which denotes a loss of skeletal muscle mass and impaired contractile function that ultimately result in physical frailty. Physical frailty/sarcopenia are frequent and contribute to adverse clinical outcomes before and after liver transplantation. Frailty indices, including the liver frailty index, focus on contractile dysfunction (physical frailty), while cross-sectional image analysis of muscle area is the most accepted and reproducible measure to define sarcopenia. Thus, physical frailty and sarcopenia are interrelated. The prevalence of physical frailty/sarcopenia is high in liver transplant candidates and these conditions have been shown to adversely impact clinical outcomes including mortality, hospitalisations, infections, and cost of care both before and after transplantation. Data on the prevalence of frailty/sarcopenia and their sex- and age-dependent impact on outcomes are not consistent in patients on the liver transplant waitlist. Physical frailty and sarcopenic obesity are frequent in the obese patient with cirrhosis, and adversely affect outcomes after liver transplantation. Nutritional interventions and physical activity remain the mainstay of management before and after transplantation, despite limited data from large scale trials. In addition to physical frailty, there is recognition that a global evaluation including a multidisciplinary approach to other components of frailty (e.g., cognition, emotional, psychosocial) also need to be addressed in patients on the transplant waitlist. Recent advances in our understanding of the underlying mechanisms of sarcopenia and contractile dysfunction have helped identify novel therapeutic targets.

Association between Frailty Assessed Using Two Electronic Medical Record-Based Frailty Assessment Tools and Long-Term Adverse Prognosis in Older Critically Ill Survivors

OBJECTIVES

Frailty has become an independent risk factor for adverse outcomes in critically ill patients. This study aimed to explore the predictive ability of two electronic medical record-based frailty assessment tools, the Hospital Frailty Risk Score (HFRS) and Frailty Index based on physiological and laboratory tests (FI-lab), for long-term adverse prognosis in older critically ill survivors.

DESIGN

Retrospective observational study.

SETTING AND PARTICIPANTS

9,082 critically ill survivors aged ≥ 65 years.

MEASUREMENTS

The HFRS and the 33-item FI-lab were constructed based on the published literature. Cox and logistic regression models assessed the association between frailty and 1-year mortality and post-discharge care needs.

RESULTS

2,586 patients died within 1 year of follow-up. In fully adjusted models, frailty assessed using both the HFRS (per point, hazard ratio [HR] 1.06, 95% confidential interval [CI] 1.05-1.06; intermediate frailty risk, HR 2.00, 95% CI 1.78-2.25; high frailty risk, HR 3.06, 95% CI 2.68-3.50) and FI-lab (per 0.01 points, HR 1.03, 95% CI 1.03-1.03; intermediate frailty risk, HR 1.59, 95% CI 1.44-1.76; high frailty risk, HR 2.30, 95% CI 2.06-2.57) was associated with mortality. Addition of frailty indicators improved the predictive validity of the Sequential Organ Failure Assessment score for mortality (HFRS alone ∆ C-index 0.034; FI-lab alone ∆ C-index 0.016; HFRS and FI-lab combined ∆ C-index 0.042). The HFRS but not the FI-lab was associated with higher probability of post-discharge care needs.

CONCLUSION

Both the HFRS and FI-lab could independently predict 1-year mortality in older critically ill survivors. Adding the HFRS to the SOFA score model improved it more than adding the FI-lab. The greatest improvement was achieved when both frailty indicators were used together. These findings suggest that electronic medical record-based frailty assessment methods can be useful tools for predicting long-term outcomes in older critically ill patients.