Changes in frailty among ICU survivors and associated factors: Results of a one-year prospective cohort study using the Dutch Clinical Frailty Scale

Prevalence of New Frailty at Hospital Discharge in Severe COVID-19 Survivors and Its Associated Factors

BACKGROUND

The development of frailty at hospital discharge affects the clinical outcomes in severe coronavirus disease 2019 (COVID-19) survivors who had no frailty before hospitalization. We aimed to describe the prevalence of new frailty using the clinical frailty scale (CFS) and evaluate its associated factors in patients with severe COVID-19 without pre-existing frailty before hospitalization.

METHODS

We performed a secondary analysis of clinical data from a nationwide retrospective cohort collected from 22 hospitals between January 1, 2020 and August 31, 2021. The patients were at least 19 years old and survived until discharge after admission to the intensive care unit (ICU) because of severe COVID-19. Development of new frailty was defined as a CFS score ≥5 at hospital discharge.

RESULTS

Among 669 severe COVID-19 survivors without pre-existing frailty admitted to the ICU, the mean age was 65.2±12.8 years, 62.5% were male, and 50.2% received mechanical ventilation (MV). The mean CFS score at admission was 2.4±0.9, and new frailty developed in 27.8% (186/483). In multivariate analysis, older age, cardiovascular disease, CFS score of 3-4 before hospitalization, increased C-reactive protein level, longer duration of corticosteroid treatment, and use of MV and extracorporeal membrane oxygenation were identified as factors associated with new-onset frailty.

CONCLUSION

Our study suggests that new frailty is not uncommon and is associated with diverse factors in survivors of severe COVID-19 without pre-existing frailty.

Prevalence of and risk factors analysis for post-intensive care syndrome among survivors of critical care during 3-month longitudinal follow-up

BACKGROUND

Patients discharged from the intensive care unit (ICU) can experience post-intensive care syndrome (PICS), which is comprised of cognitive, physical and psychological impairments.

AIM

The objective of this study was to identify the prevalence of and risk factors associated with all three domains of PICS at the first and third month after ICU discharge.

DESIGN

A prospective descriptive-analytic study was conducted in two ICUs of a Chinese university hospital. We used the Healthy Aging Brain Care Monitor Self-Report Chinese version, a scale from 1 to 57, with 57 indicating the worst outcome, to comprehensively assess PICS at the first and third month follow-ups after patients left the ICU. We performed an analysis of stepwise multiple linear regression to explore the relationship between risk factors and PICS.

RESULTS

We enrolled 654 and 584 participants at the first- and third-month follow-ups, respectively. More than 60% of patients experienced different degrees of PICS, with the most severe impairment being in the physical domain. We classified risk factors associated with PICS, categorized as patient-related, disease-related, and ICU-related factors. Among these risk factors, only being the main income provider for the family, the diagnosis of digestive system disease, trauma and the number of invasive catheters at ICU discharge significantly predicted PICS at both follow-ups. ICU-related risk factors should be given greater attention, given their potential for modification.

CONCLUSIONS

The prevalence and severity of PICS were high in this population after their ICU stay. ICU nurses and medical staff members should collaborate to pay more attention to the comprehensive risk factors and implement targeted preventive measures.

RELEVANCE TO CLINICAL PRACTICE

ICU staff must have a holistic view of PICS and a comprehensive understanding of its risk factors to proactively evaluate patients at high risk of PICS upon admission to the hospital.

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.

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.

Prediction of Long-Term Physical, Mental, and Cognitive Problems Following Critical Illness: Development and External Validation of the PROSPECT Prediction Model

OBJECTIVES

ICU survivors often suffer from long-lasting physical, mental, and cognitive health problems after hospital discharge. As several interventions that treat or prevent these problems already start during ICU stay, patients at high risk should be identified early. This study aimed to develop a model for early prediction of post-ICU health problems within 48 hours after ICU admission.

DESIGN

Prospective cohort study in seven Dutch ICUs.

SETTING/PATIENTS

ICU patients older than 16 years and admitted for greater than or equal to 12 hours between July 2016 and March 2020.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Outcomes were physical problems (fatigue or ≥ 3 new physical symptoms), mental problems (anxiety, depression, or post-traumatic stress disorder), and cognitive impairment. Patient record data and questionnaire data were collected at ICU admission, and after 3 and 12 months, of 2,476 patients. Several models predicting physical, mental, or cognitive problems and a composite score at 3 and 12 months were developed using variables collected within 48 hours after ICU admission. Based on performance and clinical feasibility, a model, PROSPECT, predicting post-ICU health problems at 3 months was chosen, including the predictors of chronic obstructive pulmonary disease, admission type, expected length of ICU stay greater than or equal to 2 days, and preadmission anxiety and fatigue. Internal validation using bootstrapping on data of the largest hospital ( n = 1,244) yielded a C -statistic of 0.73 (95% CI, 0.70-0.76). External validation was performed on data ( n = 864) from the other six hospitals with a C -statistic of 0.77 (95% CI, 0.73-0.80).

CONCLUSIONS

The developed and externally validated PROSPECT model can be used within 48 hours after ICU admission for identifying patients with an increased risk of post-ICU problems 3 months after ICU admission. Timely preventive interventions starting during ICU admission and follow-up care can prevent or mitigate post-ICU problems in these high-risk patients.

A multicomponent intervention program to Prevent and Reduce AgItation and phySical rEstraint use in the ICU (PRAISE): study protocol for a multicenter, stepped-wedge, cluster randomized controlled trial

BACKGROUND

Physical restraints remain to be commonly used in agitated intensive care unit (ICU) patients worldwide, despite a lack of evidence on efficacy and safety and reports of detrimental short and long-term consequences, such as prolonged delirium and a longer ICU length of stay. Physical restraint minimization approaches have focused mainly on educational strategies and other non-pharmacological interventions. Combining these interventions with goal-directed light sedation therapy if needed may play an important contributory role in further reducing the use of physical restraints. The aim of the study is to determine the effectiveness of a multicomponent intervention (MCI) program, combining person-centered non-pharmacological interventions with goal-directed light sedation, compared to physical restraints.

METHODS

A multicenter stepped-wedge cluster randomized controlled trial will be conducted in six Dutch ICUs. A power calculation based total of 480 (expected to become) agitated adult patients will be included in 26 months with a subsequent 2-year follow-up. Patients included in the control period will receive standard care with the current agitation management protocol including physical restraints. Patients included in the intervention period will be treated with the MCI program, consisting of four components, without physical restraints: education of ICU professionals, identification of patients at risk for agitation, formulation of a multidisciplinary person-centered care plan including non-pharmacological and medical interventions, and protocolized goal-directed light sedation using dexmedetomidine. Primary outcome is the number of days alive and outside of the ICU within 28 days after ICU admission. Secondary outcomes include length of hospital stay; 3-, 12-, and 24-month post-ICU quality of life; physical (fatigue, frailty, new physical problems), mental (anxiety, depression, and post-traumatic stress disorder), and cognitive health; and 1-year cost-effectiveness. A process evaluation will be conducted.

DISCUSSION

This will be the first multicenter randomized controlled trial determining the effect of a combination of non-pharmacological interventions and light sedation using dexmedetomidine compared to physical restraints in agitated ICU patients. The results of this study, including long-term patient-centered outcomes, will provide relevant insights to aid ICU professionals in the management of agitated patients.

TRIAL REGISTRATION

NCT05783505, registration date 23 March 2023.

Do critical illness survivors with multimorbidity need a different model of care?

There is currently a lack of evidence on the optimal strategy to support patient recovery after critical illness. Previous research has largely focussed on rehabilitation interventions which aimed to address physical, psychological, and cognitive functional sequelae, the majority of which have failed to demonstrate benefit for the selected outcomes in clinical trials. It is increasingly recognised that a person's existing health status, and in particular multimorbidity (usually defined as two or more medical conditions) and frailty, are strongly associated with their long-term outcomes after critical illness. Recent evidence indicates the existence of a distinct subgroup of critical illness survivors with multimorbidity and high healthcare utilisation, whose prior health trajectory is a better predictor of long-term outcomes than the severity of their acute illness. This review examines the complex relationships between multimorbidity and patient outcomes after critical illness, which are likely mediated by a range of factors including the number, severity, and modifiability of a person's medical conditions, as well as related factors including treatment burden, functional status, healthcare delivery, and social support. We explore potential strategies to optimise patient recovery after critical illness in the presence of multimorbidity. A comprehensive and individualized approach is likely necessary including close coordination among healthcare providers, medication reconciliation and management, and addressing the physical, psychological, and social aspects of recovery. Providing patient-centred care that proactively identifies critical illness survivors with multimorbidity and accounts for their unique challenges and needs is likely crucial to facilitate recovery and improve outcomes.

Impact of frailty on the short-term outcomes of elderly intensive care unit patients

BACKGROUND

Frailty leads to multiple unfavourable outcomes in older adults. However, few studies have investigated correlations between frailty and its impacts on morbidity and mortality of elderly patients in intensive care units (ICUs) in Taiwan.

AIMS

To investigate the impact of frailty on the risk of hospital and 30-day mortality and functional outcomes of elderly Taiwanese ICU patients.

STUDY DESIGN

A prospective observational study was conducted. Patients aged 65 years or older were recruited from three medical ICUs. We defined 'frailty' according to the Clinical Frailty Scale (CFS) higher than 4 within 1 month prior to admission. The primary outcomes were hospital and 30-day mortality. The secondary outcome was CFS changes at ICU admission, hospital discharge, and 30-day follow-up. Logistic/Cox regression was used to analyse the data.

RESULTS

We recruited a total of 106 patients, 57 (54%) of whom were classified as frail. The overall mortality rate was 21%. Hospital mortality and mortality within 30 days after discharge were higher in the frail patients without a significant statistical difference (hospital mortality: 17.5% vs. 12.2%, p = .626; 30-day mortality: 26.3% vs. 14.3%, p = .200). The risk of 30-day mortality for frail patients was up to 2.84 times greater than that of non-frail patients in the Cox model (hazard ratio = 2.84, 95% confidence interval [0.96, 8.38]). Both non-frail and frail patients had a worse CFS score on admission, but the CFS score of surviving non-frail patients improved significantly over the medium term.

CONCLUSION

Frailty tended to increase short-term ICU mortality risk and worsen functional outcomes in the elderly Taiwanese population. This information might guide critical medical decisions.

RELEVANCE TO CLINICAL PRACTICE

Frailty could be included in the prognostic evaluation of either mortality risk or functional outcome. Prompt palliative care might be one last piece of holistic elder care.

The effect of protein provision and exercise therapy on patient-reported and clinical outcomes in intensive care unit survivors: A systematic review

BACKGROUND

Intensive care unit (ICU) survivors deal with long-term health problems, which negatively affect their quality of life (QoL). Nutritional and exercise intervention could prevent the decline of muscle mass and physical functioning which occurs during critical illness. Despite the growing amount of research, robust evidence is lacking.

METHODS

For this systematic review, Embase, PubMed and Cochrane Central Register of Controlled Trials databases were searched. The effect of protein provision (PP) or combined protein and exercise therapy (CPE) during or after ICU admission on QoL, physical functioning, muscle health, protein/energy intake and mortality was assessed compared to standard care.

RESULTS

Four thousand nine hundred and fifty-seven records were identified. After screening, data were extracted for 15 articles (9 randomised controlled trials and 6 non-randomised studies). Two studies reported improvements in muscle mass, of which one found higher independency in activities of daily living. No significant effect was found on QoL. Overall, protein targets were seldom met and often below recommendations.

CONCLUSION

Evidence for the effect of PP or CPE on patient-reported outcomes in ICU survivors is limited due to study heterogeneity and lack of high-quality studies. Future research and clinical practice should focus on adequate protein delivery with exercise interventions to improve long-term outcomes.

Using the Hospital Frailty Risk Score to assess mortality risk in older medical patients admitted to the intensive care unit

BACKGROUND

Prognostic information at the time of hospital discharge can help guide goals-of-care discussions for future care. We sought to assess the association between the Hospital Frailty Risk Score (HFRS), which may highlight patients' risk of adverse outcomes at the time of hospital discharge, and in-hospital death among patients admitted to the intensive care unit (ICU) within 12 months of a previous hospital discharge.

METHODS

We conducted a multicentre retrospective cohort study that included patients aged 75 years or older admitted at least twice over a 12-month period to the general medicine service at 7 academic centres and large community-based teaching hospitals in Toronto and Mississauga, Ontario, Canada, from Apr. 1, 2010, to Dec. 31, 2019. The HFRS (categorized as low, moderate or high frailty risk) was calculated at the time of discharge from the first hospital admission. Outcomes included ICU admission and death during the second hospital admission.

RESULTS

The cohort included 22 178 patients, of whom 1767 (8.0%) were categorized as having high frailty risk, 9464 (42.7%) as having moderate frailty risk, and 10 947 (49.4%) as having low frailty risk. One hundred patients (5.7%) with high frailty risk were admitted to the ICU, compared to 566 (6.0%) of those with moderate risk and 790 (7.2%) of those with low risk. After adjustment for age, sex, hospital, day of admission, time of admission and Laboratory-based Acute Physiology Score, the odds of ICU admission were not significantly different for patients with high (adjusted odds ratio [OR] 0.99, 95% confidence interval [CI] 0.78 to 1.23) or moderate (adjusted OR 0.97, 95% CI 0.86 to 1.09) frailty risk compared to those with low frailty risk. Among patients admitted to the ICU, 75 (75.0%) of those with high frailty risk died, compared to 317 (56.0%) of those with moderate risk and 416 (52.7%) of those with low risk. After multivariable adjustment, the risk of death after ICU admission was higher for patients with high frailty risk than for those with low frailty risk (adjusted OR 2.86, 95% CI 1.77 to 4.77).

INTERPRETATION

Among patients readmitted to hospital within 12 months, patients with high frailty risk were similarly likely as those with lower frailty risk to be admitted to the ICU but were more likely to die if admitted to ICU. The HFRS at hospital discharge can inform prognosis, which can help guide discussions for preferences for ICU care during future hospital stays.

The clinical frailty scale - does it predict outcome of the very-old in UK ICUs?

Introduction

The age of patients admitted into critical care in the UK is increasing. Clinical decisions for very-old patients, usually defined as over 80, can be challenging. Clinicians are frequently asked to predict outcomes as part of discussions around the pros and cons of an intensive care unit (ICU) admission. Measures of overall health in old age, such as the clinical frailty scale (CFS), are increasingly used to help guide these discussions. We aimed to understand the characteristics of the very-old critically unwell population in the UK and the associations between frailty and outcome of an ICU admission in our healthcare system (National Health Service, NHS).

Methods

Baseline characteristics, ICU interventions and outcomes (ICU- and 30-day mortality) were recorded for sequential admissions of very old patients to UK ICUs as part of the European VIP 1 and 2 studies. Patient characteristics, interventions and outcome measures were compared by frailty group using standard statistical tests. Multivariable logistic regression modelling was undertaken to test association between baseline characteristics, admission type and outcome.

Results

1858 participants were enrolled from 95 ICUs in the UK. The median age was 83. The median CFS was 4 (IQR 3-5). 30-day survival was significantly lower in the frail group (CFS > 4, 58%) compared to vulnerable (CFS = 4, 65%) and fit (CFS < 4 68%, p = .004). Sequential organ failure assessment (SOFA) score, reason for admission and CFS were all independently associated with increased 30-day mortality (p < .01).

Conclusion

In the UK, frailty is associated with an increase in mortality at 30-days following an ICU admission. At moderate frailty (CFS 5-6), three out of every five patients admitted survived to 30-days. This is a similar mortality to septic shock.

Clinical frailty and polypharmacy in older emergency critical care patients: a single-centre retrospective case series

BACKGROUND AND OBJECTIVES

Admission of complex and frail patients to critical care units is common. Little is known about the relationship between clinical frailty and polypharmacy measures in critical care patients or how a critical care admission affects polypharmacy.We sought to: (1) Describe the extent and relationship between clinical frailty and polypharmacy in a cohort of older emergency general critical care patients, and to (2) Describe the effect of the critical care pathway on patient polypharmacy measures.

METHODS

A retrospective evaluation was undertaken in all patients ≥70 years of age, admitted as emergencies to the general critical care units of a single large UK academic hospital, over a 2-year period (March 2016 to February 2018) (n=762). Patient Clinical Frailty Scale (CFS) and polypharmacy measures on admission were described and association was tested. Medication changes and documentation on care transitions were analysed in a randomly selected convenience cohort of critical care survivors (n=77).

RESULTS

On admission patients had a median of 9 (5;12) medicines, of which a median of 3 (2;5) were high-risk medicines. Polypharmacy (5-9 medicines) and hyperpolypharmacy (≥10 medicines) occurred in 80.7% (615/762) and 43.2% (329/762) of patients, respectively. A degree of frailty was the standard (median CFS 4 (3;5)) with 45.7% (348/762) CFS 4-5 and 20% (153/762) CFS ≥6. The patient median CFS increased by 1 with polypharmacy classification increments (p<0.001). In the survivor cohort, a median of 6 (4;8) and 5 (4;8) medication changes occurred on critical care and hospital discharges, respectively. A minority of patients had detailed medication continuity plans on care transitions.

CONCLUSIONS

Polypharmacy and frailty were very common in this UK single-centre cohort of older emergency critical care patients. There was a significant association between the degree of polypharmacy and frailty score. The critical care pathway created extensive changes in patient medication therapy. Medication changes on care transitions often lacked detailed documentation.

Differences in long-term outcomes between ICU patients with persistent delirium, non-persistent delirium and no delirium: A longitudinal cohort study

PURPOSE

Determine differences in physical, mental and cognitive outcomes 1-year post-ICU between patients with persistent delirium (PD), non-persistent delirium (NPD) and no delirium (ND).

MATERIALS AND METHODS

A longitudinal cohort study was performed in adult ICU patients of two hospitals admitted between July 2016-February 2020. Questionnaires on physical, mental and cognitive health, frailty and QoL were completed regarding patients' pre-ICU health status and 1-year post-ICU. Delirium data were from patients' total hospital stay. Patients were divided in PD (≥14 days delirium), NPD (<14 days delirium) or ND patients.

RESULTS

2400 patients completed both questionnaires, of whom 529 (22.0%) patients developed delirium; 35 (6.6%) patients had PD and 494 (93.4%) had NPD. Patients with delirium (PD or NPD) had worse outcomes in all domains compared to ND patients. Compared to NPD, more PD patients were frail (34.3% vs. 14.6%, p = 0.006) and fatigued (85.7% vs. 61.1%, p = 0.012). After adjustment, PD was significantly associated with long-term cognitive impairment only (aOR 3.90; 95%CI 1.31-11.63).

CONCLUSIONS

Patients with PD had a higher likelihood to develop cognitive impairment 1-year post-ICU compared to NPD or ND. Patients with PD and NPD were more likely to experience impairment on all health domains (i.e. physical, mental and cognitive), compared to ND patients.

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

INTRODUCTION

As new treatments have become established, more frail pre-ICU patients are being admitted to intensive care units (ICUs); this is creating new challenges to provide adequate care and to ensure that resources are allocated in an ethical and economical manner. This systematic review evaluates the current standard for assessing frailty on the ICU, including methods of assessment, time point of measurements, and cut-offs.

METHODS

A systematic search was conducted on MEDLINE, Clinical Trials, Cochrane Library, and Embase. Randomized and non-randomized controlled studies were included that evaluated diagnostic tools and ICU outcomes for frailty. Exclusion criteria were the following: studies without baseline assessment of frailty on ICU admission, studies in paediatric patients or pregnant women, and studies that targeted very narrow populations of ICU patients. Eligible articles were included until January 31, 2021. Methodological quality was assessed using the Newcastle-Ottawa Scale. No meta-analysis was performed, due to heterogeneity.

RESULTS

N = 57 articles (253,376 patients) were included using 19 different methods to assess frailty or a surrogate. Frailty on ICU admission was most frequently detected using the Clinical Frailty Scale (CFS) (n = 35, 60.3%), the Frailty Index (n = 5, 8.6%), and Fried's frailty phenotype (n = 6, 10.3%). N = 22 (37.9%) studies assessed functional status. Cut-offs, time points, and manner of baseline assessment of frailty on ICU admission varied widely. Frailty on ICU admission was associated with short- and long-term mortality, functional and cognitive impairment, increased health care dependency, and impaired quality of life post-ICU discharge.

CONCLUSIONS

Frailty assessment on the ICU is heterogeneous with respect to methods, cut-offs, and time points. The CFS may best reflect frailty in the ICU. Frailty assessments should be harmonized and performed routinely in the critically ill.

Correlation of patient-reported outcome measures to performance-based function in critical care survivors: PREDICTABLE

BACKGROUND

Establishing sequela following critical illness is a public health priority; however, recruitment and retention of this cohort make assessing functional outcomes difficult. Completing patient-reported outcome measures (PROMs) via telephone may improve participant and researcher involvement; however, there is little evidence regarding the correlation of PROMs to performance-based outcome measures in critical care survivors.

OBJECTIVES

The objective of this study was to assess the relationship between self-reported and performance-based measures of function in survivors of critical illness.

METHODS

This was a nested cohort study of patients enrolled within a previously published study determining predictors of disability-free survival. Spearman's correlation (r_s) was calculated between four performance-based outcomes (the Functional Independence Measure [FIM], 6-min walk distance [6MWD], Functional Reach Test [FRT], and grip strength) that were collected during a home visit 6 months following their intensive care unit admission, with two commonly used PROMs (World Health Organization Disability Assessment Scale 2.0 12 Level [WHODAS 2.0] and EuroQol-5 Dimension-5 Level [EQ-5D-5L]) obtained via phone interview (via the PREDICT study) at the same time point.

RESULTS

There were 38 PROMs obtained from 40 recruited patients (mean age = 59.8 ± 16 yrs, M:F = 24:16). All 40 completed the FIM and grip strength, 37 the 6MWD, and 39 the FRT. A strong correlation was found between the primary outcome of the WHODAS 2.0 with all performance-based outcomes apart from grip strength where a moderate correlation was identified. Although strong correlations were also established between the EQ-5D-5L utility score and the FIM, 6MWD, and FRT, it only correlated weakly with grip strength. The EQ-5D overall global health rating only had very weak to moderate correlations with the performance-based outcomes.

CONCLUSION

The WHODAS 2.0 correlated stronger across multiple performance-based outcome measures of functional recovery and is recommended for use in survivors of critical illness.

Long term cognitive and functional status in Danish ICU patients with COVID-19

Background

ICU admission due to COVID‐19 may result in cognitive and physical impairment. We investigated the long‐term cognitive and physical status of Danish ICU patients with COVID‐19.

Methods

We included all patients with COVID‐19 admitted to Danish ICUs between March 10 and May 19, 2020. Patients were the contacted prospectively at 6 and 12 months for follow‐up. Our primary outcomes were cognitive function and frailty at 6 and 12 months after ICU admission, estimated by the Mini Montreal Cognitive Assessment, and the Clinical Frailty Scale. Secondary outcomes were 6‐ and 12‐month mortality, health‐related quality of life (HRQoL) assessed by EQ‐5D‐5L, functional status (Barthel activities of daily living and Lawton–Brody instrumental activities of daily living), and fatigue (Fatigue Assessment Scale). The study had no information on pre‐ICU admission status for the participants.

Results

A total of 326 patients were included. The 6‐ and 12‐month mortality was 37% and 38%, respectively. Among the 204 six‐month survivors, 105 (51%) participated in the 6‐month follow‐up; among the 202 twelve‐month survivors, 95 (47%) participated in the 12‐month follow‐up. At 6 months, cognitive scores indicated impairment for 26% (95% confidence interval [CI], 11.4–12.4) and at 12 months for 17% (95% CI, 12.0–12.8) of participants. Frailty was indicated in 20% (95% CI, 3.4–3.9) at 6 months, and for 18% (95% CI, 3.3–3.8) at 12 months. Fatigue was reported by 52% at 6 months, and by 47% at 12 months. For HRQoL, moderate, severe, or extreme health problems were reported by 28% at 6 months, and by 25% at 12 months.

Conclusion

Long‐term cognitive, functional impairment was found in up to one in four of patients surviving intensive care for COVID‐19. Fatigue was present in nearly half the survivors at both 6 and 12 months. However, pre‐ICU admission status of the patients was unknown.

Mature neutrophils and a NF-κB-to-IFN transition determine the unifying disease recovery dynamics in COVID-19

Disease recovery dynamics are often difficult to assess, as patients display heterogeneous recovery courses. To model recovery dynamics, exemplified by severe COVID-19, we apply a computational scheme on longitudinally sampled blood transcriptomes, generating recovery states, which we then link to cellular and molecular mechanisms, presenting a framework for studying the kinetics of recovery compared with non-recovery over time and long-term effects of the disease. Specifically, a decrease in mature neutrophils is the strongest cellular effect during recovery, with direct implications on disease outcome. Furthermore, we present strong indications for global regulatory changes in gene programs, decoupled from cell compositional changes, including an early rise in T cell activation and differentiation, resulting in immune rebalancing between interferon and NF-κB activity and restoration of cell homeostasis. Overall, we present a clinically relevant computational framework for modeling disease recovery, paving the way for future studies of the recovery dynamics in other diseases and tissues.

The frailty, outcomes, recovery and care steps of critically ill patients (FORECAST) study: pilot study results

INTRODUCTION

Frailty is common in critically ill patients and is associated with increased morbidity and mortality. There remains uncertainty as to the optimal method/timing of frailty assessment and the impact of care processes and adverse events on outcomes is unknown. We conducted a pilot study to inform on the conduct, design and feasibility of a multicenter study measuring frailty longitudinally during critical illness, care processes, occurrence of adverse events, and resultant outcomes.

METHODS

Single-center pilot study enrolling patients over the age of 55 admitted to an Intensive Care Unit (ICU) for life-support interventions including mechanical ventilation, vasopressor therapy and/or renal replacement therapy. Frailty was measured on ICU admission and hospital discharge with the Clinical Frailty Scale (CFS), the Frailty Index (FI) and CFS at 6-month follow-up. Frailty was defined as CFS ≥ 5 and a FI ≥ 0.20. Processes of care and adverse events were measured during their ICU and hospital stay including nutritional support, mobility, nosocomial infections and delirium. ICU, hospital and 6 months were determined.

RESULTS

In 49 patients enrolled, the mean (SD) age was 68.7 ± 7.9 with a 6-month mortality of 29%. Enrollment was 1 patient/per week. Frailty was successfully measured at different time points during the patients stay/follow-up and varied by method/timing of assessment; by CFS and FI, respectively, in 17/49 (36%), 23/49 (47%) on admission, 22/33 (67%), 21/33 (63%) on hospital discharge and 11/30 (37%) had a CFS ≥ 5 at 6 months. Processes of care and adverse events were readily captured during the ICU and ward stay with the exception of ward nutritional data. ICU, hospital outcomes and follow-up outcomes were worse in those who were frail irrespective of ascertainment method. Pre-existing frailty remained static in survivors, but progressed in non-frail survivors.

DISCUSSION

In this pilot study, we demonstrate that frailty measurement in critically ill patients over the course and recovery of their illness is feasible, that processes of care and adverse events are readily captured, have developed the tools and obtained data necessary for the planning and conduct of a large multicenter trial studying the interaction between frailty and critical illness.

Using long-term predicted Quality of Life in ICU clinical practice to prepare patients for life post-ICU: A feasibility study

PURPOSE

To examine the feasibility of using the PREdicting PAtients' long-term outcome for Recovery (PREPARE) prediction model for Quality of Life (QoL) 1 year after ICU admission in ICU practice to prepare expected ICU survivors and their relatives for life post-ICU.

MATERIALS AND METHODS

Between June 2020 and February 2021, the predicted change in QoL after 1 year was discussed in 25 family conferences in the ICU. 13 physicians, 10 nurses and 19 patients and/or family members were interviewed to evaluate intervention feasibility in ICU practice. Interviews were analysed qualitatively using thematic coding.

RESULTS

Patients' median age was 68.0 years, five patients (20.0%) were female and seven patients (28.0%) died during ICU stay. Generally, study participants thought the intervention, which clarified the concept of QoL through visualization and served as a reminder to discuss QoL and expectations for life post-ICU, had merit. However, some participants, especially physicians, thought the prediction model needed more data on more severely ill ICU patients to curb uncertainty.

CONCLUSIONS

Using predicted QoL scores in ICU practice to prepare patients and family members for life after ICU discharge is feasible. After optimising the model and implementation strategy, its effectiveness can be evaluated in a larger trial.

Current perspectives on defining and mitigating frailty in relation to critical illness

Up to half of ICU survivors, many of whom were premorbidly well, will have residual functional and/or cognitive impairment and be vulnerable to future health problems. Frailty describes vulnerability to poor resolution of homeostasis after a stressor event but it is not clear whether the vulnerability seen after ICU correlates with clinical measures of frailty. In clinical practice, the scales most commonly used in critically ill patients are based on the assessment of severity and survival. Identification and monitoring of frailty in the ICU may be an alternative or complimentary approach, particularly if it helps explain vulnerability during the recovery and rehabilitation period. The purpose of this review is to discuss the use of tools to assess frailty status in the critically ill, and consider their importance in clinical practice. Amongst these, we consider biomarkers with potential to identify patients at greater or lesser risk of developing post-ICU vulnerability.

Prevalence and Course of Frailty in Survivors of Critical Illness

OBJECTIVES

Little is known about frailty that develops following critical illness. We sought to describe the prevalence of newly acquired frailty, its clinical course, and the co-occurrence of frailty with disability and cognitive impairment in survivors of critical illness.

DESIGN

Longitudinal prospective cohort study.

SETTING

Medical and surgical ICUs at five U.S. centers.

PATIENTS

Adult patients treated for respiratory failure and/or shock.

MEASUREMENTS AND MAIN RESULTS

We measured frailty with the Clinical Frailty Scale at baseline (i.e., study enrollment) and at 3 and 12 months postdischarge. We constructed alluvial diagrams to describe the course of frailty and Venn diagrams to describe the overlap of frailty with disability in activities of daily living and cognitive impairment. We included 567 participants a median (interquartile range) of 61 years old (51-70 yr old) with a high severity of illness (Acute Physiology and Chronic Health Evaluation II of 23). Frailty (Clinical Frailty Scale scores ≥ 5) was present in 135 of 567 (24%) at baseline, 239 of 530 (45%) at 3 months, and 163 of 445 (37%) at 12 months. Of those with frailty at 3- or 12-month follow-up, 61% were not frail at baseline. Transition to a worse frailty state occurred in 242 of 530 of patients (46%) between baseline and 3 months and in 179 of 445 of patients (40%) between baseline and 12 months. There were 376 patients with frailty, disability, or cognitive impairment at 3-month follow-up. Of these, 53 (14%) had frailty alone. At 12 months, 276 patients had frailty, disability, or cognitive impairment, 37 (13%) of whom had frailty alone.

CONCLUSIONS

Frailty is common among survivors of critical illness. In the majority, frailty is newly acquired. Roughly one in seven had frailty without co-occurring disability or cognitive impairment. Studies to understand outcomes of frailty that develops as the result of a critical illness and to identify modifiable risk factors for this potentially reversible syndrome are needed.

Physical, Mental, and Cognitive Health Status of ICU Survivors Before ICU Admission: A Cohort Study

OBJECTIVES

Although patient's health status before ICU admission is the most important predictor for long-term outcomes, it is often not taken into account, potentially overestimating the attributable effects of critical illness. Studies that did assess the pre-ICU health status often included specific patient groups or assessed one specific health domain. Our aim was to explore patient's physical, mental, and cognitive functioning, as well as their quality of life before ICU admission.

DESIGN

Baseline data were used from the longitudinal prospective MONITOR-IC cohort study.

SETTING

ICUs of four Dutch hospitals.

PATIENTS

Adult ICU survivors (n = 2,467) admitted between July 2016 and December 2018.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Patients, or their proxy, rated their level of frailty (Clinical Frailty Scale), fatigue (Checklist Individual Strength-8), anxiety and depression (Hospital Anxiety and Depression Scale), cognitive functioning (Cognitive Failure Questionnaire-14), and quality of life (Short Form-36) before ICU admission. Unplanned patients rated their pre-ICU health status retrospectively after ICU admission. Before ICU admission, 13% of all patients was frail, 65% suffered from fatigue, 28% and 26% from symptoms of anxiety and depression, respectively, and 6% from cognitive problems. Unplanned patients were significantly more frail and depressed. Patients with a poor pre-ICU health status were more often likely to be female, older, lower educated, divorced or widowed, living in a healthcare facility, and suffering from a chronic condition.

CONCLUSIONS

In an era with increasing attention for health problems after ICU admission, the results of this study indicate that a part of the ICU survivors already experience serious impairments in their physical, mental, and cognitive functioning before ICU admission. Substantial differences were seen between patient subgroups. These findings underline the importance of accounting for pre-ICU health status when studying long-term outcomes.

Translation and validation of the Korean version of the clinical frailty scale in older patients

Background

Frailty is a multidimensional syndrome that leads to an increase in vulnerability. Previous studies have suggested that frailty is associated with poor health-related outcomes. For frailty screening, the Clinical Frailty Scale (CFS) is a simple tool that is widely used in various translated versions. We aimed to translate the CSF into Korean and evaluated its contents and concurrent validity.

Methods

Translations and back-translations of the CFS were conducted independently. A multidisciplinary team decided the final CFS-K. Between August 2019 and April 2020, a total of 100 outpatient and inpatient participants aged ≥65 years were enrolled prospectively. The clinical characteristics were evaluated using the CFS-K. The CFS-K scores were compared with those of other frailty screening tools using Pearson’s correlation coefficient and Spearman’s rank correlation. The area under curve (AUC) for identifying the Eastern Cooperative Oncology Group Performance Status (ECOG PS) grade 3 or more was calculated for the CFS-K and other screening tools.

Results

The mean age of the participants was 76.5 years (standard deviation [SD], 7.0), and 63 (63%) participants were male. The mean CFS-K was 4.8 (SD, 2.5). Low body mass index (p = 0.013) and low score on the Korean version of the Mini-Mental State Examination (p < 0.001) were significantly associated with high CFS-K scores, except for those assigned to scale 9 (terminally ill). The CFS-K showed a significant correlation with other frailty screening tools (R = 0.7742–0.9190; p < 0.01), except in the case of those assigned to scale 9 (terminally ill). In comparison with other scales, the CFS-K identified ECOG PS grade 3 or more with the best performance (AUC = 0.99). Patients assigned to scale 9 on the CFS-K (terminally ill) had similar frailty scores to those assigned to scale 4 (vulnerable) or 5 (mildly frail).

Conclusions

In conclusion, the CFS-K is a valid scale for measuring frailty in older Korean patients. The CFS-K scores were significantly correlated with the scores of other scales. To evaluate the predictive and prognostic value of this scale, further larger-scale studies in various clinical settings are warranted.

Prevalência de fragilidade autorreferida em pacientes criticamente enfermos acordados e alertas

RESUMO Indivíduos criticamente enfermos internados em unidades de terapia intensiva (UTI) podem apresentar perdas de reservas físicas e cognitivas que aumentam a vulnerabilidade frente a eventos adversos, caracterizando a síndrome da fragilidade. O objetivo do estudo foi delinear a prevalência de fragilidade autorreferida em pacientes criticamente enfermos acordados e alertas internados na UTI de um hospital escola. Foram incluídos indivíduos adultos (≥18 anos), internados por, pelo menos 48 horas nas UTI de um hospital escola de Uberaba-MG, que encontravam-se alertas no momento da avaliação. O indivíduo foi estimulado a referir seu nível de fragilidade utilizando a Escala de Fragilidade Clínica (EFC). Indivíduos com EFC de 1 a 3 foram considerados não frágeis, 4 vulneráveis e maior que 5, frágeis. Foram incluídos 50 indivíduos com idade entre 44 e 78 anos com predominância do sexo masculino. A prevalência de indivíduos frágeis foi nula, 1 indivíduo foi considerado vulnerável e os demais foram considerados não frágeis com predominância da categoria 3, com 64% da população. Ao analisar os dados demográficos e clínicos nas diferentes pontuações da EFC não foi observado diferença estatisticamente significante entre sexo e idade entre as categorias analisadas. O índice de comorbidade funcional foi crescente nas categorias analisadas, (p=0,05). A prevalência de fragilidade autorreferida foi nula em pacientes criticamente enfermos internados em um hospital escola de Uberaba-MG. Escalas autorreferidas para avaliação de fragilidade podem ser incapazes de identificar acuradamente indivíduos frágeis.