A prospective multicenter cohort study of frailty in younger critically ill patients

In-Hospital Triage

The intensive care unit (ICU) is a finite and expensive resource with demand not infrequently exceeding capacity. Understanding ICU capacity strain is essential to gain situational awareness. Increased capacity strain can influence ICU triage decisions, which rely heavily on clinical judgment. Having an admission and triage protocol with which clinicians are very familiar can mitigate difficult, inappropriate admissions. This article reviews these concepts and methods of in-hospital triage.

Frailty in severe COVID-19 survivors after ICU admission. A prospective and multicenter study in Mexico

OBJECTIVE

To analyze the presence of frailty in survivors of severe COVID-19 admitted in the Intensive Care Unit (ICU) and followed six months after discharge.

DESIGN

An observational, prospective and multicenter, nation-wide study.

SETTING

Eight adult ICU across eight academic acute care hospitals in Mexico.

PATIENTS

All consecutive adult COVID-19 patients admitted in the ICU with acute respiratory failure between March 8, 2020 to February 28, 2021 were included. Frailty was defined according to the FRAIL scale, and was obtained at ICU admission and 6-month after hospital discharge.

INTERVENTIONS

None.

MAIN VARIABLES OF INTEREST

The primary endpoint was the frailty status 6-months after discharge. A regression model was used to evaluate the predictors during ICU stay associated with frailty.

RESULTS

196 ICU survivors were evaluated for basal frailty at ICU admission and were included in this analysis. After 6-months from discharge, 164 patients were evaluated for frailty: 40 patients (20.4%) were classified as non-frail, 67 patients (34.2%) as pre-frail and 57 patients (29.1%) as frail. After adjustment, the need of invasive mechanical ventilation was the only factor independently associated with frailty at 6 month follow-up (Odds Ratio [OR] 3.70, 95% confidence interval 1.40-9.81, P = .008).

CONCLUSIONS

Deterioration of frailty was reported frequently among ICU survivors with severe COVID-19 at 6-months. The need of invasive mechanical ventilation in ICU survivors was the only predictor independently associated with frailty.

The impact of frailty and rapid response team activation on patients admitted to the intensive care unit: A case-control matched, observational, single-centre cohort study

BACKGROUND

Frailty is a multi-dimensional syndrome associated with mortality and adverse outcomes in patients admitted to the intensive care unit (ICU). Further investigation is warranted to explore the interplay among factors such as frailty, clinical deterioration triggering a medical emergency team (MET) review, and outcomes following admission to the ICU.

METHODS

Single-centre, retrospective observational case-control study of adult patients (>18 years) admitted to a medical-surgical ICU with (cases) or without (controls) a preceding MET review between 4 h and 14 days prior. Matching was performed for age, ICU admission diagnosis, Acute Physiology and Chronic Health Evaluation III (APACHE III) score and the 8-point Clinical Frailty Scale (CFS). Cox proportional hazard regression modelling was performed to determine associations with 30-day mortality after admission to ICU.

RESULTS

A total of 2314 matched admissions were analysed. Compared to non-frail patients (CFS 1-4), mortality was higher in all frail patients (CFS 5-8), at 31% vs. 13%, and in frail patients admitted after MET review at 33%. After adjusting for age, APACHE, antecedent MET review and CFS in the Cox regression, mortality hazard ratio increased by 26% per CFS point and by 3% per APACHE III point, while a MET review was not an independent predictor. Limitations of medical treatment occurred in 30% of frail patients, either with or without a MET antecedent, and this was five times higher compared to non-frail patients.

CONCLUSION

Frail patients admitted to ICU have a high short-term mortality. An antecedent MET event was associated with increased mortality but did not independently predict short-term survival when adjusting for confounding factors. The intrinsic significance of frailty should be primarily considered during MET review of frail patients. This study suggests that routine frailty assessment of hospitalised patients would be helpful to set goals of care when admission to ICU could be considered.

Frailty in the cardiac intensive care unit: assessment and impact

Frailty, a clinical syndrome of increased vulnerability, due to diminished cognitive, physical, and physiological reserves is a growing concern in the cardiac intensive care unit (CICU). It contributes to morbidity, mortality, and complications and often exerts a bidirectional association with cardiovascular disease. Although it predominately affects older adults, frailty can also be observed in younger patients <65 years of age, with approximately 30% of those admitted in CICU are frail. Acute cardiovascular illness can also impair physical and cognitive functioning among survivors and these survivors often suffer from frailty and functional declines post-CICU discharge. Patients with frailty in the CICU often have higher comorbidity burden, and they are less likely to receive optimal therapy for their acute cardiovascular conditions. Given the significance of this geriatric syndrome, this review will focus on assessment, clinical outcomes, and interventions, in an attempt to establish appropriate assessment, management, and resource utilization in frail patients during and after CICU admission.

The impact of frailty on survival times up to one year among patients admitted to ICU with in-hospital cardiac arrest

BACKGROUND

In-hospital cardiac arrest (IHCA) is a serious medical emergency. When IHCA occurs in patients with frailty, short-term survival is poor. However, the impact of frailty on long-term survival is unknown.

METHODS

We performed a retrospective multicentre study of all critically ill adult (age ≥ 16 years) patients admitted to Australian intensive care units (ICU) between 1st January 2018 to 31st March 2022. We included all patients who had an IHCA within the 24 h before ICU admission with a documented Clinical Frail Scale (CFS). The primary outcome was median survival up to one year following ICU admission. The effect of frailty on one-year survival was assessed using a Cox proportional hazards model, adjusting for age, sex, comorbidities, sequential organ failure assessment (SOFA) score, and hospital type.

RESULTS

We examined 3769 patients, of whom 30.8% (n = 1160) were frail (CFS ≥ 5). The median survival was significantly shorter for patients with frailty (median [IQR] days 19 [1-365] vs 302 [9-365]; p < 0.001). The overall one-year mortality was worse for the patients with frailty when compared to the non-frail group (64.8% [95%CI 61.9-67.5] vs 36.4% [95%CI 34.5-38.3], p < 0.001). Each unit increment in the CFS was associated with 22% worse survival outcome (adjusted Hazard ratio = 1.22, 95%-CI 1.19-1.26), after adjustment for confounders. The survival trend was similar among patients who survived the hospitalization.

CONCLUSION

In this retrospective multicentre study, frailty was associated with poorer one-year survival in patients admitted to Australian ICUs following an IHCA.

Prevalence of frailty among chronic respiratory disease patients

BACKGROUND

Although frailty is one of the aging syndromes, it can occur at a younger age and in individuals with organ diseases. Identifying frailty and pre-frailty in patients with chronic respiratory diseases (CRDs) is an emerging assessment in the field of pulmonary medicine and rehabilitation. The aim of this study was to find out the prevalence of frailty among chronic respiratory disease patients.

METHODS

A single centre cross-sectional survey study with a total population of 381 patients, adults aged 18-90 years presenting to the pulmonology OPD was included based on the inclusion and exclusion criteria. Primary data collected were demographics, medical history, including comorbidities, use of long-term oxygen therapy (LTOT), BiPAP (Bilevel Positive Airway Pressure), previous hospital admissions, medication history and frailty assessment were done using the Fried frailty index.

RESULTS

Univariate analysis showed that sex, ECHO abnormality, patients using LTOT, BiPAP, home nebulizers and patients who did not attend the pulmonary rehabilitation programme had a significant association with frailty. Multivariate analysis showed that female sex, LTOT use and older age were significantly associated with frailty.

CONCLUSION

Frailty is frequent in CRD patients regardless of age. The prevalence of frailty has an association with female sex, patients using LTOT, and home BiPAP.

FRailty in Australian patients admitted to Intensive care unit after eLective CANCER-related SURGery: a retrospective multicentre cohort study (FRAIL-CANCER-SURG study)

BACKGROUND

The association between frailty and short-term and long-term outcomes in patients receiving elective surgery for cancer remains unclear, particularly in those admitted to the ICU.

METHODS

In this multicentre retrospective cohort study, we included adults ≥16 yr old admitted to 158 ICUs in Australia from January 1, 2018 to March 31, 2022 after elective surgery for cancer. We investigated the association between frailty and survival time up to 4 yr (primary outcome), adjusting for a prespecified set of covariates. We analysed how this association changed in specific subgroups (age categories [<65, 65-80, ≥80 yr], and those who survived hospitalisation), and over time by splitting the survival information at monthly intervals.

RESULTS

We included 35,848 patients (median follow-up: 18.1 months [inter-quartile range: 8.3-31.1 months], 19,979 [56.1%] male, median age 69.0 yr [inter-quartile range: 58.8-76.0 yr]). Some 3502 (9.8%) patients were frail (defined as clinical frailty scale ≥5). Frailty was associated with lower survival (hazard ratio: 1.72, 95% confidence interval [CI]: 1.59-1.86 compared with clinical frailty scale ≤4); this was concordant across several sensitivity analyses. Frailty was most strongly associated with mortality early on in follow-up, up to 10 months (hazard ratio: 1.39, 95% CI: 1.03-1.86), but this association plateaued, and its predictive capacity subsequently diminished with time up until 4 yr (1.96, 95% CI: 0.73-5.28). Frailty was associated with similar effects when stratified based on age, and in those who survived hospitalisation.

CONCLUSIONS

Frailty was associated with poorer outcomes after an ICU admission after elective surgery for cancer, particularly in the short term. However, its predictive capacity with time diminished, suggesting a potential need for longitudinal reassessment to ensure appropriate prognostication in this population.

Predictive validity of the Clinical Frailty Scale-España on the increase in dependency after hospital discharge

INTRODUCTION

The frailty present at hospital admission and the stressors to which patients are subjected during their stay may increase dependency at hospital discharge.

OBJECTIVES

To assess the predictive validity of the Clinical Frailty Scale-España (CFS-Es) on increased dependency at 3 and 12 months (m) after hospital discharge.

METHODOLOGY

Multicentre cohort study in 2020-2022. Including patients with >48 h stay in intensive care units (ICU) and non-COVID-19.

VARIABLES

pre-admission frailty (CFS-Es). Sex, age, days of stay (ICU and hospital), dependency on admission and at 3 m and 12 m after discharge (Barthel index), muscle weakness (Medical Research Council Scale sum score <48), hospital readmissions.

STATISTICS

descriptive and multivariate analysis.

RESULTS

254 cases were included. Thirty-nine per cent were women and the median [Q1-Q3] age was 67 [56-77] years. SAPS 3 on admission (median [Q1-Q3]): 62 [51-71] points. Frail patients on admission (CFS-Es 5-9): 58 (23%). Dependency on admission (n = 254) vs. 3 m after hospital discharge (n = 171) vs. 12 m after hospital discharge (n = 118): 1) Barthel 90-100: 82% vs. 68% vs. 65%. 2) Barthel 60-85: 15% vs. 15% vs. 20%. 3) Barthel 0-55: 3% vs. 17% vs. 15%. In the multivariate analysis, adjusted for the variables recorded, we observed that frail patients on admission (CFS-Es 5-9) are 2.8 times (95%CI: 1.03-7.58; p = 0.043) more likely to increase dependency (Barthel 90-100 to <90 or Barthel 85-60 to <60) at 3 m post-discharge (with respect to admission) and 3.5 times (95%CI: 1.18-10.30; p = 0.024) more likely to increase dependency at 12 m post-discharge. Furthermore, for each additional CFS-Es point there is a 1.6-fold (95%CI: 1.01-2.23; p = 0.016) greater chance of increased dependency in the 12 m following discharge.

CONCLUSIONS

CFS-Es at admission can predict increased dependency at 3 m and 12 m after hospital discharge.

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.

Impact of frailty on long-term survival in patients discharged alive from hospital after an ICU admission with COVID-19

Objective

Though frailty is associated with mortality, its impact on long-term survival after an ICU admission with COVID-19 is unclear. We aimed to investigate the association between frailty and long-term survival in patients after an ICU admission with COVID-19.

Design Setting and Participants

This registry-based multicentre, retrospective, cohort study included all patients ≥16 years discharged alive from the hospital following an ICU admission with COVID-19 and documented clinical frailty scale (CFS). Data from 118 ICUs between 01/01/2020 through 31/12/2020 in New Zealand and 31/12/2021 in Australia were reported in the Australian and New Zealand Intensive Care Society Adult Patient Database. The patients were categorised as 'not frail' (CFS 1-3), 'mildly frail' (CFS 4-5) and 'moderately-to-severely frail' (CFS 6-8).

Main Outcome Measures

The primary outcome was survival time up to two years, which we analysed using Cox regression models.

Results

We included 4028 patients with COVID-19 in the final analysis. 'Moderately-to-severely frail' patients were older (66.6 [56.3-75.8] vs. 69.9 [60.3-78.1]; p < 0.001) than those without frailty (median [interquartile range] 53.0 [40.1-64.6]), had higher sequential organ failure assessment scores (p < 0.001), and less likely to receive mechanical ventilation (p < 0.001) than patients without frailty or mild frailty. After adjusting for confounders, patients with mild frailty (adjusted hazards ratio: 2.31, 95%-CI: 1.75-3.05) and moderate-to-severe frailty (adjusted hazards ratio: 2.54, 95%-CI: 1.89-3.42) had higher mortality rates than those without frailty.

Conclusions

Frailty was independently associated with shorter survival times to two years in patients with severe COVID-19 in ANZ following hospital discharge. Recognising frailty provides individualised patient intervention in those with frailty admitted to ICUs with severe COVID-19.

Clinical trial registration

Not applicable.

The impact of prehabilitation on outcomes in frail and high-risk patients undergoing major abdominal surgery: A systematic review and meta-analysis

BACKGROUND & AIMS

Prehabilitation comprises multidisciplinary preoperative interventions including exercise, nutritional optimisation and psychological preparation aimed at improving surgical outcomes. The aim of this systematic review and meta-analysis was to determine the impact of prehabilitation on postoperative outcomes in frail and high-risk patients undergoing major abdominal surgery.

METHODS

Embase, Medline, CINAHAL and Cochrane databases were searched from January 2010 to January 2023 for randomised clinical trials (RCTs) and observational studies evaluating unimodal (exercise) or multimodal prehabilitation programmes. Meta-analysis was limited to length of stay (primary end point), severe postoperative complications (Clavien-Dindo Classification ≥ Grade 3) and the 6-minute walk test (6MWT). The analysis was performed using RevMan v5.4 software.

RESULTS

Sixteen studies (6 RCTs, 10 observational) reporting on 3339 patients (1468 prehabilitation group, 1871 control group) were included. The median (interquartile range) age was 74.0 (71.0-78.4) years. Multimodal prehabilitation was applied in fifteen studies and unimodal in one. Meta-analysis of nine studies showed a reduction in hospital length of stay (weighted mean difference -1.07 days, 95 % CI -1.60 to -0.53 days, P < 0.0001, I2 = 19 %). Ten studies addressed severe complications and a meta-analysis suggested a decline in occurrence by up to 44 % (odds ratio 0.56, 95 % CI 0.37 to 0.82, P < 0.004, I2 = 51 %). Four studies provided data on preoperative 6MWT. The pooled weighted mean difference was 40.1 m (95 % CI 32.7 to 47.6 m, P < 0.00001, I2 = 24 %), favouring prehabilitation.

CONCLUSION

Given the significant impact on shortening length of stay and reducing severe complications, prehabilitation should be encouraged in frail, older and high-risk adult patients undergoing major abdominal surgery.

Frailty and long-term survival among patients in Australian intensive care units with metastatic cancer (FRAIL-CANCER study): a retrospective registry-based cohort study

BACKGROUND

Recent advances in cancer therapeutics have improved outcomes, resulting in increasing candidacy of patients with metastatic cancer being admitted to intensive care units (ICUs). A large proportion of patients also have frailty, predisposing them to poor outcomes, yet the literature reporting on this is scarce. We aimed to assess the impact of frailty on survival in patients with metastatic cancer admitted to the ICU.

METHODS

In this retrospective registry-based cohort study, we used data from the Australia and New Zealand Intensive Care Society Adult Patient (age ≥16 years) database to identify patients with advanced (solid and haematological cancer) and a documented Clinical Frailty scale (CFS) admitted to 166 Australian ICUs. Patients without metastatic cancer were excluded. We analysed the effect of frailty (CFS 5-8) on long-term survival, and how this effect changed in specific subgroups (cancer subtypes, age [<65 years or ≥65 years], and those who survived hospitalisation). Because estimates tend to cluster within centres and vary between them, we used Cox proportional hazards regression models with robust sandwich variance estimators to assess the effect of frailty on survival time up to 4 years after ICU admission between groups.

FINDINGS

Between Jan 1, 2018, and March 31, 2022, 30 026 patients were eligible, and after exclusions 21 174 patients were included in the analysis; of these, 6806 (32·1%) had frailty, and 11 662 (55·1%) were male, 9489 (44·8%) were female, and 23 (0·1%) were intersex or self-reported indeterminate sex. The overall survival was lower for patients with frailty at 4 years compared with patients without frailty (29·5% vs 10·9%; p<0·0001). Frailty was associated with shorter 4-year survival times (adjusted hazard ratio 1·52 [95% CI 1·43-1·60]), and this effect was seen across all cancer subtypes. Frailty was associated with shorter survival times in patients younger than 65 years (1·66 [1·51-1·83]) and aged 65 years or older (1·40 [1·38-1·56]), but its effects were larger in patients younger than 65 years (pinteraction<0·0001). Frailty was also associated with shorter survival times in patients who survived hospitalisation (1·49 [1·40-1·59]).

INTERPRETATION

In patients with metastatic cancer admitted to the ICU, frailty was associated with poorer long-term survival. Patients with frailty might benefit from a goal-concordant time-limited trial in the ICU and will need suitable post-intensive care supportive management.

FUNDING

None.

Frailty assessment by two screening instruments in non-elderly patients with head and neck cancer

PURPOSE

Frailty assessment is often overlooked in non-elderly patients with cancer, possibly due to the lack of an effective frailty screening tool. This study aimed to evaluate the performance of two modern frailty screening tools, the Flemish version of the Triage Risk Screening Tool (fTRST) and the modified 5-Item Frailty Index (mFI-5), compared to the gold standard comprehensive geriatric assessment (GA) among non-elderly patients with head and neck cancer (HNC).

METHODS

We prospectively included 354 consecutive patients aged < 65 years with newly diagnosed HNC scheduled for definitive concurrent chemoradiotherapy (CCRT) at three academic hospitals in Taiwan between January 2020 and December 2022. Frailty assessment using the GA, fTRST, and mFI-5 was performed in all patients to evaluate the relationship between frailty and treatment outcomes.

RESULTS

The prevalence of frailty was 27.1%, 37.0%, and 42.4% based on GA, mFI-5, and fTRST, respectively. mFI-5 and fTRST demonstrated good predictive value in identifying frail patients compared to the GA. Patients with frailty, as defined by GA, mFI-5, and fTRST, exhibited higher risks of treatment-related complications, incomplete treatment, and poorer baseline quality of life (QoL). However, only GA showed significant prognostic value for overall survival.

CONCLUSIONS

Frailty assessment using fTRST and mFI-5 is valuable for predicting treatment-related adverse events, treatment tolerance, and QoL in non-elderly patients with HNC. Incorporating frailty assessment into the management of non-elderly cancer patients can aid in the identification of high-risk individuals. However, the performance of these tools varies, highlighting the need for further validation and refinement.

Frailty trajectories in ICU survivors: A comparison between the clinical frailty scale and the Tilburg frailty Indicator and association with 1 year mortality

PURPOSE

To test the agreement of the Clinical Frailty Scale (CFS) and the Tilburg Frailty Indicator (TFI), their association with 3, 6 months and 1-year mortality and the trajectory of frailty in a mixed population of ICU survivors.

MATERIAL AND METHODS

This is a prospective, multicenter, longitudinal study on ICU survivors ≥18 years old with an ICU stay >72 h. For each patient, sociodemographic and clinical data were collected. Frailty was assessed during ICU stay and at 3, 6, 12 months after ICU discharge, through both CFS and TFI.

RESULTS

124 patients with a mean age of 66 years old were enrolled. The baseline prevalence of frailty was 15.3% by CFS and 44.4% by TFI. Baseline CFS and TFI correlated but showed low agreement (Cohen's K = 0.23, p < 0.001). Baseline CFS score, but not TFI, was significantly associated to 1 year mortality. Moreover, CFS score during the follow-up was independently associated 1-year mortality (OR = 1.43; 95% CI: 1.18-1.73).

CONCLUSIONS

CFS and TFI identify different populations of frail ICU survivors. Frail patients before ICU according to CFS have a significantly higher mortality after ICU discharge. The CFS during follow-up is an independent negative prognostic factor of long-term mortality in the ICU population.

Self-reported symptoms experienced by intensive care unit patients: a prospective observational multicenter study

PURPOSE

The purpose of this study is to describe the prevalence, intensity and distress of five symptoms in intensive care unit (ICU) patients and to investigate possible predictive factors associated with symptom intensity.

METHODS

This is a prospective cohort study of ICU patients. A symptom questionnaire (i.e., Patient Symptom Survey) was used to describe the prevalence, intensity and distress of pain, thirst, anxiousness, tiredness, and shortness of breath over seven ICU days. Associations between symptom intensity and possible predictive factors were assessed using the general estimating equation (GEE) model.

RESULTS

Out of 603 eligible patients, 353 (Sample 2) were included in the present study. On the first ICU day, 195 patients (Sample 1) reported thirst as the most prevalent symptom (66%), with the highest mean intensity score (6.13, 95% confidence interval (CI) [5.7-6.56]). Thirst was the most prevalent (64%) and most intense (mean score 6.05, 95%CI [5.81-6.3]) symptom during seven days in the ICU. Anxiousness was the most distressful (mean score 5.24, 95%CI [4.32-6.15]) symptom on the first day and during seven days (mean score 5.46, 95%CI [4.95-5.98]). During seven days, analgesic administration and sepsis diagnosis were associated with increased thirst intensity. Older age and being mechanically ventilated were associated with decreased pain intensity, and analgesic administration was associated with increased pain intensity. Family visits and female gender were associated with increased intensity of anxiousness and shortness of breath, respectively.

CONCLUSIONS

Self-reporting ICU patients experienced a high and consistent symptom burden across seven days. Certain variables were associated with the degree of symptom intensity, but further research is required to better understand these associations.

The Clinical Frailty Scale for mortality prediction of old acutely admitted intensive care patients: a meta-analysis of individual patient-level data

BACKGROUND

This large-scale analysis pools individual data about the Clinical Frailty Scale (CFS) to predict outcome in the intensive care unit (ICU).

METHODS

A systematic search identified all clinical trials that used the CFS in the ICU (PubMed searched until 24th June 2020). All patients who were electively admitted were excluded. The primary outcome was ICU mortality. Regression models were estimated on the complete data set, and for missing data, multiple imputations were utilised. Cox models were adjusted for age, sex, and illness acuity score (SOFA, SAPS II or APACHE II).

RESULTS

12 studies from 30 countries with anonymised individualised patient data were included (n = 23,989 patients). In the univariate analysis for all patients, being frail (CFS ≥ 5) was associated with an increased risk of ICU mortality, but not after adjustment. In older patients (≥ 65 years) there was an independent association with ICU mortality both in the complete case analysis (HR 1.34 (95% CI 1.25-1.44), p < 0.0001) and in the multiple imputation analysis (HR 1.35 (95% CI 1.26-1.45), p < 0.0001, adjusted for SOFA). In older patients, being vulnerable (CFS 4) alone did not significantly differ from being frail. After adjustment, a CFS of 4-5, 6, and ≥ 7 was associated with a significantly worse outcome compared to CFS of 1-3.

CONCLUSIONS

Being frail is associated with a significantly increased risk for ICU mortality in older patients, while being vulnerable alone did not significantly differ. New Frailty categories might reflect its "continuum" better and predict ICU outcome more accurately.

TRIAL REGISTRATION

Open Science Framework (OSF: https://osf.io/8buwk/ ).

Prevalence of Frailty in ICU and its Impact on Patients' Outcomes

Introduction

Frailty describes a state or syndrome of reduced physical, physiologic, and cognitive reserve that increases vulnerability to acute illness. To study the prevalence of frailty in critically ill patients and find its association with resource utilization and short-term intensive care unit (ICU) outcomes.

Material and methods

This was a prospective observational study. All adult patients ≥50 years admitted to the ICU were included and frailty was assessed by the clinical frailty score (CFS). Data were collected on demography, coexisting illness, CFS, Acute Physiology and Chronic Health Evaluation II (APACHE-II), and Sequential Organ Failure Assessment Score (SOFA) scores. Patients were followed for 30 days. Outcome data were collected on organ supports provided, duration of ICU and hospital length of stay (LOS), and ICU and 30-day mortality.

Results

137 patients were enrolled in the study. The prevalence of frailty was 38.6%. Frail patients were older and had a more comorbid illness. APACHE-II and SOFA scores were 22.1 ± 7.0 and 7.2 ± 3.29, significantly higher in frail patients, respectively. There was a trend towards higher requirement for organ supports in frail patients. Median ICU and hospital LOS were 8 vs 6 and 20 vs 12 (frail vs nonfrail) days, respectively (p < 0.05). Intensive care unit mortality in frail and nonfrail patients was 28.3% and 23.8%, respectively (p = 0.56). Thirty-day mortality in frail patients was 49%, significantly higher compared with nonfrail patients (28.5%).

Conclusion

The prevalence of frailty in ICU patients was high. Frail patients were quite ill on ICU admission, and they had a prolonged ICU and hospital LOS. Increasing frailty score was associated with higher mortality at 30 days.

How to cite this article

Kalaiselvan MS, Yadav A, Kaur R, Menon A, Wasnik S. Prevalence of Frailty in ICU and its Impact on Patients' Outcomes. Indian J Crit Care Med 2023;27(5):335-341.

Sex differences in long-term survival after intensive care unit treatment for sepsis: A cohort study

OBJECTIVE

To determine the effect of sex on sepsis-related ICU admission and survival for up to 3-years.

METHODS

Retrospective cohort study of adults admitted to Australian ICUs between 2018 and 2020. Men and women with a primary diagnosis of sepsis were included. The primary outcome of time to death for up to 3-years was examined using Kaplan Meier plots. Secondary outcomes included the duration of ICU and hospital stay.

RESULTS

Of 523,576 admissions, there were 63,039 (12·0%) sepsis-related ICU admissions. Of these, there were 50,956 patients (43·4% women) with 3-year survival data. Men were older (mean age 66·5 vs 63·6 years), more commonly received mechanical ventilation (27·4% vs 24·7%) and renal replacement therapy (8·2% vs 6·8%) and had worse survival (Hazard Ratio [HR] 1·11; 95% Confidence Interval [CI] 1·07 to 1·14, P<0·001) compared to women. The duration of hospital and ICU stay was longer for men, compared to women (median hospital stay, 9.8 vs 9.4 days; p<0.001 and ICU stay, 2.7 vs 2.6 days; p<0.001).

CONCLUSION

Men are more likely to be admitted to ICU with sepsis and have worse survival for up to 3-years. Understanding causal mechanisms of sex differences may facilitate the development of targeted sepsis strategies.

Frailty is a stronger predictor of death in younger intensive care patients than in older patients: a prospective observational study

BACKGROUND

While frailty is a known predictor of adverse outcomes in older patients, its effect in younger populations is unknown. This prospective observational study was conducted in a tertiary-level mixed ICU to assess the impact of frailty on long-term survival in intensive care patients of different ages.

METHODS

Data on premorbid frailty (Clinical Frailty Score; CFS), severity of illness (the Simplified Acute Physiology Score, third version; SAPS3), limitations of care and outcome were collected in 817 adult ICU patients. Hazard ratios (HR) for death within 180 days after ICU admission were calculated. Unadjusted and adjusted analyses were used to evaluate the association of frailty with outcome in different age groups.

RESULTS

Patients were classified into predefined age groups (18-49 years (n = 241), 50-64 (n = 188), 65-79 (n = 311) and 80 years or older (n = 77)). The proportion of frail (CFS ≥ 5) patients was 41% (n = 333) in the overall population and increased with each age strata (n = 46 (19%) vs. n = 67 (36%) vs. n = 174 (56%) vs. n = 46 (60%), P < 0.05). Frail patients had higher SAPS3, more treatment restrictions and higher ICU mortality. Frailty was associated with an increased risk of 180-day mortality in all age groups (HR 5.7 (95% CI 2.8-11.4), P < 0.05; 8.0 (4.0-16.2), P < 0.05; 4.1 (2.2-6.6), P < 0.05; 2.4 (1.1-5.0), P = 0.02). The effect remained significant after adjustment for SAPS3, comorbidity and limitations of treatment only in patients aged 50-64 (2.1 (1.1-3.1), P < 0.05).

CONCLUSIONS

Premorbid frailty is common in ICU patients of all ages and was found in 55% of patients aged under 64 years. Frailty was independently associated with mortality only among middle-aged patients, where the risk of death was increased twofold. Our study supports the use of frailty assessment in identifying younger ICU patients at a higher risk of death.

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.

The Clinical Frailty Scale can indicate prognosis and care requirements on discharge in oncology and haemato-oncology inpatients: A cohort study

OBJECTIVES

Routinely used performance status scales, assessing patients' suitability for cancer treatment, have limited ability to account for multimorbidity, frailty and cognition. The Clinical Frailty Scale (CFS) is a suggested alternative, but research detailing its use in oncology is limited. This study aims to evaluate if CFS is associated with prognosis and care needs on discharge in oncology inpatients.

METHODS

We evaluated a large, single-centre cohort study in this research. CFS was recorded for adult inpatients at a Regional Cancer Centre. The associations between CFS, age, tumour type, discharge destination and care requirements and survival were evaluated.

RESULTS AND CONCLUSIONS

A total of 676 patients were included in the study. Levels of frailty were high (Median CFS 6, 81.8% scored ≥5) and CFS correlated with performance status (R = 0.13: P = 0.047). Patients who were frail (CFS ≥ 5) were less likely to be discharged home (62.9%) compared with those who were not classed as frail (86.1%) (OR 3.6 [95%CI 2.1 to 6.3]: P < 0.001). Higher CFS was significantly associated with poorer prognosis in all ages. Solid organ malignancy (hazard ratio [HR] 2.60 [95%CI 2.05-3.32]) and CFS (HR 1.43 [95%CI 1.29-1.59]; P < 0.001) were independently associated with poorer survival. This study demonstrated that CFS may help predict prognosis in adult oncology inpatients of any age. This may aid informed shared decision-making in this setting. Future work should establish if routine CFS measurement can aid the appropriate prescription of systemic therapy and enable early conversations about discharge planning.

Impact of frailty on clinical outcomes in patients with and without COVID-19 pneumonitis admitted to intensive care units in Australia and New Zealand: a retrospective registry data analysis

BACKGROUND

It is unclear if the impact of frailty on mortality differs between patients with viral pneumonitis due to COVID-19 or other causes. We aimed to determine if a difference exists between patients with and without COVID-19 pneumonitis.

METHODS

This multicentre, retrospective, cohort study using the Australian and New Zealand Intensive Care Society Adult Patient Database included patients aged ≥ 16 years admitted to 153 ICUs between 01/012020 and 12/31/2021 with admission diagnostic codes for viral pneumonia or acute respiratory distress syndrome, and Clinical Frailty Scale (CFS). The primary outcome was hospital mortality.

RESULTS

A total of 4620 patients were studied, and 3077 (66.6%) had COVID-19. The patients with COVID-19 were younger (median [IQR] 57.0 [44.7-68.3] vs. 66.1 [52.0-76.2]; p < 0.001) and less frail (median [IQR] CFS 3 [2-4] vs. 4 [3-5]; p < 0.001) than non-COVID-19 patients. The overall hospital mortality was similar between the patients with and without COVID-19 (14.7% vs. 14.9%; p = 0.82). Frailty alone as a predictor of mortality showed only moderate discrimination in differentiating survivors from those who died but was similar between patients with and without COVID-19 (AUROC 0.68 vs. 0.66; p = 0.42). Increasing frailty scores were associated with hospital mortality, after adjusting for Australian and New Zealand Risk of Death score and sex. However, the effect of frailty was similar in patients with and without COVID-19 (OR = 1.29; 95% CI: 1.19-1.41 vs. OR = 1.24; 95% CI: 1.11-1.37).

CONCLUSION

The presence of frailty was an independent risk factor for mortality. However, the impact of frailty on outcomes was similar in COVID-19 patients compared to other causes of viral pneumonitis.

Anticipating need for intensive care in the healthcare trajectory of patients with chronic disease: A qualitative study among specialists

Introduction

We investigated the reflections and perceptions of non-ICU physicians about anticipating the need for ICU admission in case of acute decompensation in patients with chronic disease.

Methods

We performed a qualitative multicentre study using semi-structured interviews among non-ICU specialist physicians. The interview guide, developed in advance, focused on 3 questions: (1) What is your perception of ICU care? (2) How do you think advance directives can be integrated into the patient’s healthcare goals? and (3) How can the possibility of a need for ICU admission be integrated into the patient’s healthcare goals? Interviews were recorded, transcribed and analysed by thematic analysis. Interviews were performed until theoretical saturation was reached.

Results

In total, 16 physicians (8 women, 8 men) were interviewed. The main themes related to intensive care being viewed as a distinct specialty, dispensing very technical care, and with major human and ethical challenges, especially regarding end-of-life issues. The participants also mentioned the difficulty in anticipating an acute decompensation, and the choices that might have to be made in such situations. The timing of discussions about potential decompensation of the patient, the medical culture and the presence of advance directives are issues that arise when attempting to anticipate the question of ICU admission in the patient’s healthcare goals or wishes.

Conclusion

This study describes the perceptions that physicians treating patients with chronic disease have of intensive care, notably that it is a distinct and technical specialty that presents challenging medical and ethical situations. Our study also opens perspectives for actions that could promote a pluridisciplinary approach to anticipating acute decompensation and ICU requirements in patients with chronic disease.

Frailty and clinical outcomes in critically ill patients with cancer: A cohort study

INTRODUCTION

Our aim was to assess impact of frailty on short-term clinical outcomes in critically ill patients with cancer.

MATERIALS AND METHODS

We conducted a cohort study at a medical and surgical intensive care unit (ICU) in Argentina. We included 269 consecutive patients, ≥18 years old, with diagnosis of cancer. We recorded demographic and clinical characteristics, Clinical Frailty Scale (CFS, ≥5 defined a patient as frail), and the number and duration of organ support therapies during ICU stay. Primary outcome was ICU and hospital mortality.

RESULTS

Median age 69 (range 20-90); 152 (56%) patients were male. Sixty-eight (25.2%) patients presented frailty at admission. Older adults (≥65 years old) made up 62.8% of patients. Frail patients were 69.7 years versus 64.4 years for non-frail, P = 0.007, with higher Acute Physiology and Chronic Health Evaluation II (APACHE II) 14.7 ± 7 versus 10.8 ± 6, P = 0.001 and Simplified Acute Physiology Score (SAPS II) 40.1 ± 17 versus 28.7 ± 14, P = 0.001, respectively. After adjusting by age, severity score, type of admission, and type of cancer, frailty was independently associated with hospital mortality, odds ratio (OR) 4.87 (95% confidence interval [CI], 2.19-11.19, P ≤0.001). Median ICU length of stay was five days (interquartile range [IQR] 3-7) versus six days (IQR 3.8-9), in non-frail versus frail patients, respectively (P = 0.100), and hospital stay was nine days (IQR 6-17) versus 11.5 days (IQR 7-19.5) in non-frail versus frail patients, respectively (P = 0.085).

DISCUSSION

Frailty as a medical condition was strongly associated with worse clinical outcomes among oncologic critically ill patients.

Efficacy of power training to improve physical function in individuals diagnosed with frailty and chronic disease: A meta-analysis

Muscle power training with emphasis on high-velocity of concentric movement improves physical functionality in healthy older adults, and, maybe superior to traditional exercise programs. Power training may also be advantageous for patients with acute and chronic illnesses, as well as frail individuals. To determine the efficacy of power training compared with traditional resistance training on physical function outcomes in individuals diagnosed with frailty, acute illness or chronic disease. PubMed (MEDLINE), CINAHL, PEDro, Web of Science, and Google Scholar. (1) at least one study group receives muscle power training of randomized controlled trial (RCT) (2) study participants diagnosed as prefrail, frail or have an ongoing acute or chronic disease, condition or illness; (3) study participants over the age of 18; (4) publication in English language; (5) included physical function as the primary or secondary outcome measures. Two independent reviewers assessed articles for inclusion and graded the methodological quality using Cochrane Risk-of-Bias tool for RCTs. Fourteen RCTs met the inclusion criteria. In seven studies, muscle power training was more effective at improving physical function compared to control activities with a mean fixed effect size (ES) of 0.41 (p = 0.006; 95% CI 0.12 to 0.71). Power training and conventional resistance training had similar effectiveness in eight studies with a mean fixed ES of 0.10 (p = 0.061; 95% CI -0.01 to 0.40). Muscle power training is just as efficacious for improving physical function in individuals diagnosed with frailty and chronic disease when compared to traditional resistance training. The advantages of power training with reduced work per session may support power training as a preferential exercise modality for clinical populations. The findings should be interpreted with caution since generalizability is questioned due to the heterogeneity of patient populations enrolled and participants were relatively mobile at baseline.

Effects of frailty on postoperative clinical outcomes of aneurysmal subarachnoid hemorrhage: results from the National Inpatient Sample database

Background

This study aimed to investigate the potential effect of preoperative frailty on postoperative clinical outcomes of patients with aneurysmal subarachnoid hemorrhage (aSAH).

Methods

Data of patients aged 18 years and older who were diagnosed with subarachnoid hemorrhage or intracerebral hemorrhage, underwent aneurysm repair surgical intervention from 2005 to 2014. A retrospective database analysis was performed based on U.S. National Inpatient Sample (NIS) from 2005 to 2014. Frailty was determined using the Johns Hopkins Adjusted Clinical Groups (ACG) frailty-defining diagnoses indicator. Patients were stratified into frail and non-frail groups and the study endpoints were incidence of postoperative complications and related adverse clinical outcomes.

Results

Among 20,527 included aSAH patients, 2303 (11.2%) were frail and 18,224 (88.8%) were non-frail. Significant differences were found between frailty and non-frailty groups in the four clinical outcomes (all p < 0.05). Multivariate analysis showed that frailty was associated with significant higher risks of discharge to institutional care (aOR: 2.50, 95%CI: 2.10–2.97), tracheostomy or gastrostomy tube replacement (aOR: 4.41, 95%CI: 3.81–5.10) and postoperative complications (aOR: 3.29, 95%CI: 2.55–4.25) but a lower risk of death in hospital (aOR: 0.40, 95%CI: 0.33–0.49) as compared with non-frailty. Stratified analysis showed the impact of frailty on some of the outcomes were greater among patients younger than 65 years than their older counterparts.

Conclusions

Frailty is significantly correlated with the increased risk of discharge to institutional care, tracheostomy or gastrostomy tube placement, and postoperative complications but with the reduced risk of in-hospital mortality outcomes after aneurysm repair. Frailty seems to have greater impact among younger adults than older ones. Baseline frailty evaluation could be applied to risk stratification for aSAH patients who were undergoing surgery.

Improving physical function of patients following intensive care unit admission (EMPRESS): protocol of a randomised controlled feasibility trial

INTRODUCTION

Physical rehabilitation delivered early following admission to the intensive care unit (ICU) has the potential to improve short-term and long-term outcomes. The use of supine cycling together with other rehabilitation techniques has potential as a method of introducing rehabilitation earlier in the patient journey. The aim of the study is to determine the feasibility of delivering the designed protocol of a randomised clinical trial comparing a protocolised early rehabilitation programme including cycling with usual care. This feasibility study will inform a larger multicentre study.

METHODS AND ANALYSIS

90 acute care medical patients from two mixed medical-surgical ICUs will be recruited. We will include ventilated patients within 72 hours of initiation of mechanical ventilation and expected to be ventilated a further 48 hours or more. Patients will receive usual care or usual care plus two 30 min rehabilitation sessions 5 days/week.Feasibility outcomes are (1) recruitment of one to two patients per month per site; (2) protocol fidelity with >75% of patients commencing interventions within 72 hours of mechanical ventilation, with >70% interventions delivered; and (3) blinded outcome measures recorded at three time points in >80% of patients. Secondary outcomes are (1) strength and function, the Physical Function ICU Test-scored measured on ICU discharge; (2) hospital length of stay; and (3) mental health and physical ability at 3 months using the WHO Disability Assessment Schedule 2. An economic analysis using hospital health services data reported with an embedded health economic study will collect and assess economic and quality of life data including the Hospital Anxiety and Depression Scales core, the Euroqol-5 Dimension-5 Level and the Impact of Event Score.

ETHICS AND DISSEMINATION

The study has ethical approval from the South Central Hampshire A Research Ethics Committee (19/SC/0016). All amendments will be approved by this committee. An independent trial monitoring committee is overseeing the study. Results will be made available to critical care survivors, their caregivers, the critical care societies and other researchers.

TRIAL REGISTRATION NUMBER

NCT03771014.

Hospital re-admission after critical care survival: a systematic review and meta-analysis

Survivors of critical illness frequently require increased healthcare resources after hospital discharge. We undertook a systematic review and meta-analysis to assess hospital re-admission rates following critical care admission and to explore potential re-admission risk factors. We searched the MEDLINE, Embase and CINAHL databases on 05 March 2020. Our search strategy incorporated controlled vocabulary and text words for hospital re-admission and critical illness, limited to the English language. Two reviewers independently applied eligibility criteria and assessed quality using the Newcastle Ottawa Score checklist and extracted data. The primary outcome was acute hospital re-admission in the year after critical care discharge. Of the 8851 studies screened, 87 met inclusion criteria and 41 were used within the meta-analysis. The analysis incorporated data from 3,897,597 patients and 741,664 re-admission episodes. Pooled estimates for hospital re-admission after critical illness were 16.9% (95%CI: 13.3-21.2%) at 30 days; 31.0% (95%CI: 24.3-38.6%) at 90 days; 29.6% (95%CI: 24.5-35.2%) at six months; and 53.3% (95%CI: 44.4-62.0%) at 12 months. Significant heterogeneity was observed across included studies. Three risk factors were associated with excess acute care rehospitalisation one year after discharge: the presence of comorbidities; events during initial hospitalisation (e.g. the presence of delirium and duration of mechanical ventilation); and subsequent infection after hospital discharge. Hospital re-admission is common in survivors of critical illness. Careful attention to the management of pre-existing comorbidities during transitions of care may help reduce healthcare utilisation after critical care discharge. Future research should determine if targeted interventions for at-risk critical care survivors can reduce the risk of subsequent rehospitalisation.

Frailty and mortality associations in patients with COVID ‐19: A Systematic Review and Meta‐analysis

Background

Observational data during the pandemic have demonstrated mixed associations between frailty and mortality.

Aim

To examine associations between frailty and short‐term mortality in patients hospitalised with coronavirus disease 2019 (COVID‐19).

Methods

In this systematic review and meta‐analysis, we searched PubMed, Embase and the COVID‐19 living systematic review from 1 December 2019 to 15 July 2021. Studies reporting mortality and frailty scores in hospitalised patients with COVID‐19 (age ≥18 years) were included. Data on patient demographics, short‐term mortality (in hospital or within 30 days), intensive care unit (ICU) admission and need for invasive mechanical ventilation (IMV) were extracted. The quality of studies was assessed using the Newcastle−Ottawa Scale.

Results

Twenty‐five studies reporting 34 628 patients were included. Overall, 26.2% (n = 9061) died. Patients who died were older (76.7 ± 9.6 vs 69.2 ± 13.4), more likely male (risk ratio (RR) = 1.08; 95% confidence interval (CI): 1.06–1.11) and had more comorbidities. Fifty‐eight percent of patients were frail. Adjusting for age, there was no difference in short‐term mortality between frail and non‐frail patients (RR = 1.04; 95% CI: 0.84–1.28). The non‐frail patients were commonly admitted to ICU (27.2% (4256/15639) vs 29.1% (3567/12274); P = 0.011) and had a higher mortality risk (RR = 1.63; 95% CI: 1.30–2.03) than frail patients. Among patients receiving IMV, there was no difference in mortality between frail and non‐frail (RR = 1.62; 95% CI 0.93–2.77).

Conclusion

This systematic review did not demonstrate an independent association between frailty status and short‐term mortality in patients with COVID‐19. Patients with frailty were less commonly admitted to ICU and non‐frail patients were more likely to receive IMV and had higher mortality risk. This finding may be related to allocation decisions for patients with frailty amidst the pandemic.

Characteristics and Outcomes of Patients With Frailty Admitted to ICU With Coronavirus Disease 2019: An Individual Patient Data Meta-Analysis

Supplemental Digital Content is available in the text.

Frailty is often used in clinical decision-making for patients with coronavirus disease 2019, yet studies have found a variable influence of frailty on outcomes in those admitted to the ICU. In this individual patient data meta-analysis, we evaluated the characteristics and outcomes across the range of frailty in patients admitted to ICU with coronavirus disease 2019.

Clinical Significance of Frailty on Treatment Outcome in Nongeriatric Patients With Head and Neck Cancer and Esophageal Cancer Undergoing Curative-Intent Concurrent Chemoradiotherapy

BACKGROUND

Whether the prevalence of frailty and its clinical significance are relevant to treatment outcomes in younger (aged < 65 years) cancer patients remains uncertain. This study aimed to evaluate the impact of frailty on treatment outcomes in younger cancer patients with head and neck and esophageal malignancy.

MATERIAL AND METHODS

This multicenter prospective study recruited 502 patients with locally advanced head and neck and esophageal cancer during 2016-2017 in Taiwan, aged 20-64 years who received curative-intent concurrent chemoradiotherapy (CCRT) as first-line antitumor treatment. Baseline frailty assessment using geriatric assessment (GA) was performed for each patient within 7 days before CCRT initiation.

RESULTS

Frailty was observed in 169 (33.7%) of 502 middle-aged patients. Frail patients had significantly higher incidences of chemotherapy incompletion (16.6% versus 3.3%, P < .001) and radiotherapy incompletion (16.6% versus 3.6%, P < .001) than fit patients. During CCRT, frail patients had a significantly higher percentage of hospitalizations (42.0% versus 24.6%, P < .001) and a trend toward a higher percentage of emergency room visits (37.9% versus 30.0%, P = .08) than fit patients. Frail patients more likely had a significantly higher incidence of grade ≥ 3 adverse events than fit patients during CCRT. The 1-year survival rate was 68.7% and 85.2% (hazard ratio 2.56, 95% confidence interval 1.80-3.63, P < .001) for frail and fit patients, respectively.

CONCLUSIONS

This study demonstrated the significance of pretreatment frailty on treatment tolerance, treatment-related toxicity, and survival outcome in younger patients with head and neck and esophageal cancer undergoing CCRT. While GA is commonly targeted toward the older population, frailty assessment by GA may also be utilized in younger patients for decision-making guidance and prognosis prediction.

Frailty Triage: Is Rationing Intensive Medical Treatment on the Grounds of Frailty Ethical?

In early 2020, a number of countries developed and published intensive care triage guidelines for the pandemic. Several of those guidelines, especially in the UK, encouraged the explicit assessment of clinical frailty as part of triage. Frailty is relevant to resource allocation in at least three separate ways, through its impact on probability of survival, longevity and quality of life (though not a fourth-length of intensive care stay). I review and reject claims that frailty-based triage would represent unjust discrimination on the grounds of age or disability. I outline three important steps to improve the ethical incorporation of frailty into triage. Triage criteria (ie frailty) should be assessed consistently in all patients referred to the intensive care unit. Guidelines must make explicit the ethical basis for the triage decision. This can then be applied, using the concept of triage equivalence, to other (non-frail) patients referred to intensive care.

Frailty is not independently associated with intensive care unit length of stay: An observational study

BACKGROUND

Frailty is independently associated with morbidity and mortality in critically ill patients. However, the association between preadmission frailty and the degree of treatment received in the intensive care unit (ICU) remains unclear.

OBJECTIVE

To describe patient length of stay in an ICU and the treatments provided according to the extent of patient frailty.

METHODS

Single-centre retrospective cohort study of adult patients admitted to a tertiary ICU between January 2018 and December 2019. Frailty was assessed using the Clinical Frailty Scale (CFS). The primary outcome was ICU length of stay stratified by CFS score (1-8). Secondary outcomes were the proportion of patients with each CFS score treated with vasoactive agents, invasive ventilation, noninvasive ventilation, renal replacement therapy, and tracheostomy. Poisson regression and competing risks regression was used to analyse associations between ICU length of stay and potential confounders.

RESULTS

The study cohort comprised 2743 patients, with CFS scores known for 2272 (83%). Length of stay in the ICU increased with each increment in the CFS up to a score of 5, beyond which it decreased with higher frailty scores. After adjusting for age, illness severity, admission type, and treatment limitation, CFS scores were not independently associated with length of stay in the ICU (P = 0.31). The proportion of patients receiving specific ICU treatments peaked at different CFS scores, being highest for vasoactive agents at CFS 5 (47%), invasive ventilation CFS 3 (51%), noninvasive ventilation CFS 6 (11%), renal replacement therapy CFS 6 (8.2%), and tracheostomy CFS 5 (2.2%). Increasing frailty was associated with increased mortality and discharge to a destination other than home.

CONCLUSIONS

The extent of frailty is not independently associated with length of stay in the ICU. The proportion of patients receiving specific ICU treatments peaked at different CFS scores.

Evaluation of a hypothetical decision-support tool for intensive care triage of patients with coronavirus disease 2019 (COVID-19)

Background: At the start of the coronavirus disease 2019 (COVID-19) pandemic there was widespread concern about potentially overwhelming demand for intensive care and the need for intensive care unit (ICU) triage. In March 2020, a draft United Kingdom (UK) guideline proposed a decision-support tool (DST). We sought to evaluate the accuracy of the tool in patients with COVID-19. Methods: We retrospectively identified patients in two groups: referred and not referred to intensive care in a single UK national health service (NHS) trust in April 2020. Age, Clinical Frailty Scale score (CFS), and co-morbidities were collected from patients’ records and recorded, along with ceilings of treatment and outcome. We compared the DST, CFS, and age alone as predictors of mortality, and treatment ceiling decisions. Results: In total, 151 patients were included in the analysis, with 75 in the ICU and 76 in the non-ICU-reviewed groups. Age, clinical frailty and DST score were each associated with increased mortality and higher likelihood of treatment limitation (p-values all <.001). A DST cut-off score of >8 had 65% (95% confidence interval (CI) 51%-79%) sensitivity and 63% (95% CI 54%-72%) specificity for predicting mortality. It had a sensitivity of 80% (70%-88%) and specificity of 96% (95% CI 90%-100%) for predicting treatment limitation. The DST was more discriminative than age alone (p<0.001), and potentially more discriminative than CFS (p=0.08) for predicting treatment ceiling decisions. Conclusions: During the first wave of the COVID-19 pandemic, in a hospital without severe resource limitations, a hypothetical decision support tool was limited in its predictive value for mortality, but appeared to be sensitive and specific for predicting treatment limitation.

Long term outcomes following critical care hospital admission: A prospective cohort study of UK biobank participants✰,★

BACKGROUND

: This study aimed to understand the impact of a critical care admission on long-term outcomes, compared to other hospitalised patients without a critical care encounter. A secondary aim was to examine the interrelationship between emotional, physical, and social problems during recovery.

METHODS

: We utilised data from the UK Biobank, an on-going, prospective population-based cohort study. We employed propensity score matching to assess differences in outcomes between patients with a critical care encounter and patients admitted to the hospital (first admission to hospital available) without critical care. Structural equation modelling was used to analyse emotional, physical and social outcomes following critical illness and the relationships between these health domains.

FINDINGS

: Data from 1,618 patients were analysed. The median time to follow-up in the critical care cohort was 4427 days (IQR:788-6146) vs 4516 days (IQR: 811-6369) in the non-critical care, hospitalised cohort. Across the two time periods assessed (pre and post 2000), patients exposed to critical care were more likely to experience mental health issues such as depression (p < 0.01) and social isolation (p = 0.01) following discharge from hospital. The critical care cohort were also more likely to have social problems such as the requirement for government funded welfare support (p = 0.02). In the critical care cohort, social and emotional health were closely correlated (p < 0.001, 95% CI:0.33-0.54). The nature of physical problems changed over time; pre-2000 there was a significant difference between the critical and non-critical care in physical outcomes following discharge from hospital, however, there was no difference detected between the two cohorts post-2000.

INTERPRETATION

This cohort study has demonstrated that survivors of critical illness have different psycho-social outcomes to matched patients, hospitalised without a critical care encounter.

FUNDING

JM is funded by a THIS.Institute (University of Cambridge) Research Fellowship (PD-2019-02-16). AHL is part of the Social and Public Health Sciences Unit, funded by the Medical Research Council (MC_UU_12017/13) and the Scottish Government Chief Scientist Office (SPHSU13).

Pandemic ICU triage challenge and medical ethics

The COVID-19 pandemic has made unprecedented global demands on healthcare in general and especially the intensive care unit (ICU). the virus is spreading out of control. To this day, there is no clear, published directive for doctors regarding the allocation of ICU beds in times of scarcity. This means that many doctors do not feel supported by their government and are afraid of the medicolegal consequences of the choices they have to make. Consequently, there has been no transparent discussion among professionals and the public. The thought of being at the mercy of absolute arbitrariness leads to fear among the population, especially the vulnerable groups.

Frailty predicts 30-day mortality in intensive care patients: A prospective prediction study

BACKGROUND

Frailty is a multidimensional syndrome characterised by a loss of reserve and an increased risk of adverse outcomes.

OBJECTIVE

To study the impact of frailty on mortality in unselected intensive care patients, and to compare its discriminatory ability to an established model for outcome prediction in intensive care.

DESIGN

A prospective study with a comparison of two prediction models.

SETTING

A tertiary mixed ICU, from January 2017 to June 2018.

PATIENTS AND MAIN OUTCOME MEASURES

Data on premorbid frailty (clinical frailty scale; CFS), severity of illness (the simplified acute physiology score, third version; SAPS3), therapeutic procedures, limitations of care and outcome were collected in 872 adult ICU patients. A cut-off level of CFS for predicting death within 30 days was identified and unadjusted and adjusted analyses were used to evaluate the association of frailty to outcome.

RESULTS

The receiver operating curve, area under the curve of CFS [0.74 (95% confidence interval, 0.69 to 0.79)] did not differ significantly from that of SAPS3 [0.79 (0.75 to 0.83), P = 0.53], whereas combining the two resulted in an improved discriminatory ability [area under the curve = 0.82 (0.79 to 0.86), CFS + SAPS3 vs. SAPS3 alone, P = 0.02]. The correlation of CFS to SAPS3 was moderate (r = 0.4). A cut-off level was identified at CFS at least 5, defining 43% (n=375) of the patients as frail. Frail patients were older with higher SAPS3 and more comorbidities. Treatment in the ICU was more often withheld or withdrawn in frail patients, and mortality was higher. After adjustment for SAPS3, comorbidities, limitations of treatment, age and sex, frailty remained a strong predictor of death within 30 days [hazard ratio 2.12 (95% confidence interval, 1.44 to 3.14), P < 0.001].

CONCLUSION

Premorbid frailty was common in general ICU patients and was an independent predictor of death. Our study suggests that frailty could be a valuable addition in outcome prediction in intensive care.

Theorising survivorship after intensive care: A systematic review of patient and family experiences

AIMS AND OBJECTIVE

This systematic literature review explores and maps what we know about survivorship to understand how survivorship can be theoretically defined.

BACKGROUND

Survivorship of critical illness has been identified as a challenge for the 21st Century. Whilst the use of the term 'survivorship' is now common in critical care, it has been borrowed from the cancer literature where the discourse on what survivorship means in a cancer context is ongoing and remains largely descriptive. In the absence of a theoretical understanding, the term 'survivorship' is often used in critical illness in a generic way, limiting our understanding of what survivorship is. The current COVID-19 pandemic adds to an urgency of understanding what intensive care unit (ICU) survivorship might mean, given the emerging long-term consequences of this patient cohort. We set out to explore how survivorship after critical illness is being conceptualised and what the implications might be for clinical practice and research.

DESIGN

Integrated systematic literature review. The review protocol was registered with PROSPERO International Prospective Register of Systematic Reviews. PRISMA guidelines were followed and a PRISMA checklist for reporting systematic reviews completed.

RESULTS

The three main themes around which the reviewed studies were organised are: (a) healthcare system; (b) ICU survivors' families; and (c) ICU survivor's identity. These three themes feed into an overarching core theme of 'ICU Survivorship Experiences'. These themes map our current knowledge of what happens when a patient survives a critical illness and where we are in understanding ICU survivorship.

CONCLUSION

We mapped in this systematic review the different pieces of the jigsaw that emerge following critical illness to understand and see the bigger picture of what happens after patients survive critical illness. It is evident that existing research has mapped these connections, but what we have not managed to do yet is defining what survivorship is theoretically. We offer a preliminary definition of survivorship as a process but are aware that this definition needs to be developed further with patients and families.

Measuring frailty in younger populations: a rapid review of evidence

OBJECTIVES

Frailty is typically assessed in older populations. Identifying frailty in adults aged under 60 years may also have value, if it supports the delivery of timely care. We sought to identify how frailty is measured in younger populations, including evidence of the impact on patient outcomes and care.

DESIGN

A rapid review of primary studies was conducted.

DATA SOURCES

Four databases, three sources of grey literature and reference lists of systematic reviews were searched in March 2020.

ELIGIBILITY CRITERIA

Eligible studies measured frailty in populations aged under 60 years using experimental or observational designs, published after 2000 in English.

DATA EXTRACTION AND SYNTHESIS

Records were screened against review criteria. Study data were extracted with 20% of records checked for accuracy by a second researcher. Data were synthesised using a narrative approach.

RESULTS

We identified 268 studies that measured frailty in samples that included people aged under 60 years. Of these, 85 studies reported evidence about measure validity. No measures were identified that were designed and validated to identify frailty exclusively in younger groups. However, in populations that included people aged over and under 60 years, cumulative deficit frailty indices, phenotype measures, the FRAIL Scale, the Liver Frailty Index and the Short Physical Performance Battery all demonstrated predictive validity for mortality and/or hospital admission. Evidence of criterion validity was rare. The extent to which measures possess validity across the younger adult age (18-59 years) spectrum was unclear. There was no evidence about the impact of measuring frailty in younger populations on patient outcomes and care.

CONCLUSIONS

Limited evidence suggests that frailty measures have predictive validity in younger populations. Further research is needed to clarify the validity of measures across the adult age spectrum, and explore the utility of measuring frailty in younger groups.

Frailty status among older critically ill patients with severe acute kidney injury

BACKGROUND

Frailty status among critically ill patients with acute kidney injury (AKI) is not well described despite its importance for prognostication and informed decision-making on life-sustaining therapies. In this study, we aim to describe the epidemiology of frailty in a cohort of older critically ill patients with severe AKI, the outcomes of patients with pre-existing frailty before AKI and the factors associated with a worsening frailty status among survivors.

METHODS

This was a secondary analysis of a prospective multicentre observational study that enrolled older (age > 65 years) critically ill patients with AKI. The clinical frailty scale (CFS) score was captured at baseline, at 6 months and at 12 months among survivors. Frailty was defined as a CFS score of ≥ 5. Demographic, clinical and physiological variables associated with frailty as baseline were described. Multivariable Cox proportional hazard models were constructed to describe the association between frailty and 90-day mortality. Demographic and clinical factors associated with worsening frailty status at 6 months and 12 months were described using multivariable logistic regression analysis and multistate models.

RESULTS

Among the 462 patients in our cohort, median (IQR) baseline CFS score was 4 (3-5), with 141 (31%) patients considered frail. Pre-existing frailty was associated with greater hazard of 90-day mortality (59% (n = 83) for frail vs. 31% (n = 100) for non-frail; adjusted hazards ratio [HR] 1.49; 95% CI 1.11-2.01, p = 0.008). At 6 months, 68 patients (28% of survivors) were frail. Of these, 57% (n = 39) were not classified as frail at baseline. Between 6 and 12 months of follow-up, 9 (4% of survivors) patients transitioned from a frail to a not frail status while 10 (4% of survivors) patients became frail and 11 (5% of survivors) patients died. In multivariable analysis, age was independently associated with worsening CFS score from baseline to 6 months (adjusted odds ratio [OR] 1.08; 95% CI 1.03-1.13, p = 0.003).

CONCLUSIONS

Pre-existing frailty is an independent risk factor for mortality among older critically ill patients with severe AKI. A substantial proportion of survivors experience declining function and worsened frailty status within one year.

The FRAIL-FIT 30 Study – Factors influencing 30-day mortality in frail patients admitted to ICU: A retrospective observational cohort study

Background

Frailty is a multi-dimensional syndrome of reduced reserve, resulting from overlapping physiological decrements across multiple systems. The contributing factors, temporality and magnitude of frailty’s effect on mortality after ICU admission are unclear. This study assessed frailty’s impact on mortality and life sustaining therapy (LST) use, following ICU admission.

Methods

This single-centre retrospective observational cohort study analysed data collected prospectively in Glasgow Royal Infirmary ICU. Of 684 eligible patients, 171 were frail and 513 were non-frail. Frailty was quantified using the Rockwood Clinical Frailty Scale (CFS). All patients were followed up 1-year after ICU admission. The primary outcome was all-cause mortality at 30-days post-ICU admission. Key secondary outcomes included mortality at 1-year and LST use.

Results

Frail patients were significantly less likely to survive 30-days post-ICU admission (61.4% vs 81.1%, p < 0.001). This continued to 1-year (48.5% vs 68.2%, p < 0.001). Frailty significantly increased mortality hazards in covariate-adjusted analyses at 30-days (HR 1.56; 95%CI 1.14–2.15; p = 0.006), and 1-year (HR 1.35; 95%CI 1.03–1.76; p = 0.028). Single-point CFS increases were associated with a 30-day mortality hazard of 1.23 (95%CI 1.13–1.34; p < 0.001) in unadjusted analyses, and 1.11 (95%CI 1.01–1.22; p = 0.026) after covariate adjustment. Frail patients received significantly more days of LST (median[IQR]: 5[3,11] vs 4[2,9], p = 0.008).

Conclusion

Frailty was significantly associated with greater mortality at all time points studied, but most notably in the first 30-days post-ICU admission. This was despite greater LST use. The accrual effect of frailty increased adverse outcomes. Point-by-point use of frailty scoring could allow for more informed decision making in ICU.

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.

Characteristics and outcomes of frail patients with suspected infection in intensive care units: a descriptive analysis from a multicenter cohort study

Background

Frailty is associated with morbidity and mortality in patients admitted to intensive care units (ICUs). However, the characteristics of frail patients with suspected infection remain unclear. We aimed to investigate the characteristics and outcomes of frail patients with suspected infection in ICUs.

Methods

This is a secondary analysis of a multicenter cohort study, including 22 ICUs in Japan. Adult patients (aged ≥16 years) with newly suspected infection from December 2017 to May 2018 were included. We compared baseline patient characteristics and outcomes among three frailty groups based on the Clinical Frailty Scale (CFS) score: fit (score, 1–3), vulnerable (score, 4), and frail (score, 5–9). We conducted subgroup analysis of patients with sepsis defined as per Sepsis-3 criteria. We also produced Kaplan–Meier survival curves for 90-day survival.

Results

We enrolled 650 patients with suspected infection, including 599 (92.2%) patients with sepsis. Patients with a median CFS score of 3 (interquartile range [IQR] 3–5) were included: 337 (51.8%) were fit, 109 (16.8%) were vulnerable, and 204 (31.4%) were frail. The median patient age was 72 years (IQR 60–81). The Sequential Organ Failure Assessment scores for fit, vulnerable, and frail patients were 7 (IQR 4–10), 8 (IQR 5–11), and 7 (IQR 5–10), respectively (p = 0.59). The median body temperatures of fit, vulnerable, and frail patients were 37.5 °C (IQR 36.5 °C–38.5 °C), 37.5 °C (IQR 36.4 °C–38.6 °C), and 37.0 °C (IQR 36.3 °C–38.1 °C), respectively (p < 0.01). The median C-reactive protein levels of fit, vulnerable, and frail patients were 13.6 (IQR 4.6–24.5), 12.1 (IQR 3.9–24.9), 10.5 (IQR 3.0–21.0) mg/dL, respectively (p < 0.01). In-hospital mortality did not statistically differ among the patients according to frailty (p = 0.19). Kaplan–Meier survival curves showed little difference in the mortality rate during short-term follow-up. However, more vulnerable and frail patients died after 30-day than fit patients; this difference was not statistically significant (p = 0.25). Compared with the fit and vulnerable groups, the rate of home discharge was lower in the frail group.

Conclusion

Frail and vulnerable patients with suspected infection tend to have poor disease outcomes. However, they did not show a statistically significant increase in the 90-day mortality risk.