Feasibility and reliability of frailty assessment in the critically ill: a systematic review

Frailty assessment in critically ill older adults: a narrative review

Frailty, a condition that was first defined 20 years ago, is now assessed via multiple different tools. The Frailty Phenotype was initially used to identify a population of "pre-frail" and "frail" older adults, so as to prevent falls, loss of mobility, and hospitalizations. A different definition of frailty, via the Clinical Frailty Scale, is now actively used in critical care situations to evaluate over 65 year-old patients, whether it be for Intensive Care Unit (ICU) admissions, limitation of life-sustaining treatments or prognostication. Confusion remains when mentioning "frailty" in older adults, as to which tools are used, and what the impact or the bias of using these tools might be. In addition, it is essential to clarify which tools are appropriate in medical emergencies. In this review, we clarify various concepts and differences between frailty, functional autonomy and comorbidities; then focus on the current use of frailty scales in critically ill older adults. Finally, we discuss the benefits and risks of using standardized scales to describe patients, and suggest ways to maintain a complex, three-dimensional, patient evaluation, despite time constraints. Frailty in the ICU is common, involving around 40% of patients over 75. The most commonly used scale is the Clinical Frailty Scale (CFS), a rapid substitute for Comprehensive Geriatric Assessment (CGA). Significant associations exist between the CFS-scale and both short and long-term mortality, as well as long-term outcomes, such as loss of functional ability and being discharged home. The CFS became a mainstream tool newly used for triage during the Covid-19 pandemic, in response to the pressure on healthcare systems. It was found to be significantly associated with in-hospital mortality. The improper use of scales may lead to hastened decision-making, especially when there are strains on healthcare resources or time-constraints. Being aware of theses biases is essential to facilitate older adults' access to equitable decision-making regarding critical care. The aim is to help counteract assessments which may be abridged by time and organisational constraints.

Outcome, predictors and longitudinal trajectories of subjects with critical illness polyneuropathy and myopathy (CINAMOPS): study protocol of an observational cohort study in a clinical and post-clinical setting

INTRODUCTION

Critical illness polyneuropathy and myopathy (CIP/CIM) are frequent complications in the intensive care unit (ICU) with major consequences for the progress and outcome of subjects. CIP/CIM delays the weaning process, prolongs the hospital stay and increases the mortality rate. Additionally, it may have long-term consequences beyond the hospitalisation phase with prolonged disability. Even though there is growing interest in CIP/CIM, research about the clinical and post-clinical course as well as the middle-term and long-term outcomes of subjects with CIP/CIM is scarce. A large prospective study of critically ill subjects is needed with accurate diagnosis during the acute stage and comprehensive assessment during long-term follow-up.

METHODS AND ANALYSIS

This prospective observational cohort study aims to compare the clinical and post-clinical course of chronically critically ill subjects with and without the diagnosis of CIP/CIM and to determine predictors for the middle-term and long-term outcomes of subjects with CIP/CIM. In addition, the influence of the preclinical health status and the preclinical frailty on the long-term outcome of subjects with CIP/CIM will be investigated.This single-centre study will include 250 critically ill patients who were invasively ventilated for at least 5 days at the ICU and show reduced motor strength. At five study visits at admission and discharge to neurological rehabilitation, and 12, 18 and 24 months after disease onset, a comprehensive test battery will be applied including assessments of functioning and impairment, independence, health-related quality of life, activity and participation, cognition, gait and balance, fatigue, mental health and frailty.Secondary objectives are the documentation of therapy goals, therapy content and achieved milestones during the rehabilitation, to evaluate the clinimetric properties of the Mini-BESTest in critically ill patients, and to evaluate the time course and outcome of subjects with CIP/CIM after SARS-CoV-2 infection.

ETHICS AND DISSEMINATION

The study was approved by the ethical committee of the Ludwig-Maximilians University Munich. Participants will be included in the study after having signed informed consent.Results will be published in scientific, peer-reviewed journals and at national and international conferences.

TRIAL REGISTRATION NUMBER

German Clinical Trial Register (DRKS00021753).

Long-stay ICU patients with frailty: mortality and recovery outcomes at 6 months

BACKGROUND

Prolonged intensive care unit (ICU) stay is associated with physical, cognitive, and psychological disabilities. The impact of baseline frailty on long-stay ICU patients remains uncertain. This study aims to investigate how baseline frailty influences mortality and post-ICU disability 6 months after critical illness in long-stay ICU patients.

METHODS

In this retrospective cohort study, we assessed patients hospitalized for ≥ 7 days in the ICU between May 2018 and May 2021, following them for up to 6 months or until death. Based on the Clinical Frailty Scale (CFS) at ICU admissions, patients were categorized as frail (CFS ≥ 5), pre-frail (CFS 3-4) and non-frail (CFS 1-2). Kaplan-Meier curves and a multivariate Cox model were used to examine the association between frailty and mortality. At the 6 month follow-up, we assessed psychological, physical, cognitive outcomes, and health-related quality of life (QoL) using descriptive statistics and linear regressions.

RESULTS

We enrolled 531 patients, of which 178 (33.6%) were frail, 200 (37.6%) pre-frail and 153 (28.8%) non-frail. Frail patients were older, had more comorbidities, and greater disease severity at ICU admission. At 6 months, frail patients presented higher mortality rates than pre-frail and non-frail patients (34.3% (61/178) vs. 21% (42/200) vs. 13.1% (20/153) respectively, p < 0.01). The rate of withdrawing or withholding of care did not differ significantly between the groups. Compared with CFS 1-2, the adjusted hazard ratios of death at 6 months were 1.7 (95% CI 0.9-2.9) for CFS 3-4 and 2.9 (95% CI 1.7-4.9) for CFS ≥ 5. At 6 months, 192 patients were seen at a follow-up consultation. In multivariate linear regressions, CFS ≥ 5 was associated with poorer physical health-related QoL, but not with poorer mental health-related QoL, compared with CFS 1-2.

CONCLUSION

Frailty is associated with increased mortality and poorer physical health-related QoL in long-stay ICU patients at 6 months. The admission CFS can help inform patients and families about the complexities of survivorship during a prolonged ICU stay.

Use of Artificial Intelligence in the Identification and Management of Frailty: A Scoping Review Protocol

INTRODUCTION

Rapid population ageing and associated health issues such as frailty are a growing public health concern. While early identification and management of frailty may limit adverse health outcomes, the complex presentations of frailty pose challenges for clinicians. Artificial intelligence (AI) has emerged as a potential solution to support the early identification and management of frailty. In order to provide a comprehensive overview of current evidence regarding the development and use of AI technologies including machine learning and deep learning for the identification and management of frailty, this protocol outlines a scoping review aiming to identify and present available information in this area. Specifically, this protocol describes a review that will focus on the clinical tools and frameworks used to assess frailty, the outcomes that have been evaluated and the involvement of knowledge users in the development, implementation and evaluation of AI methods and tools for frailty care in clinical settings.

METHODS AND ANALYSIS

This scoping review protocol details a systematic search of eight major academic databases, including Medline, Embase, PsycInfo, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Ageline, Web of Science, Scopus and Institute of Electrical and Electronics Engineers (IEEE) Xplore using the framework developed by Arksey and O'Malley and enhanced by Levac et al and the Joanna Briggs Institute. The search strategy has been designed in consultation with a librarian. Two independent reviewers will screen titles and abstracts, followed by full texts, for eligibility and then chart the data using a piloted data charting form. Results will be collated and presented through a narrative summary, tables and figures.

ETHICS AND DISSEMINATION

Since this study is based on publicly available information, ethics approval is not required. Findings will be communicated with healthcare providers, caregivers, patients and research and health programme funders through peer-reviewed publications, presentations and an infographic.

REGISTRATION DETAILS

OSF Registries (https://doi.org/10.17605/OSF.IO/T54G8).

Functional independence, frailty and perceived quality of life in patients who developed delirium during ICU stay: a prospective cohort study

BACKGROUND

Survivors of critical illness are frequently left with a long-lasting disability. We hypothesised that patients who developed delirium during ICU stay, compared with patients who did not, would have worse health-related quality of life following a critical illness.

METHODS

Prospective longitudinal observational and analytical study assessing functional independence, frailty and perceived quality of life measured with the Barthel Index, the Clinical Frailty Scale, and the SF-36, comparing patients who developed delirium during ICU stay and patients who did not. The questionnaires were used at different times during the follow-up (upon ICU admission, at ICU discharge, at hospital discharge and 2 years after hospital discharge).

RESULTS

In a cohort of 1462 patients, we matched 93 patients who developed delirium (delirium group) with 93 patients who did not develop delirium (no-delirium group). Of 156 completed questionnaires (84.7%), we observed that (a) in each of the two groups of patients, the scores related to functional independence (Barthel Index) and frailty (Clinical Frailty Scale) tended to improve over time (p < 0.001), being consistently less favourable in the delirium group compared to the no-delirium group (p < 0.001); (b) the patients who developed delirium also presented lower scores on the SF-36 scale, these differences being statistically significant, and therefore evidencing a worse quality of life, with impact on both the psychological and social spheres (p < 0.001).

CONCLUSIONS

Patients who developed delirium had significantly lower scores 2 years after hospital discharge on the three used questionnaires, displaying a clear negative impact on the physical, psychological, and social dimensions. The study's results reinforce the need to support and strengthen the care of ICU survivors.

Reliability and validity of a frailty assessment tool in specialized burn care, a retrospective multicentre cohort study

BACKGROUND

Frailty is a predictor of adverse outcomes in elderly patients. The Canadian Study of Health and Aging Clinical Frailty Scale (CFS) is an often-used frailty assessment instrument. However, the CFS's reliability and validity in patients with burn injuries are unknown. This study aimed to assess the CFS's inter-rater reliability and validity (predictive validity, known group validity and convergent validity) in patients with burn injuries treated to specialized burn care.

METHODS

A retrospective multicentre cohort study was conducted in all three Dutch burn centres. Patients aged ≥ 50 years with burn injuries, with a primary admission in 2015-2018, were included. Based on information in the electronic patient files, a research team member scored the CFS retrospectively. Inter-rater reliability was calculated using Krippendorff's α. Validity was assessed using logistic regression analysis. Patients with a CFS ≥ 5 were considered frail.

RESULTS

In total, 540 patients were included, with a mean age of 65.8 years (SD 11.5) and a Total Body Surface Area (TBSA) burned of 8.5%. The CFS was used to assess frailty in 540 patients and the reliability of the CFS was scored for 212 patients. Mean CFS was 3.4(SD 2.0). Inter-rater reliability was adequate, Krippendorff's α 0.69 (95%CI 0.62-0.74). A positive frailty screening was predictive of a non-home discharge location (OR 3.57, 95%CI 2.16-5.93), a higher in-hospital mortality rate (OR 1.06-8.77), and a higher mortality rate within 12 months after discharge (OR 4.61, 95%CI 1.99-10.65) after adjustment for age, TBSA, and inhalation injury. Frail patients were more likely to be older (for<70 vs. ≥70 years odds ratio 2.88, 95%CI 1.95-4.25) and their comorbidities were more severe (ASA ≥3 vs 1-2 OR 6.43, 95%CI 4.26-9.70) (known group validity). The CFS was significantly related (rSpearman=0.55) to the Dutch Safety Management System (DSMS) frailty screening, reflecting a fair-good correlation between the CFS and DSMS frailty screening outcomes.

CONCLUSION

The Clinical Frailty scale is reliable and has shown its validity, including its association with adverse outcomes in patients with burn injury admitted to specialized burn care. Early frailty assessment with the CFS must be considered, to optimize early recognition and treatment of frailty.

Comparison of a multidomain frailty index from routine health data with the hospital frailty risk score in older patients in an Australian hospital

BACKGROUND

Frailty is an important determinant of health-care needs and outcomes for people in hospital.

OBJECTIVES

To compare characteristics and predictive ability of a multidomain frailty index derived from routine health data (electronic frailty index-acute hospital; eFI-AH) with the hospital frailty risk score (HFRS).

METHODS

This retrospective study included 6771 patients aged ≥75 years admitted to an Australian metropolitan tertiary referral hospital between October 2019 and September 2020. The eFI-AH and the HFRS were calculated for each patient and compared with respect to characteristics, agreement, association with age and ability to predict outcomes.

RESULTS

Median eFI-AH was 0.17 (range 0-0.66) whilst median HFRS was 3.2 (range 0-42.9). Moderate agreement was shown between the tools (Pearson's r 0.61). After adjusting for age and gender, both models had associations with long hospital stay, in-hospital mortality, unplanned all-cause readmission and fall-related readmission. Specifically, the eFI-AH had the strongest association with in-hospital mortality (adjusted odds ratio (aOR) 2.81, 95% confidence intervals (CI) 2.49-3.17), whilst the HFRS was most strongly associated with long hospital stay (aOR 1.20, 95% CI 1.18-1.21). Both tools predicted hospital stay >10 days with good discrimination and calibration.

CONCLUSIONS

Although the eFI-AH and the HFRS did not consistently identify the same inpatients as frail, both were associated with adverse outcomes and they had comparable predictive ability for prolonged hospitalisation. These two constructs of frailty may have different implications for clinical practice and health service provision and planning.

Frailty, Acute Brain Dysfunction, and Posthospitalization Disability Outcomes in Critically Ill Older Adults

BACKGROUND

Identifying potentially modifiable factors that mediate adverse outcomes in frail adults with critical illness may facilitate development of interventions to improve intensive care unit (ICU) survivorship.

OBJECTIVES

To estimate the relationship between frailty, acute brain dysfunction (as reflected by delirium or persistent coma), and 6-month disability outcomes.

METHODS

Older adults (aged ≥50 years) admitted to the ICU were enrolled prospectively. Frailty was identified with the Clinical Frailty Scale. Delirium and coma were assessed daily with the Confusion Assessment Method for the ICU and the Richmond Agitation-Sedation Scale, respectively. Disability outcomes (death and severe physical disability [defined as new dependence in 5 or more activities of daily living]) were assessed by telephone within 6 months after discharge.

RESULTS

In 302 older adults (mean [SD] age, 67.2 [10.8] y), both frail and vulnerable patients had a higher risk for acute brain dysfunction (adjusted odds ratio [AOR], 2.9 [95% CI, 1.5-5.6], and 2.0 [95% CI, 1.0-4.1], respectively) compared with fit patients. Both frailty and acute brain dysfunction were independently associated with death or severe disability at 6 months (AOR, 3.3 [95% CI, 1.6-6.5] and 2.4 [95% CI, 1.4 -4.0], respectively). The average proportion of the frailty effect mediated by acute brain dysfunction was estimated to be 12.6% (95% CI, 2.1%-23.1%; P = .02).

CONCLUSION

Frailty and acute brain dysfunction were important independent predictors of disability outcomes in older adults with critical illness. Acute brain dysfunction may be an important mediator of increased risk for physical disability outcomes after critical illness.

Who to escalate during a pandemic? A retrospective observational study about decision-making during the COVID-19 pandemic in the UK

BACKGROUND

Optimal decision-making regarding who to admit to critical care in pandemic situations remains unclear. We compared age, Clinical Frailty Score (CFS), 4C Mortality Score and hospital mortality in two separate COVID-19 surges based on the escalation decision made by the treating physician.

METHODS

A retrospective analysis of all referrals to critical care during the first COVID-19 surge (cohort 1, March/April 2020) and a late surge (cohort 2, October/November 2021) was undertaken. Patients with confirmed or high clinical suspicion of COVID-19 infection were included. A senior critical care physician assessed all patients regarding their suitability for potential intensive care unit admission. Demographics, CFS, 4C Mortality Score and hospital mortality were compared depending on the escalation decision made by the attending physician.

RESULTS

203 patients were included in the study, 139 in cohort 1 and 64 in cohort 2. There were no significant differences in age, CFS and 4C scores between the two cohorts. Patients deemed suitable for escalation by clinicians were significantly younger with significantly lower CFS and 4C scores compared with patients who were not deemed to benefit from escalation. This pattern was observed in both cohorts. Mortality in patients not deemed suitable for escalation was 61.8% in cohort 1 and 47.4% in cohort 2 (p<0.001).

CONCLUSIONS

Decisions who to escalate to critical care in settings with limited resources pose moral distress on clinicians. 4C score, age and CFS did not change significantly between the two surges but differed significantly between patients deemed suitable for escalation and those deemed unsuitable by clinicians. Risk prediction tools may be useful in a pandemic to supplement clinical decision-making, even though escalation thresholds require adjustments to reflect changes in risk profile and outcomes between different pandemic surges.

A comparison of three approaches to measuring frailty to determine adverse health outcomes in critically ill patients

BACKGROUND

studies comparing different frailty measures in intensive care unit settings are lacking. We aimed to compare the frailty index based on physiological and laboratory tests (FI-Lab), modified frailty index (MFI) and hospital frailty risk score (HFRS) to predict short-term outcomes for critically ill patients.

METHODS

we conducted a secondary analysis of data from the Medical Information Mart for Intensive Care IV database. Outcomes of interest included in-hospital mortality and discharge with need for nursing care.

RESULTS

the primary analysis was conducted with 21,421 eligible critically ill patients. After adjusting for confounding variables, frailty as diagnosed by all three frailty measures was found to be significantly associated with increased in-hospital mortality. In addition, frail patients were more likely to receive further nursing care after being discharged. All three frailty scores could improve the discrimination ability of the initial model generated by baseline characteristics for adverse outcomes. The FI-Lab had the best predictive ability for in-hospital mortality, whereas the HFRS had the best predictive performance for discharge with need for nursing care amongst the three frailty measures. A combination of the FI-Lab with either the HFRS or MFI improved the identification of critically ill patients at increased risk of in-hospital mortality.

CONCLUSIONS

frailty, as assessed by the HFRS, MFI and FI-Lab, was associated with short-term survival and discharge with need for nursing care amongst critically ill patients. The FI-Lab was a better predictor of in-hospital mortality than the HFRS and MFI. Future studies focusing on FI-Lab are warranted.

Differential utility of various frailty diagnostic tools in non-geriatric hospital departments of several countries: A longitudinal study

BACKGROUND

There is limited knowledge on the performance of different frailty scales in clinical settings. We sought to evaluate in non-geriatric hospital departments the feasibility, agreement and predictive ability for adverse events after 1 year follow-up of several frailty assessment tools.

METHODS

Longitudinal study with 667 older adults recruited from five hospitals in three different countries (Spain, Italy and United Kingdom). Participants were older than 75 years attending the emergency room, cardiology and surgery departments. Frailty scales used were Frailty Phenotype (FP), FRAIL scale, Tilburg and Groningen Frailty Indicators, and Clinical Frailty Scale (CFS). Analyses included the prevalence of frailty, degree of agreement between tools, feasibility and prognostic value for hospital readmission, worsening of disability and mortality, by tool and setting.

RESULTS

Emergency Room and cardiology were the settings with the highest frailty prevalence, varying by tool between 40.4% and 67.2%; elective surgery was the one with the lowest prevalence (between 13.2% and 38.2%). The tools showed a fair to moderate agreement. FP showed the lowest feasibility, especially in urgent surgery (35.6%). FRAIL, CFS and FP predicted mortality and readmissions in several settings, but disability worsening only in cardiology.

CONCLUSIONS

Frailty is a highly frequent condition in older people attending non-geriatric hospital departments. We recommend that based upon their current feasibility and predictive ability, the FRAIL scale, CFS and FP should be preferentially used in these settings. The low concordance among the tools and differences in prevalence reported and predictive ability suggest the existence of different subtypes of frailty.

Critical Appraisal of the Concept Frailty: Rating of Frailty in Elderly People has Weak Scientific Basis and should not be Used for Managing Individual Patients

The concept frail elderly has been used to highlight the biological, rather than chronological, age. International and national bodies recommend that individuals over age 70 who visit healthcare facilities should be screened for frailty. There are important objections to the concept. Diagnostics: 'Frailty' is used for several completely different types of health problems. There are no useful biomarkers, but more than 60 different published rating methods for frailty, where different methods provide very different prevalence of frailty and also do not identify the same groups of elderly people. There is significant overlap between Clinical Frailty Scale- scores and activity of daily living (ADL)-scores. There is no gold standard method against which published frailty rating scales can be validated. It is unclear when, where and how often screening for frailty should occur in healthcare. Treatment: The evidence for treatment of frailty is very weak. A recent systematic overview found that the 21 included randomised, controlled studies (RCTs) were very heterogeneous as regards inclusion/exclusion criteria, how the condition of frailty was defined, what treatment was given and what health outcomes were assessed. In addition, there are often problems with the quality of the studies. The lack of a clear definition and evidence-based treatment of frailty means that it is inappropriate to introduce assessments of frailty in individual elderly patients in health care.

Elderly Outcomes After Hospitalization: The Hospital Frailty Risk Score Applied on the French Health Data Hub

Objectives: To demonstrate the association between the Hospital Frailty Risk Score (HFRS) and 30-day mortality, 30-day hospital readmission and length of stay (LOS) in France. Methods: Logistic regressions were performed using data recorded in the French national health data system ( SNDS) for elderly patients (≥75 years old) hospitalized in France in 2017. Results: Over the 1,111,090 patients included, 30-day mortality was associated with the HFRS: adjusted OR (aOR) for an intermediate HFRS (5–15 points) was 1.91 [95% confidence interval (95% IC); 1.87–1.95] and aOR 2.57 [95% IC; 2.50–2.64] for high HFRS (>15 points), as compared to low HFRS (<5 points). LOS >10 days increased with the HFRS (aOR = 1.36 [95% IC; 1.34–1.38] for an intermediate HFRS and aOR 1.51 [95% IC; 1.48–1.54] for a high HFRS). A high HFRS was associated with 30-day hospital readmission (aOR = 1.06 [95% IC; 1.04–1.08]). Discussion: This real-life analysis of in- and out-patient healthcare pathways confirmed the HFRS’s ability to predict adverse outcomes, after adjustment on social deprivation.

Frailty-Diagnostik in verschiedenen AINS-Settings

Das Vorliegen eines sog. Frailty-Syndroms („Gebrechlichkeit“) ist für den postoperativen Verlauf ein entscheidender Faktor. So kommt es, auch durch eine zunehmende Fokussierung auf die patientenzentrierte Versorgung, zu einer erhöhten Nachfrage nach Instrumenten, die den Patient*innenstatus umfassender beurteilen und Krankheitsverläufe vorhersagen können. Der Beitrag stellt die 3 führenden Modelle zur Frailty-Diagnostik vor.

Comparing the Clinical Frailty Scale and an International Classification of Diseases-10 Modified Frailty Index in Predicting Long-Term Survival in Critically Ill Patients

The Clinical Frailty Scale (CFS) is the most used frailty measure in intensive care unit (ICU) patients. Recently, the modified frailty index (mFI), derived from 11 comorbidities has also been used. It is unclear to what degree the mFI is a true measure of frailty rather than comorbidity. Furthermore, the mFI cannot be freely obtained outside of specific proprietary databases.

OBJECTIVE

To compare the performance of CFS and a recently developed International Classification of Diseases-10 (ICD-10) mFI (ICD-10mFI) as frailty-based predictors of long-term survival for up to 1 year.

DESIGN

A retrospective multicentric observational study.

SETTING AND PARTICIPANTS

All adult (≥16 yr) critically ill patients with documented CFS scores admitted to sixteen Australian ICUs in the state of Victoria between April 1, 2017 to June 30, 2018 were included. We used probabilistic methods to match de-identified ICU admission episodes listed in the Australia and New Zealand Intensive Care Society Adult Patient Database with the Victorian Admission Episode Dataset and the Victorian Death Index via the Victorian Data Linkage Centre.

MAIN OUTCOMES AND MEASURES

The primary outcome was the longest available survival following ICU admission. We compared CFS and ICD-10mFI as primary outcome predictors, after adjusting for key confounders.

RESULTS

The CFS and ICD-10mFI were compared in 7,001 ICU patients. The proportion of patients categorized as frail was greater with the CFS than with the ICD-10mFI (18.9% [n = 1,323] vs. 8.8% [n = 616]; p < 0.001). The median (IQR) follow-up time was 165 (82-276) days. The CFS predicted long-term survival up to 6 months after adjusting for confounders (hazard ratio [HR] = 1.26, 95% CI, 1.21-1.31), whereas ICD-10mFI did not (HR = 1.04, 95% CI, 0.98-1.10). The ICD-10mFI weakly correlated with the CFS (Spearman's rho = 0.22) but had a poor agreement (kappa = 0.06). The ICD-10mFI more strongly correlated with the Charlson comorbidity index (Spearman's rho 0.30) than CFS (Spearman's rho = 0.25) (p < 0.001).

CONCLUSIONS

CFS, but not ICD-10mFI, predicted long-term survival in ICU patients. ICD-10mFI correlated with co-morbidities more than CFS. These findings suggest that CFS and ICD-10mFI are not equivalent.

RELEVANCE

CFS and ICD-10mFI are not equivalent in screening for frailty in critically ill patients and therefore ICD-10mFI in its current form should not be used.

Long-term recovery after critical illness in older adults

PURPOSE OF REVIEW

The population is aging, and recent epidemiologic work reveals that an increasing number of older adults are presenting to the ICU with preexisting geriatric syndromes. In this update, we discuss recent literature pertaining to the long-term recovery of older ICU patients and highlight gaps in current knowledge.

RECENT FINDINGS

A recent longitudinal study demonstrated that the incidence of frailty, disability, and multimorbidity among older ICU patients is rising; these geriatric syndromes have all previously been shown to impact long-term recovery. Recent studies have demonstrated the impact of social factors in long-term outcomes after critical illness; for example, social isolation was recently shown to be associated with disability and mortality among older adults in the year after critical illness. Socioeconomic disadvantage is associated with higher rates of dementia and disability following critical illness impacting recovery, and further studies are necessary to better understand factors influencing this disparity. The COVID-19 pandemic disproportionately impacted older adults, resulting in worse outcomes and increased rates of functional decline and social isolation. In considering how to best facilitate recovery for older ICU survivors, transitional care programs may address the unique needs of older adults and help them adapt to new disability if recovery has not been achieved.

SUMMARY

Recent work demonstrates increasing trends of geriatric syndromes in the ICU, all of which are known to confer increased vulnerability among critically ill older adults and decrease the likelihood of post-ICU recovery. Risk factors are now known to extend beyond geriatric syndromes and include social risk factors and structural inequity. Strategies to improve post-ICU recovery must be viewed with a lens across the continuum of care, with post-ICU recovery programs targeted to the unique needs of older adults.

External validation of the hospital frailty risk score among older adults receiving mechanical ventilation

To externally validate the Hospital Frailty Risk Score (HFRS) in critically ill patients. We selected older adult (≥ 75 years old) hospitalizations receiving mechanical ventilation, using the Nationwide Readmissions Database (January 1, 2016-November 30, 2018). Frailty risk was subcategorized into low-risk (HFRS score < 5), intermediate-risk (score 5-15), and high-risk (score > 15). We evaluated the HFRS to predict in-hospital mortality, prolonged hospitalization, and 30-day readmissions, using multivariable logistic regression, adjusting for patient and hospital characteristics. Model performance was assessed using the c-statistic, Brier score, and calibration plots. Among 649,330 weighted hospitalizations, 9.5%, 68.3%, and 22.2% were subcategorized as low-, intermediate-, and high-risk for frailty, respectively. After adjustment, high-risk patient hospitalizations were associated with increased risks of prolonged hospitalization (adjusted odds ratio [aOR] 5.59 [95% confidence interval [CI] 5.24-5.97], c-statistic 0.694, Brier 0.216) and 30-day readmissions (aOR 1.20 [95% CI 1.13-1.27], c-statistic 0.595, Brier 0.162), compared to low-risk hospitalizations. Conversely, high-risk hospitalizations were inversely associated with in-hospital mortality (aOR 0.46 [95% CI 0.45-0.48], c-statistic 0.712, Brier 0.214). The HFRS was not successfully validated to predict in-hospital mortality in critically ill older adults. While it may predict other outcomes, its use should be avoided in the critically ill.

Performance of the APOP-screener for predicting in-hospital mortality in older COVID-19 patients: a retrospective study

BACKGROUND

A variety of prediction models concerning COVID-19 have been proposed since onset of the pandemic, but to this date no gold standard exists. Mortality rates show a sharp increase with advancing age but with the large heterogeneity of this population in terms of comorbidities, vulnerability and disabilities, identifying risk factors is difficult. Therefore, we aimed to research the multidimensional concept of frailty, measured by the Acute Presenting Older Patient (APOP)-screener, as a risk factor for in-hospital mortality in older COVID-19 patients.

METHODS

All consecutive patients of 70 years or older, with a PCR confirmed COVID-19 infection and a completed APOP-score, presenting at the Emergency Department (ED) of the Jeroen Bosch Hospital, the Netherlands, between February 27th 2020 and February 1st 2021 were retrospectively included. We gathered baseline characteristics and scored the CCI and CFS from patient records. The primary outcome was in-hospital mortality.

RESULTS

A total of 292 patients met the inclusion criteria. Approximately half of the patients were considered frail by the APOP or CFS. 127 patients (43.5%) scored frail on the CFS, 158 (54.1%) scored high risk on the APOP-screener. 79 patients (27.1%) died during their hospital admission. The APOP-screener showed a significantly elevated risk of in-hospital mortality when patients scored both high risk of functional and evidence of cognitive impairment (OR 2.24, 95% 1.18-4.25). Significant elevation of in-hospital mortality was found for the high CCI-scores (≥ 5)(OR 1.78, 95% 1.02-3.11), but not for the highest CFS category (5-9, frail) (OR 1.35, 95% 0.75-2.47). The discriminatory performance of the APOP, CFS and CCI were comparable (AUC resp. 0.59 (0.52-0.66), 0.54 (0.46-0.62) and 0.58 (0.51-0.65)).

CONCLUSION

Although the elevated risk for in-hospital mortality found for the most frail patients as scored by the APOP, this instrument has poor discriminatory value. Additionally, the CFS did not show significance in predicting in-hospital mortality and had a poor discriminatory value as well. Therefore, treatment decisions based on frailty or comorbidities alone should be made with caution. Approaching the heterogeneity of the older population by adding frailty as assessed by the APOP-score to existing prediction models may enhance the predictive value of these models.

Preoperative frailty based on laboratory data and postoperative health outcomes in patients undergoing coronary artery bypass graft surgery

BACKGROUND

Frailty is associated with adverse surgical outcomes. Patients with cardiovascular diseases have many risk factors of frailty; thus, preoperative frailty evaluation is necessary to predict adverse outcomes after coronary artery bypass graft (CABG) surgery. Laboratory data based-frailty assessments are objective and not time-consuming, addressing the need for an accurate but simple frailty screening for patients awaiting CABG surgery.

OBJECTIVES

This retrospective study aimed to determine the association between laboratory based-frailty and patient health outcomes after CABG surgery.

METHODS

We evaluated 896 patients who underwent on-pump or off-pump CABG surgery between August 1, 2015 and July 31, 2020 at a tertiary hospital. The frailty index-laboratory (FI-LAB), which comprises 32 laboratory parameters and vital signs, was used for frailty assessment.

RESULTS

The patients were divided into three groups according to their preoperative FI-LAB level as low (FI-LAB <0.25, 23.0%), moderate (FI-LAB ≥0.25 to ≤0.4, 54.9%), and high (FI-LAB>0.4, 22.1%) frailty groups. In the confounder-adjusted analysis, the lengths of hospital stay and intensive care unit stay were longer by 2.20 days (p=.023) and by 0.89 days (p=.009), respectively, in the high frailty group than those in the low frailty group. The odds ratio for 30-day readmission was also 2.58 times higher in the high frailty group than that in the low frailty group.

CONCLUSION

A high preoperative FI-LAB score indicates increasing risks of adverse postoperative outcomes among CABG surgery patients. FI-LAB has potential strengths to capture the need for a more thorough frailty assessment for cardiac surgery patients.

Defining ICD-10 surrogate variables to estimate the modified frailty index: a Delphi-based approach

BACKGROUND

There are currently no validated globally and freely available tools to estimate the modified frailty index (mFI). The widely available and non-proprietary International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) coding could be used as a surrogate for the mFI. We aimed to establish an appropriate set of the ICD-10 codes for comorbidities to be used to estimate the eleven-variable mFI.

METHODS

A three-stage, web-based, Delphi consensus-building process among a panel of intensivists and geriatricians using iterative rounds of an online survey, was conducted between March and July 2021. The consensus was set a priori at 75% overall agreement. Additionally, we assessed if survey responses differed between intensivists and geriatricians. Finally, we ascertained the level of agreement.

RESULTS

A total of 21 clinicians participated in all 3 Delphi surveys. Most (86%, 18/21) had more than 5-years' experience as specialists. The agreement proportionately increased with every Delphi survey. After the third survey, the panel had reached 75% consensus in 87.5% (112/128) of ICD-10 codes. The initially included 128 ICD-10 variables were narrowed down to 54 at the end of the 3 surveys. The inter-rater agreements between intensivists and geriatricians were moderate for surveys 1 and 3 (κ = 0.728, κ = 0.780) respectively, and strong for survey 2 (κ = 0.811).

CONCLUSIONS

This quantitative Delphi survey of a panel of experienced intensivists and geriatricians achieved consensus for appropriate ICD-10 codes to estimate the mFI. Future studies should focus on validating the mFI estimated from these ICD-10 codes.

TRIAL REGISTRATION

Not applicable.

Comparison of the predictive ability of clinical frailty scale and hospital frailty risk score to determine long-term survival in critically ill patients: a multicentre retrospective cohort study

BACKGROUND

The Clinical Frailty Scale (CFS) is the most commonly used frailty measure in intensive care unit (ICU) patients. The hospital frailty risk score (HFRS) was recently proposed for the quantification of frailty. We aimed to compare the HFRS with the CFS in critically ill patients in predicting long-term survival up to one year following ICU admission.

METHODS

In this retrospective multicentre cohort study from 16 public ICUs in the state of Victoria, Australia between 1st January 2017 and 30th June 2018, ICU admission episodes listed in the Australian and New Zealand Intensive Care Society Adult Patient Database registry with a documented CFS, which had been linked with the Victorian Admitted Episode Dataset and the Victorian Death Index were examined. The HFRS was calculated for each patient using the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) codes that represented pre-existing conditions at the time of index hospital admission. Descriptive methods, Cox proportional hazards and area under the receiver operating characteristic (AUROC) were used to investigate the association between each frailty score and long-term survival up to 1 year, after adjusting for confounders including sex and baseline severity of illness on admission to ICU (Australia New Zealand risk-of-death, ANZROD).

RESULTS

7001 ICU patients with both frailty measures were analysed. The overall median (IQR) age was 63.7 (49.1-74.0) years; 59.5% (n = 4166) were male; the median (IQR) APACHE II score 14 (10-20). Almost half (46.7%, n = 3266) were mechanically ventilated. The hospital mortality was 9.5% (n = 642) and 1-year mortality was 14.4% (n = 1005). HFRS correlated weakly with CFS (Spearman's rho 0.13 (95% CI 0.10-0.15) and had a poor agreement (kappa = 0.12, 95% CI 0.10-0.15). Both frailty measures predicted 1-year survival after adjusting for confounders, CFS (HR 1.26, 95% CI 1.21-1.31) and HFRS (HR 1.08, 95% CI 1.02-1.15). The CFS had better discrimination of 1-year mortality than HFRS (AUROC 0.66 vs 0.63 p < 0.0001).

CONCLUSION

Both HFRS and CFS independently predicted up to 1-year survival following an ICU admission with moderate discrimination. The CFS was a better predictor of 1-year survival than the HFRS.

The feasibility and reliability of frailty assessment tools applicable in acute in-hospital trauma patients: A systematic review

BACKGROUND

Assessing frailty in patients with an acute trauma can be challenging. To provide trustworthy results, tools should be feasible and reliable. This systematic review evaluated existing evidence on the feasibility and reliability of frailty assessment tools applied in acute in-hospital trauma patients.

METHODS

A systematic search was conducted in relevant databases until February 2020. Studies evaluating the feasibility and/or reliability of a multidimensional frailty assessment tool used to identify frail trauma patients were identified. The feasibility and reliability results and the risk of bias of included studies were assessed. This study was conducted and reported in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement and registered in Prospective Register of Systematic Reviews (ID: CRD42020175003).

RESULTS

Nineteen studies evaluating 12 frailty assessment tools were included. The risk of bias of the included studies was fair to good. The most frequently evaluated tool was the Clinical Frailty Scale (CFS) (n = 5). All studies evaluated feasibility in terms of the percentage of patients for whom frailty could be assessed; feasibility was high (median, 97%; range, 49-100%). Other feasibility aspects, including time needed for completion, tool availability and costs, availability of instructions, and necessity of training for users, were hardly reported. Reliability was only assessed in three studies, all evaluating the CFS. The interrater reliability varied between 42% and >90% agreement, with a Krippendorff α of 0.27 to 0.41.

CONCLUSION

Feasibility of most instruments was generally high. Other aspects were hardly reported. Reliability was only evaluated for the CFS with results varying from poor to good. The reliability of frailty assessment tools for acute trauma patients needs further critical evaluation to conclude whether assessment leads to trustworthy results that are useful in clinical practice.

LEVEL OF EVIDENCE

Systematic review, Level II.

Comparison of feasibility and results of frailty assessment methods prior to left ventricular assist device implantation

AIMS

Assessing frailty and sarcopenia is considered a valuable cornerstone of perioperative risk stratification in advanced heart failure patients. The lack of an international consensus on a diagnostic standard impedes its implementation in the clinical routine. This study aimed to compare the feasibility and prognostic impact of different assessment tools in patients undergoing continuous-flow left ventricular assist device (cf-LVAD) implantation.

METHODS AND RESULTS

We prospectively compared feasibility and prognostic values of six frailty/sarcopenia assessment methods in 94 patients prior to cf-LVAD implantation: bioelectrical impedance analysis (BIA), computed tomography (CT)-based measurement of two muscle areas/body surface area [erector spinae muscle (TMESA/BSA) and iliopsoas muscle (TPA/BSA)], physical performance tests [grip strength, 6 min walk test (6MWT)] and Rockwood Clinical Frailty Scale (RCFS). Six-month mortality and/or prolonged ventilation time >95 h was defined as the primary endpoint. BIA and CT showed full feasibility (100%); physical performance and RCFS was limited due to patients' clinical status (feasibility: 87% grip strength, 62% 6MWT, 88% RCFS). Phase angle derived by BIA showed the best results regarding the prognostic value for 6 month mortality and/or prolonged ventilation time >95 h (odds ratio (OR) 0.66 [95% confidence interval (CI): 0.46-0.92], P = 0.019; area under the curve (AUC) 0.65). It provided incremental value to the clinical risk assessment of EuroSCORE II: C-index of the combined model was 0.75 [95% CI; 0.651-0.848] compared with C-index of EuroSCORE II alone, which was 0.73 (95% CI: 0.633-0.835). Six-month survival was decreased in patients with reduced body cell mass derived by BIA or reduced muscle area in the CT scan compared with patients with normal values: body cell mass 65% (95% CI: 51.8-81.6%) vs. 83% (95% CI: 74.0-93.9%); P = 0.03, TMESA/BSA 65% (95% CI: 51.2-82.2%) vs. 82% (95% CI: 73.2-93.0%); P = 0.032 and TPA/BSA 66% (95% CI: 53.7-81.0%) vs. 85% (95% CI: 75.0-95.8%); P = 0.035.

CONCLUSIONS

Bioelectrical impedance analysis parameters and CT measurements were shown to be suitable to predict 6-month mortality and/or prolonged ventilation time >95 h in patients with advanced heart failure prior to cf-LVAD implantation. Phase angle had the best predictive capacity and sarcopenia diagnosed by reduced body cell mass in BIA or muscle area in CT was associated with a decreased 6 month survival.

Frailty-aware care: giving value to frailty assessment across different healthcare settings

Healthcare systems need to adapt to better serve an aging population with complex presentations. Frailty assessments are a potential means to address this heterogeneity in aging to identify individuals at increased risk for adverse health outcomes. Furthermore, frailty assessments offer an opportunity to optimize patient care in various healthcare settings. While the vast number of frailty assessment tools available can be a source of confusion for clinicians, each tool has features adaptable to the constraints and goals of different healthcare settings. This review discusses and compares barriers, facilitators, and the application of frailty assessments in primary care, the emergency department/intensive care unit and surgical care to cover a breadth of settings with different frailty assessment considerations. The implementation of frailty-aware care across healthcare settings potentiates better healthcare outcomes for older adults.

Frailty assessment and acute frailty service provision in the UK: results of a national 'day of care' survey

Background

The incorporation of acute frailty services into the acute care pathway is increasingly common. The prevalence and impact of acute frailty services in the UK are currently unclear.

Methods

The Society for Acute Medicine Benchmarking Audit (SAMBA) is a day of care survey undertaken annually within the UK. SAMBA 2019 (SAMBA19) took place on Thursday 27th June 2019. A questionnaire was used to collect hospital and patient-level data on the structure and organisation of acute care delivery. SAMBA19 sought to establish the frequency of frailty assessment tool use and describe acute frailty services nationally. Hospitals were classified based on the presence of acute frailty services and metrics of performance compared.

Results

A total of 3218 patients aged ≥70 admitted to 129 hospitals were recorded in SAMBA19. The use of frailty assessment tools was reported in 80 (62.0%) hospitals. The proportion of patients assessed for the presence of frailty in individual hospitals ranged from 2.2 to 100%. Bedded Acute Frailty Units were reported in 65 (50.3%) hospitals. There was significant variation in admission rates between hospitals. This was not explained by the presence of a frailty screening policy or presence of a dedicated frailty unit.

Conclusion

Two fifths of participating UK hospitals did not have a routine frailty screening policy: where this existed, rates of assessment for frailty were variable and most at-risk patients were not assessed. Responses to positive results were poorly defined. The provision of acute frailty services is variable throughout the UK. Improvement is needed for the aspirations of national policy to be fully realised.

Frailty assessment using routine clinical data: An integrative review

BACKGROUND

Frailty is a common but complex problem in older adults. Frailty assessment using routine clinical data has been suggested as a pragmatic approach based on electronic health records from primary care center or hospital settings.

PURPOSE

We aimed to explore the tools and outcome variables used in the published studies on frailty assessment using routine clinical data.

METHODS

An integrative literature review was conducted using the method of Whittemore and Knafl. A literature search was conducted in PubMed, EMBASE, and CINAHL from January 2010 to October 2021.

RESULTS

A total of 45 studies and thirteen frailty assessment tools were analyzed. The assessment items were generally biased toward frailty's risk factors rather than the mechanisms or phenotypes of frailty. Similar to using conventional tools, routine clinical data-based frailty was associated with adverse health outcomes.

CONCLUSIONS

Frailty assessment based on routine clinical data could efficiently evaluate frailty using electronic health records from primary care centers or hospitals. However, they need refinement to consider the risk factors, mechanisms, and frailty phenotypes.

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.

The prevalence of frailty among breast cancer patients: a systematic review and meta-analysis

PURPOSE

Coexistence of frailty and breast cancer (BC) is related to a higher risk of hospitalization, mortality, and falls. Given the potential reversibility of frailty, investigating its epidemiology in BC is of great importance. However, estimates of the prevalence of frailty in BC patients vary considerably. We synthesized the existing body of literature on the prevalence of frailty among BC patients.

METHODS

We searched English databases (Cochrane Library, PubMed, Medline, CINAHL, Embase, Scopus, and Web of Science) and Chinese databases (CNKI, WanFang, CBM, and VIP database) from the inception to April 15, 2021, and collected observational studies about the prevalence of frailty among BC patients. The robustness of the pooled estimates was validated by analysis of different subgroups, meta-regression, and sensitivity. All data were analyzed using Stata 15.1.

RESULTS

In total, 4645 articles were screened and data from 24 studies involving 13,510 subjects were used in the meta-analysis. The prevalence of frailty among BC patients in individual studies varied from 5 to 71%. The pooled prevalence of frailty was 43% (95% confidence intervals (CI): 36% to 50%, I² = 98.4%, P < 0.05). Subgroup analyses revealed that the therapeutic method, frailty scales, age, frailty stage, regions, publication years, and study quality were associated with the prevalence of frailty among BC patients.

CONCLUSIONS

The prevalence of frailty among BC patients was relatively high, and the conditions of BC treatment can increase the risk of frailty. Understanding the effects of frailty on BC, especially in elderly patients, can provide the healthcare personnel with the theoretical basis for patients' management and treatment.

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.

Risk factors associated with the development of delirium in general ICU patients. A prospective observational study

Objective

We aimed to analyze risk factors related to the development of delirium, aiming for early intervention in patients with greater risk.

Material and methods

Observational study, including prospectively collected patients treated in a single general ICU. These were classified into two groups, according to whether they developed delirium or not (screening performed using CAM-ICU tool). Demographics and clinical data were analyzed. Multivariate logistic regression analyses were performed to quantify existing associations.

Results

1462 patients were included. 93 developed delirium (incidence: 6.3%). These were older, scored higher on the Clinical Frailty Scale, on the risk scores on admission (SAPS-3 and SOFA), and had a greater number of organ failures (OF). We observed more incidence of delirium in patients who (a) presented more than two OF (20.4%; OR 4.9; CI95%: 2.9–8.2), and (b) were more than 74 years old albeit having <2 OF (8.6%; OR 2.1; CI95%: 1.3–3.5). Patients who developed delirium had longer ICU and hospital length-of-stays and a higher rate of readmission.

Conclusions

The highest risk observed for developing delirium clustered in patients who presented more than 2 OF and patients over 74 years old. The detection of patients at high risk for developing delirium could imply a change in management and improved quality of care.

Frailty assessed by administrative tools and mortality in patients with pneumonia admitted to the hospital and ICU in Wales

The ideal method of identifying frailty is uncertain, and data on long-term outcomes is relatively limited. We examined frailty indices derived from population-scale linked data on Intensive Care Unit (ICU) and hospitalised non-ICU patients with pneumonia to elucidate the influence of frailty on mortality. Longitudinal cohort study between 2010-2018 using population-scale anonymised data linkage of healthcare records for adults admitted to hospital with pneumonia in Wales. Primary outcome was in-patient mortality. Odds Ratios (ORs [95% confidence interval]) for age, hospital frailty risk score (HFRS), electronic frailty index (eFI), Charlson comorbidity index (CCI), and social deprivation index were estimated using multivariate logistic regression models. The area under the receiver operating characteristic curve (AUC) was estimated to determine the best fitting models. Of the 107,188 patients, mean (SD) age was 72.6 (16.6) years, 50% were men. The models adjusted for the two frailty indices and the comorbidity index had an increased odds of in-patient mortality for individuals with an ICU admission (ORs for ICU admission in the eFI model 2.67 [2.55, 2.79], HFRS model 2.30 [2.20, 2.41], CCI model 2.62 [2.51, 2.75]). Models indicated advancing age, increased frailty and comorbidity were also associated with an increased odds of in-patient mortality (eFI, baseline fit, ORs: mild 1.09 [1.04, 1.13], moderate 1.13 [1.08, 1.18], severe 1.17 [1.10, 1.23]. HFRS, baseline low, ORs: intermediate 2.65 [2.55, 2.75], high 3.31 [3.17, 3.45]). CCI, baseline < 1, ORs: '1-10' 1.15 [1.11, 1.20], > 10 2.50 [2.41, 2.60]). For predicting inpatient deaths, the CCI and HFRS based models were similar, however for longer term outcomes the CCI based model was superior. Frailty and comorbidity are significant risk factors for patients admitted to hospital with pneumonia. Frailty and comorbidity scores based on administrative data have only moderate ability to predict outcome.

Different aspects of frailty and COVID-19: points to consider in the current pandemic and future ones

BACKGROUND

Older adults at a higher risk of adverse outcomes and mortality if they get infected with Severe acute respiratory syndrome coronavirus 2 (SARS- CoV-2). These undesired outcomes are because ageing is associated with other conditions like multimorbidity, frailty and disability. This paper describes the impact of frailty on coronavirus disease 2019 (COVID-19) management and outcomes. We also try to point out the role of inflamm-ageing, immunosenescence and reduced microbiota diversity in developing a severe form of COVID-19 and a different response to COVID-19 vaccination among older frail adults. Additionally, we attempt to highlight the impact of frailty on intensive care unit (ICU) outcomes, and hence, the rationale behind using frailty as an exclusion criterion for critical care admission. Similarly, the importance of using a time-saving, validated, sensitive, and user-friendly tool for frailty screening in an acute setting as COVID-19 triage. We performed a narrative review. Publications from 1990 to March 2021 were identified by searching the electronic databases MEDLINE, CINAHL and SCOPUS. Based on this search, we have found that in older frail adults, many mechanisms contribute to the severity of COVID-19, particularly cytokine storm; those mechanisms include lower immunological capacity and status of ongoing chronic inflammation and reduced gut microbiota diversity. Higher degrees of frailty were associated with poor outcomes and higher mortality rates during and after ICU admission. Also, the response to COVID-19 vaccination among frail older adults might differ from the general population regarding effectiveness and side effects. Researches also had shown that there are many tools for identifying frailty in an acute setting that could be used in COVID-19 triage, and before ICU admission, the clinical frailty scale (CFS) was the most recommended tool.

CONCLUSION

Older frail adults have a pre-existing immunopathological base that puts them at a higher risk of undesired outcomes and mortality due to COVID-19 and poor response to COVID-19 vaccination. Also, their admission in ICU should depend on their degree of frailty rather than their chronological age, which is better to be screened using the CFS.

The PALliative MUlticenter Study in Intensive Care (PalMuSIC). Results From a Multicenter Study Addressing Frailty and Palliative Care Interventions in Intensive Care Units in Portugal

INTRODUCTION

Frailty is a clinically recognizable state of increased vulnerability common in critical medicine. When underrecognized, it may lead to invasive treatments that do not serve the patients' best interest. Our aim was to evaluate the use of both palliative care consultation and invasive interventions in frail patients admitted to Intensive Care Units in Portugal.

METHODS

This was a prospective, observational study. All consecutive adult patients admitted for more than 24 h, over a 15-day period were enrolled. Twenty-three Portuguese Intensive Care Units were included. Informed consent was obtained from all patients or their surrogate. The doctor and nurse in charge calculated the Clinical Frailty Score as well as the reference family member.

RESULTS

A total of 335 patients were included in the study (66% male). Mean age was 63.2 ± 16.8 and SAPS II score was 41.8 ± 17.4. Mean Clinical Frailty Score value was 3.5 ± 1.7. Frailty prevalence (mean score ≥ 5) was 20.9%. Frail patients were offered organ support therapy (64,3% invasive mechanical ventilation; 24,3% renal replacement therapy; 67,1% vasopressors) more often than non-frail patients. Nevertheless, limitation of therapeutic effort or a do not resuscitate order (p < 0.001) were more common in frail patients. Mortality rate by 6 months was higher among frail patients (50% vs. 32.3%, p < 0.001). Palliative Care was offered to only 15% of frail patients (3.9% overall).

CONCLUSIONS

The authors suggest that palliative care should be universally consulted once frailty is identified in critical patients.

Association of baseline diaphragm, rectus femoris and vastus intermedius muscle thickness with weaning from mechanical ventilation

BACKGROUND

To determine whether baseline diaphragm (T_di), rectus femoris (RF) and vastus intermedius (VI) muscle thickness (T_RF and T_RF + VI) are associated with weaning success.

MATERIAL AND METHODS

Right T_di, T_RF and T_RF + VI were measured by ultrasonography within 36 h of intubation and diaphragmatic excursion (DE) was evaluated at the first spontaneous breathing trial in adult critically-ill patients. Reintubation or death within 7 days after extubation was defined as weaning failure. Weaning failure and success groups were compared in terms of ultrasonographic measurements and clinical features.

RESULTS

Thirty-eight patients were assessed for weaning, 15 (39.4%) being in the weaning failure group. The median body mass index (BMI) was lower while the median clinical frailty scale (CFS), vasopressor use, duration of mechanical ventilation, intensive care and hospital mortality rate were higher in the weaning failure group, and the median T_RF + VI (14.0 [12.3-26.2] vs 23.6 [21.3-27.1] mm, p = 0.03) and median DE (19.4 [14.6-24.0] vs 25.9 [19.3-38.5] mm, p = 0.045) were lower. The median T_di was similar in two groups (1.9 [1.5-2.3] vs 2.0 [1.7-2.4] mm, p = 0.26). In ROC analysis, area under the curve for T_RF + VI was 0.71 (95% CI: 0.51-0.90; p = 0.035), with 21 mm cut-off having sensitivity of 82% and specificity of 57%. Binary logistic regression analysis revealed T_RF + VI < 21 mm as the only predictor of weaning failure with an odds ratio of 10.5 (95% CI: 1.1-97.8, p = 0.038) after adjusting for age, sex, BMI and CFS.

CONCLUSIONS

T_RF + VI lower than 21 mm, measured by ultrasonography within 36 h of intubation, was associated with weaning failure among critically-ill patients.

Frailty Severity and Hospitalization After Dialysis Initiation

Background:

Frailty is associated with hospitalization and mortality among dialysis patients. To now, few studies have considered the degree of frailty as a predictor of hospitalization.

Objective:

We evaluated whether frailty severity was associated with hospitalization after dialysis initiation.

Design:

Retrolective cohort study.

Setting:

Nova Scotia, Canada.

Patients:

Consecutive adult, chronic dialysis patients who initiated dialysis from January 1, 2009 to June 30, 2014, (last follow-up June, 2015).

Methods:

Frailty Severity, as determined by the 7-point Clinical Frailty Scale (CFS, ranging from 1 = very fit to 7 = severely frail), was measured at dialysis initiation and treated as continuous and in categories (CFS scores of 1-3, 4/5, and 6/7). Hospitalization was characterized by cumulative time admitted to hospital (proportion of days admitted/time at risk) and by the joint risk of hospitalization and death. Time at risk included time in hospital after dialysis initiation and patients were followed until transplantation or death.

Results:

Of 647 patients (mean age: 62 ± 15), 564 (87%) had CFS scores. The mean CFS score was 4 (“corresponding to “vulnerable”) ± 2 (“well” to “moderately frail”). In an adjusted negative binomial regression model, moderate-severely frail patients (CFS 6/7) had a >2-fold increased risk of cumulative time admitted to hospital compared to the lowest CFS category (IRR = 2.18, 95% confidence interval [CI] = 1.31-3.63). In the joint model, moderate-severely frail patients had a 61% increase in the relative hazard for hospitalization (hazard ratio [HR] = 1.61, 95% CI = 1.29-2.02) and a 93% increase in the relative hazard for death compared to the lowest CFS category (HR = 1.93, 95% CI = 1.16-3.22).

Limitations:

Potential unknown confounders may have affected the association between frailty severity and hospitalization given observational study design. The CFS is subjective and different clinicians may grade frailty severity differently or misclassify patients on the basis of limited availability.

Conclusions:

Among incident dialysis patients, a higher frailty severity as defined by the CFS is associated with both an increased risk of cumulative time admitted to hospital and joint risk of hospitalization and death.

Routine Frailty Screening in Critical Illness: A Population-Based Cohort Study in Australia and New Zealand

BACKGROUND

Frailty is associated with poor outcomes in critical illness. However, it is unclear whether frailty screening on admission to the ICU can be conducted routinely at the population level and whether it has prognostic importance.

RESEARCH QUESTION

Can population-scale frailty screening with the Clinical Frailty Scale (CFS) be implemented for critically ill adults in Australia and New Zealand (ANZ) and can it identify patients at risk of negative outcomes?

STUDY DESIGN AND METHODS

We conducted a binational prospective cohort study of critically ill adult patients admitted between July 1, 2018, and June 30, 2020, in 175 ICUs in ANZ. We classified frailty with the CFS on admission to the ICU. The primary outcome was in-hospital mortality; secondary outcomes were length of stay (LOS), discharge destination, complications (delirium, pressure injury), and duration of survival.

RESULTS

We included 234,568 critically ill patients; 45,245 (19%) were diagnosed as living with frailty before ICU admission. Patients with vs without frailty had higher in-hospital mortality (16% vs 5%; P < .001), delirium (10% vs 4%; P < .001), longer LOS in the ICU and hospital, and increased new chronic care discharge (3% vs 1%; P < .001), with worse outcomes associated with increasing CFS category. Of patients with very severe frailty (CFS score, 8), 39% died in hospital vs 2% of very fit patients (CFS score, 1; multivariate categorical CFS score, 8 [reference, 1]; OR, 7.83 [95% CI, 6.39-9.59]; P < .001). After adjustment for illness severity, frailty remained highly significantly predictive of mortality, including among patients younger than 50 years, with improvement in the area under the receiver operating characteristic curve of the Acute Physiology and Chronic Health Evaluation III-j score to 0.882 (95% CI, 0.879-0.885) from 0.868 (95% CI, 0.866-0.871) with the addition of frailty (P < .001).

INTERPRETATION

Large-scale population screening for frailty degree in critical illness was possible and prognostically important, with greater frailty (especially CFS score of ≥ 6) associated with worse outcomes, including among younger patients.

Critical Care Outreach Team During COVID-19: Ventilatory Support in the Ward and Outcomes

BACKGROUND

During the coronavirus disease 2019 (COVID-19) outbreak, a critical care outreach team was implemented in our hospital to guarantee multidisciplinary patient assessment at admission and prompt ICU support in medical wards. In this paper, we report the activity plan results and describe the baseline characteristics of the referred subjects.

METHODS

We retrospectively evaluated data from 125 subjects referred to the critical care outreach team from March 22 to April 22, 2020. We considered subjects with a ceiling of care decision, with those deemed eligible assigned to level 3 care (ward subgroup), and those deemed ineligible admitted to the ICU (ICU subgroup). Quality indicators of the outreach team plan delivery included number of cardiac arrest calls, number of intubations in level 2 areas, and ineffective palliative support.

RESULTS

We enrolled 125 consecutive adult subjects with a confirmed diagnosis of COVID-19. We did not report any emergency endotracheal intubations in the clinical ward. In the care ceiling subgroup, we had 2 (3.3%) emergency calls for cardiac arrest, whereas signs of ineffective palliative support were reported in 5 subjects (12.5%). Noninvasive forms of respiratory assistance were delivered to 40.0% of subjects in the ward subgroup (median 3 d [interquartile range (IQR) 2-5]), to 45.9% of subjects in the care ceiling subgroup (median 5 d [IQR 3-7]), and to 64.7% of subjects in the ICU subgroup (median 2.5 d [IQR 1-3]). Thirty of the 31 ward subjects (96.7%), 26 of the 34 ICU subjects, (76.4%), and 19 of the 61 ceiling of care subjects (31.1%) were discharged.

CONCLUSIONS

In the context of a hospital and ICU surge, a multidisciplinary daily plan supported by a dedicated critical care outreach team was associated with a low rate of cardiac arrest calls, no emergency intubations in the ward, and appropriate palliative care support for subjects with a ceiling of care decision.

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.

Frailty and hospitalization-associated disability after pneumonia: A prospective cohort study

BACKGROUND

Pneumonia is a major cause of morbidity and mortality in older adults. The role of frailty assessment in older adults with pneumonia is not well defined. Our purpose of the study was to investigate 30-day clinical course and functional outcomes of pneumonia in older adults with different levels of frailty.

METHODS

A prospective cohort was conducted at a university hospital in Seoul, Korea with 176 patients who were 65 years or older and hospitalized with pneumonia. A 50-item deficit-accumulation frailty index (FI) (range: 0-1; robust < 0.15, pre-frail 0.15-0.24, mild-to-moderately frail 0.25-0.44, and severely frail ≥ 0.45) and the pneumonia severity CURB-65 score (range: 0-5) were measured. Primary outcome was death or functional decline, defined as worsening dependencies in 21 daily activities and physical tasks in 30 days. Secondary outcomes were intensive care unit admission, psychoactive drug use, nasogastric tube feeding, prolonged hospitalization (length of stay > 15 days), and discharge to a long-term care institution.

RESULTS

The population had a median age 79 (interquartile range, 75-84) years, 68 (38.6 %) female, and 45 (25.5 %) robust, 36 (47.4 %) pre-frail, 37 (21.0 %) mild-to-moderately frail, and 58 (33.0 %) severely frail patients. After adjusting for age, sex, and CURB-65, the risk of primary outcome for increasing frailty categories was 46.7 %, 61.1 %, 83.8 %, and 86.2 %, respectively (p = 0.014). The risk was higher in patients with frailty (FI ≥ 0.25) than without (FI < 0.25) among those with CURB-65 0-2 points (75 % vs. 52 %; p = 0.022) and among those with CURB-65 3-5 points (93 % vs. 65 %; p = 0.007). In addition, patients with greater frailty were more likely to require nasogastric tube feeding (robust vs. severe frailty: 13.9 % vs. 60.3 %) and prolonged hospitalization (18.2 % vs. 50.9 %) and discharge to a long-term care institution (4.4 % vs. 59.3 %) (p < 0.05 for all). Rates of intensive care unit admission and psychoactive drug use were similar.

CONCLUSIONS

Older adults with frailty experience high rates of death or functional decline in 30 days of pneumonia hospitalization, regardless of the pneumonia severity. These results underscore the importance of frailty assessment in the acute care setting.

Frailty and hospitalization-associated disability after pneumonia: A prospective cohort study

Background

Pneumonia is a major cause of morbidity and mortality in older adults. The role of frailty assessment in older adults with pneumonia is not well defined. Our purpose of the study was to investigate 30-day clinical course and functional outcomes of pneumonia in older adults with different levels of frailty.

Methods

A prospective cohort was conducted at a university hospital in Seoul, Korea with 176 patients who were 65 years or older and hospitalized with pneumonia. A 50-item deficit-accumulation frailty index (FI) (range: 0–1; robust < 0.15, pre-frail 0.15–0.24, mild-to-moderately frail 0.25–0.44, and severely frail ≥ 0.45) and the pneumonia severity CURB-65 score (range: 0–5) were measured. Primary outcome was death or functional decline, defined as worsening dependencies in 21 daily activities and physical tasks in 30 days. Secondary outcomes were intensive care unit admission, psychoactive drug use, nasogastric tube feeding, prolonged hospitalization (length of stay > 15 days), and discharge to a long-term care institution.

Results

The population had a median age 79 (interquartile range, 75–84) years, 68 (38.6 %) female, and 45 (25.5 %) robust, 36 (47.4 %) pre-frail, 37 (21.0 %) mild-to-moderately frail, and 58 (33.0 %) severely frail patients. After adjusting for age, sex, and CURB-65, the risk of primary outcome for increasing frailty categories was 46.7 %, 61.1 %, 83.8 %, and 86.2 %, respectively (p = 0.014). The risk was higher in patients with frailty (FI ≥ 0.25) than without (FI < 0.25) among those with CURB-65 0–2 points (75 % vs. 52 %; p = 0.022) and among those with CURB-65 3–5 points (93 % vs. 65 %; p = 0.007). In addition, patients with greater frailty were more likely to require nasogastric tube feeding (robust vs. severe frailty: 13.9 % vs. 60.3 %) and prolonged hospitalization (18.2 % vs. 50.9 %) and discharge to a long-term care institution (4.4 % vs. 59.3 %) (p < 0.05 for all). Rates of intensive care unit admission and psychoactive drug use were similar.

Conclusions

Older adults with frailty experience high rates of death or functional decline in 30 days of pneumonia hospitalization, regardless of the pneumonia severity. These results underscore the importance of frailty assessment in the acute care setting.

Reliability of the Clinical Frailty Scale in very elderly ICU patients: a prospective European study

Purpose

Frailty is a valuable predictor for outcome in elderly ICU patients, and has been suggested to be used in various decision-making processes prior to and during an ICU admission. There are many instruments developed to assess frailty, but few of them can be used in emergency situations. In this setting the clinical frailty scale (CFS) is frequently used. The present study is a sub-study within a larger outcome study of elderly ICU patients in Europe (the VIP-2 study) in order to document the reliability of the CFS.

Materials and methods

From the VIP-2 study, 129 ICUs in 20 countries participated in this sub-study. The patients were acute admissions ≥ 80 years of age and frailty was assessed at admission by two independent observers using the CFS. Information was obtained from the patient, if not feasible, from the family/caregivers or from hospital files. The profession of the rater and source of data were recorded along with the score. Interrater variability was calculated using linear weighted kappa analysis.

Results

1923 pairs of assessors were included and background data of patients were similar to the whole cohort (n = 3920). We found a very high inter-rater agreement (weighted kappa 0.86), also in subgroup analyses. The agreement when comparing information from family or hospital records was better than using only direct patient information, and pairs of raters from same profession performed better than from different professions.

Conclusions

Overall, we documented a high reliability using CFS in this setting. This frailty score could be used more frequently in elderly ICU patients in order to create a more holistic and realistic impression of the patient´s condition prior to ICU admission.

Norepinephrine Infusion in the Emergency Department in Septic Shock Patients: A Retrospective 2-Years Safety Report and Outcome Analysis

Hemodynamic optimization during sepsis and septic shock is based on a prompt and large fluid resuscitation strategy associated with early administration of norepinephrine. In our hospital, norepinephrine is administered in the emergency department (ED), within a protocol-guided management context, to reduce norepinephrine infusion timing due to central line insertion. This choice, however, can be associated with side effects. Objectives: We conducted a retrospective analysis regarding the safety of norepinephrine in the ED. We also appraised the association between in-hospital mortality and predefined ED variables and patients’ admission severity scores. Design, settings, and participants: This was a retrospective analysis of electronic sheets of the ED of a tertiary hospital in the North of Italy. Outcomes measure and analysis: Electronic documentation was assessed to identify local and systemic side effects. We considered two subgroups of patients according to the in-hospital clinical paths: (1) those admitted in the intensive care unit (ICU); and (2) those who received a ceiling of care decision. We collected and considered variables related to septic shock treatment in the ED and analyzed their association with in-hospital mortality. Main Results: We considered a two-year period, including 108,033 ED accesses, and ultimately analyzed data from 127 patients. Side effects related to the use of this drug were reported in five (3.9%) patients. Thirty patients (23.6%) were transferred to the ICU from the ED, of whom six (20.0%) died. Twenty-eight patients (22.0%) received a ceiling of care indication, of whom 21 (75.0%) died. Of the 69 (54.3%) finally discharged to either medical or surgical wards, 21 (30.4%) died. ICU admission was the only variable significantly associated to in-hospital mortality in the multivariable analysis [OR (95% CI) = 4.48 (1.52–13.22); p-value = 0.007]. Conclusions: Norepinephrine peripheral infusion in the ED was associated with a low incidence of adverse events requiring discontinuation (3.9%). It could be considered safe within <12 h when a specific line management protocol and pump infusion protocol are adopted. None of the variables related to septic shock management affected in-hospital mortality, except for the patient’s ICU admission.

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.

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.

Frailty as a Prognostic Indicator in Intensive Care

BACKGROUND

The percentage of patients in intensive care who are 80 years old or older is continually increasing. Such patients already made up more than 20% of all patients in intensive care in Germany in the years 2007-2011. Meanwhile, effective treatments that support the organs of the body and keep severely ill patients alive are also being continually developed and refined. Frailty is a key prognostic parameter. The scientifically based assessment of frailty can be highly useful in intensive care medicine with regard to consented decision-making, individualized prognostication, treatment planning, and aftercare.

METHODS

Pertinent publications were retrieved by a selective search in the PubMed database. On the basis of the literature assessment, a variety of screening instruments were used to assess frailty and its significance for very old, critically ill patients in German intensive care units.

RESULTS

Only a small number of screening instruments are suitable for routine use in German intensive care units. The scores vary in diagnostic precision. The Clinical Frailty Scale (CFS) enables highly accurate prognostication; it considers the patient in relation to his or her social environment, and to the reference population. Categorization is achieved by means of pictograms that are supplemented with brief written descriptions. The CFS can be used prospectively and is easy to learn. Its interrater reliability is high (weighted Cohen's κ: 0.85 [0.84; 0.87]), and it has been validated for routine use in intensive care units in Germany.

CONCLUSION

None of the available scores enable perfect prognostication. In Germany, frailty in intensive-care patients is currently best assessed on a simple visual scale (CFS).

Sublingual microcirculation detects impaired perfusion in dehydrated older patients

BACKGROUND: Dehydration occurs frequently in older patients and constitutes a significant clinical problem. OBJECTIVE: This proof-of-concept study examines whether 1) sublingual measurement in dehydrated old patients is feasible, 2) frailty and incompliance in old, awake patients affects video-quality, 3) dehydration impacts microcirculation METHODS: This prospective observational study included clinically dehydrated patients aged ≥65 years immediately after admission. Dehydration was assessed clinically. A sidestream dark field camera (SDF) was used for measurement. Video-quality was evaluated with MIQS (microcirculation image quality score). Both AVA 4.3C- and AVA POEM-software analyzed the videos. Seventeen patients ≥65 years not showing dehydration served as control. RESULTS: Thirteen patients (8 female) were included. The average age was 83±8 years. The mini-mental test was 17±15 points, the Clinical Frailty Scale 4±3, the Barthel-Index 59±39. None of these parameters correlated with MIQS (3.4±4.2 SD (“acceptable”)). Dehydrated patients had a slightly impaired microcirculation, with a significantly lower percentage of perfused small vessels compared to control (83.1±7.7% versus 88.0±6.0%, P < 0.05). After rehydration, there was acute improvement in the microcirculation. CONCLUSIONS: Sublingual microcirculatory SDF-measurement is both, safe and valid for dehydrated old patients - regardless of frailty, age or cognitive performance. Dehydration leads to an impaired microcirculation.