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

Association of frailty and sarcopenia with short-term mortality in older critically ill patients

BACKGROUND

There is still no study on the use of the SARC-CalF questionnaire for older critically ill patients. Moreover, there is limited evidence on whether a combination of sarcopenia and frailty can provide incremental improvements in risk stratification for older critically ill patients.

METHODS

A total of 653 patients older than 60 years were recruited. We used the clinical frailty scale (CFS) and SARC-CalF questionnaire to assess the frailty status and sarcopenia risk, respectively, of older patients shortly after admission to the ICU. The effect of frailty and sarcopenia risk on ICU mortality and 30-day mortality was evaluated.

RESULTS

A total of 147 (22.5%) patients died in the ICU, and 187 (28.6%) patients died within 30 days after ICU admission. The CFS score was associated with increased ICU mortality [per 1-score increase: odds ratio (OR) = 1.222, 95% confidential interval (CI): 1.003-1.489] and 30-day mortality (per 1-score increase: OR = 1.307, 95% CI: 1.079-1.583). The SARC-CalF score was also associated with increased ICU mortality (per 1-score increase: OR = 1.204, 95% CI: 1.120-1.294) and 30-day mortality (per 1-score increase: OR = 1.247, 95% CI: 1.163-1.337). The addition of the CFS + SARC-CalF score to Acute Physiology and Chronic Health Evaluation (APACHE) II improved discrimination and reclassified ICU and 30-day mortality risk.

CONCLUSIONS

Sarcopenia risk assessed by the SARC-CalF questionnaire provided independent prognostic information for older critically ill patients. A combination of sarcopenia and frailty improved the prediction of mortality for older critically ill patients and thus might be useful in the clinical decision-making process.

Agreement and predictive value of the clinical frailty scale in hospitalized older patients

PURPOSE

Our objective was to perform an external validity study of the clinical frailty scale (CFS) classification tree by determining the agreement of the CFS when attributed by a senior geriatrician, a junior geriatrician, or using the classification tree. Additionally, we evaluated the predictive value of the CFS for 6-month mortality after admission to an acute geriatric unit.

METHODS

This prospective study was conducted in two acute geriatric units in Belgium. The premorbid CFS was determined by a senior and a junior geriatrician based on clinical judgment within the first 72 h of admission. Another junior geriatrician, who did not have a treatment relationship with the patient, scored the CFS using the classification tree. Intra-class correlation coefficient (ICC) was calculated to assess agreement. A ROC curve and Cox regression model determined prognostic value.

RESULTS

In total, 97 patients were included (mean age 86 ± 5.2; 66% female). Agreement of the CFS, when determined by the senior geriatrician and the classification tree, was moderate (ICC 0.526, 95% CI [0.366-0.656]). This is similar to the agreement between the senior and junior geriatricians' CFS (ICC 0.643, 95% CI [0.510-0.746]). The AUC for 6-month mortality based on the CFS by respectively the classification tree, the senior and junior geriatrician was 0.719, 95% CI [0.592-0.846]; 0.774, 95% CI [0.673-0.875]; 0.774, 95% CI [0.665-0.882]. Cox regression analysis indicated that severe or very severe frailty was associated with a higher risk of mortality compared to mild or moderate frailty (hazard ratio respectively 6.274, 95% CI [2.613-15.062] by the classification tree; 3.476, 95% CI [1.531-7.888] by the senior geriatrician; 4.851, 95% CI [1.891-12.442] by the junior geriatrician).

CONCLUSION

Interrater agreement in CFS scoring on clinical judgment without Comprehensive Geriatric Assessment is moderate. The CFS classification tree can help standardize CFS scoring.

Cluster analysis of thoracic muscle mass using artificial intelligence in severe pneumonia

Severe pneumonia results in high morbidity and mortality despite advanced treatments. This study investigates thoracic muscle mass from chest CT scans as a biomarker for predicting clinical outcomes in ICU patients with severe pneumonia. Analyzing electronic medical records and chest CT scans of 778 ICU patients with severe community-acquired pneumonia from January 2016 to December 2021, AI-enhanced 3D segmentation was used to assess thoracic muscle mass. Patients were categorized into clusters based on muscle mass profiles derived from CT scans, and their effects on clinical outcomes such as extubation success and in-hospital mortality were assessed. The study identified three clusters, showing that higher muscle mass (Cluster 1) correlated with lower in-hospital mortality (8% vs. 29% in Cluster 3) and improved clinical outcomes like extubation success. The model integrating muscle mass metrics outperformed conventional scores, with an AUC of 0.844 for predicting extubation success and 0.696 for predicting mortality. These findings highlight the strong predictive capacity of muscle mass evaluation over indices such as APACHE II and SOFA. Using AI to analyze thoracic muscle mass via chest CT provides a promising prognostic approach in severe pneumonia, advocating for its integration into clinical practice for better outcome predictions and personalized patient management.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Prognosticating the outcome of intensive care in older patients-a narrative review

Prognosis determines major decisions regarding treatment for critically ill patients. Statistical models have been developed to predict the probability of survival and other outcomes of intensive care. Although they were trained on the characteristics of large patient cohorts, they often do not represent very old patients (age ≥ 80 years) appropriately. Moreover, the heterogeneity within this particular group impairs the utility of statistical predictions for informing decision-making in very old individuals. In addition to these methodological problems, the diversity of cultural attitudes, available resources as well as variations of legal and professional norms limit the generalisability of prediction models, especially in patients with complex multi-morbidity and pre-existing functional impairments. Thus, current approaches to prognosticating outcomes in very old patients are imperfect and can generate substantial uncertainty about optimal trajectories of critical care in the individual. This article presents the state of the art and new approaches to predicting outcomes of intensive care for these patients. Special emphasis has been given to the integration of predictions into the decision-making for individual patients. This requires quantification of prognostic uncertainty and a careful alignment of decisions with the preferences of patients, who might prioritise functional outcomes over survival. Since the performance of outcome predictions for the individual patient may improve over time, time-limited trials in intensive care may be an appropriate way to increase the confidence in decisions about life-sustaining treatment.

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.

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

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

Critical care beyond organ support: the importance of geriatric rehabilitation

Very old critically ill patients pose a growing challenge for intensive care. Critical illness and the burden of treatment in the intensive care unit (ICU) can lead to a long-lasting decline of functional and cognitive abilities, especially in very old patients. Multi-complexity and increased vulnerability to stress in these patients may lead to new and worsening disabilities, requiring careful assessment, prevention and rehabilitation. The potential for rehabilitation, which is crucial for optimal functional outcomes, requires a systematic, multi-disciplinary approach and careful long-term planning during and following ICU care. We describe this process and provide recommendations and checklists for comprehensive and timely assessments in the context of transitioning patients from ICU to post-ICU and acute hospital care, and review the barriers to the provision of good functional outcomes.

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.

Recovery following discharge from intensive care: What do patients think is helpful and what services are missing?

BACKGROUND

Recovery following critical illness is complex due to the many challenges patients face which influence their long-term outcomes. We explored patients' views about facilitators of recovery after critical illness which could be used to inform the components and timing of specific rehabilitation interventions.

AIMS

To explore the views of patients after discharge from an intensive care unit (ICU) about their recovery and factors that facilitated recovery, and to determine additional services that patients felt were missing during their recovery.

METHODS

Qualitative study involving individual face-to-face semi-structured interviews at six months (n = 11) and twelve months (n = 10). Written, informed consent was obtained. [Ethics approval 17/NI/0115]. Interviews were audiotaped, transcribed and analysed using template analysis.

FINDINGS

Template analysis revealed four core themes: (1) Physical activity and function; (2) Recovery of cognitive and emotional function; (3) Facilitators to recovery; and (4) Gaps in healthcare services.

CONCLUSION

Patient reported facilitators to recovery include support and guidance from others and self-motivation and goal setting, equipment for mobility and use of technology. Barriers include a lack of follow up services, exercise rehabilitation, peer support and personal feedback. Patients perceived that access to specific healthcare services was fragmented and where services were unavailable this contributed to slower or poorer quality of recovery. ICU patient recover could be facilitated by a comprehensive rehabilitation intervention that includes patient-directed strategies and health care services.

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 trajectory of very old critically ill patients

The demographic shift, together with financial constraint, justify a re-evaluation of the trajectory of care of very old critically ill patients (VIP), defined as older than 80 years. We must avoid over- as well as under-utilisation of critical care interventions in this patient group and ensure the inclusion of health care professionals, the patient and their caregivers in the decision process. This new integrative approach mobilises expertise at each step of the process beginning prior to intensive care unit (ICU) admission and extending to long-term follow-up. In this review, several international experts have contributed to provide recommendations that can be universally applied. Our aim is to define a minimum core dataset of information to be shared and discussed prior to ICU admission and to facilitate the shared-decision-making process with the patient and their caregivers, throughout the patient journey. Documentation of uncertainty may contribute to a tailored level of care and ultimately to discussions around possible limitations of life sustaining treatments. The goal of ICU care is not only to avoid death, but more importantly to maintain an acceptable quality of life and functional autonomy after hospital discharge. Societal consideration is important to highlight, together with alternatives to ICU admission. We discuss challenges for the future and potential areas of research. In summary, this review provides a state-of-the-art current overview and aims to outline future directions to address the challenges in the treatment of VIP.

Ethics: Crisis Standards of Care Simulation

Ethical dilemmas exist with decision-making regarding resource allocations, such as critical care, ventilators and other critical equipment, and pharmaceuticals during pandemics. Triage artificial intelligence (AI) algorithms based on prognostication tools exist to guide these decisions; however, implicit bias may affect the decision-making process leading to deviation from the algorithm recommendations. Conflict within the ethical domain may be affected as well. A knowledge gap was identified within the Adult-Gerontology Acute Care Nurse Practitioner (AG-ACNP) curriculum regarding ethics in crisis standards of care (CSC) medical decision-making. Incorporating a CSC simulation looked to address this knowledge gap. A simulation-based learning (SBL) experience was designed as a critical access setting where CSC are in place and three diverse, medically complex patients in need of critical care present to the hospital where one critical care bed remains open. Given the complexity of the simulation scenario, a table-top pilot test was selected. Three AG-ACNP fourth-quarter students in their critical care rotation volunteered for the pilot test. Students were provided with the topic, "ethics crisis standards of care" and the article, "A catalogue of tools and variables from crisis and routine care to support decision-making during pandemics" by M. Cardona et al. (2021), to read in advance. Students were provided with the triage AI algorithm (M. Cardona et al., 2021) utilizing prognostication tools to prioritize which patient requires the critical care bed. The expectation was that implicit bias would enter the decision-making process, causing deviation from the triage AI algorithm and moral distress. The debriefing session revealed that students deviated from the triage AI algorithm, experienced implicit bias, moral distress, and utilized clinical judgment and experience to care for all three patients. The pilot test results support that a CSC SBL experience addresses a critical knowledge gap in AG-ACNP education and an SBL experience incorporating ethical decision-making curriculum with standardized patients should be developed and trialed as the next step.

Frailty's influence on 30-day mortality in old critically ill ICU patients: a bayesian analysis evaluating the clinical frailty scale

INTRODUCTION

Frailty is widely acknowledged as influencing health outcomes among critically ill old patients. Yet, the traditional understanding of its impact has predominantly been through frequentist statistics. We endeavored to explore this association using Bayesian statistics aiming to provide a more nuanced understanding of this multifaceted relationship.

METHODS

Our analysis incorporated a cohort of 10,363 older (median age 82 years) patients from three international prospective studies, with 30-day all-cause mortality as the primary outcome. We defined frailty as Clinical Frailty Scale ≥ 5. A hierarchical Bayesian logistic regression model was employed, adjusting for covariables, using a range of priors. An international steering committee of registry members reached a consensus on a minimal clinically important difference (MCID).

RESULTS

In our study, the 30-day mortality was 43%, with rates of 38% in non-frail and 51% in frail groups. Post-adjustment, the median odds ratio (OR) for frailty was 1.60 (95% CI 1.45-1.76). Frailty was invariably linked to adverse outcomes (OR > 1) with 100% probability and had a 90% chance of exceeding the minimal clinically important difference (MCID) (OR > 1.5). For the Clinical Frailty Scale (CFS) as a continuous variable, the median OR was 1.19 (1.16-1.22), with over 99% probability of the effect being more significant than 1.5 times the MCID. Frailty remained outside the region of practical equivalence (ROPE) in all analyses, underscoring its clinical importance regardless of how it is measured.

CONCLUSIONS

This research demonstrates the significant impact of frailty on short-term mortality in critically ill elderly patients, particularly when the Clinical Frailty Scale (CFS) is used as a continuous measure. This approach, which views frailty as a spectrum, enables more effective, personalized care for this vulnerable group. Significantly, frailty was consistently outside the region of practical equivalence (ROPE) in our analysis, highlighting its clinical importance.

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.

Exploring fraity and sarcopenia in older adults admitted to acute medical unit, looking at prevalence, trajectory, and outcomes: A protocol testing the feasibility and acceptability of the TYSON study

BACKGROUND

Frailty and sarcopenia are common in older people and are associated with adverse outcomes including increased mortality and morbidity. It is unclear whether screening for frailty and sarcopenia would identify specific populations most at risk of poor outcomes during unplanned hospital admissions, which screening tools should be used and what the trajectory of both conditions are over the course of an admission. The TYSON study is an observational cohort study aiming to determine the prevalence, trajectory and outcomes associated with frailty and sarcopenia in different patient cohorts. This protocol tests the feasibility and acceptability of TYSON processes.

OBJECTIVES

To determine in acutely admitted medical patients who are older adults: Primary: The feasibility and acceptability of frailty and sarcopenia assessments; Secondary: (1) Differences in community and hospital frailty assessments, as assessed by the medical team, the patient and elderly care physicians, (2) The dynamic changes in frailty and sarcopenia during a hospital admission, and patient outcomes; Exploratory: Inflammatory and metabolic mediators associated with frailty and sarcopenia.

METHODS

A single centre, prospective observational study including patients aged ≥ 65 years admitted to an acute medical unit. Frailty assessments include the Rockwood clinical frailty and e-frailty index. Sarcopenia assessments include the Bilateral Anterior Thigh Thickness (BATT) measurement. Each participant will be asked to complete 5 visits, at day 0, day 3, day 7, month 3 and month 6. Blood samples will be collected to explore inflammatory and metabolic markers associated with frailty and sarcopenia. The study and protocol have been ethically approved by the Health Research Authority (REC 20/WA/0263).

DISCUSSION

The study will determine the feasibility and acceptability of frailty and sarcopenia assessments in an acute hospital setting, and inform on the prevalence, trajectory and associated outcomes of frailty and sarcopenia in this group of patients. An inflammatory and metabolic profile will be explored in frailty and sarcopenia.

[Frailty phenotype and risk factor for disturbed sleep]

Regardless of the nature of its operationalization, frailty has significant negative consequences for the person concerned and the community. Even if a generally accepted definition of frailty is still missing, there is no doubt about the existence of this phenomenon. Pathophysiologically, a dysfunctional interaction between multiple complex systems is discussed. Therapeutic interventions show that frailty is a dynamic state that can be improved. The pathophysiological characteristics of frailty and sleep disturbances show numerous similarities. In addition, the risk of frailty is increased in individuals with sleep disturbances. As the majority of sleep disorders can usually be well treated, screening for sleep disorders should be integrated into a comprehensive concept of management of frailty.