Frailty and the Association Between Long-Term Recovery After Intensive Care Unit Admission

Frailty and sarcopenia in patients with acute-on-chronic liver failure: Assessment and risk in the liver transplant setting

Frailty and sarcopenia are well-recognized factors related to worse outcomes in patients with cirrhosis, including liver transplant (LT) candidates. Implications of pre-LT functional and muscle deterioration also affect post-LT outcomes. Patients with cirrhosis and acute-on-chronic liver failure (ACLF) have a lower survival rate, both before and after LT. There is a need to better identify those patients with ACLF who would benefit from LT. This review aims to present the available data about frailty and sarcopenia in patients with ACLF in the LT setting. An exhaustive review of the published literature was conducted. Data regarding frailty and sarcopenia in LT candidates with ACLF are scarce and heterogeneous. Studies evaluating frailty and sarcopenia in critically ill patients outside the liver literature are also presented in this review to enrich the knowledge of this field in expansion. Frailty and sarcopenia seem to contribute to worse outcomes in LT candidates with ACLF, both before and after LT. Sarcopenia evaluation may be the most prudent approach for those very sick patients. Skeletal muscle index assessed by computed tomography is recommended to evaluate sarcopenia. The role of muscle ultrasound and bioelectrical impedance analysis is to be determined. Frailty and sarcopenia are crucial factors to consider on a case-by-case basis in LT candidates with ACLF to improve patient outcomes best.

Biological age as a predictor of unplanned intensive care readmission during the same hospitalization

BACKGROUND

Biological age is increasingly being recognized as an important predictor of health but its utility in acute care setting remains uncertain.

OBJECTIVE

We assessed whether biological age on intensive care unit (ICU) admission can predict unplanned ICU readmission during the same hospitalization.

METHODS

The Levine PhenoAge model based on biomarkers of DNA methylation was used to determine each patient's biological age. The difference between PhenoAge and chronological age was indexed to the local context by regressing PhenoAge on chronological age using linear regression. A positive residual implied one's biological age was older than the corresponding chronological age compared to other patients - defined as PhenoAgeAccel.

RESULTS

Of the 2950 patients included, 153 (5.2%) had unplanned ICU readmission. Chronological age, Acute Physiology and Chronic Health Evaluation II score, the use of mechanical ventilation, vasopressor, or renal replacement therapy were not significantly different between those with and without readmission. PhenoAgeAccel was, however, more common among those who had unplanned ICU readmission (52% vs 43%, p =0.031). Quantitatively, the degree of phenotypical age above chronological age exhibited a 'dose-related' relationship with the risk of readmission (odds ratio 1.12, 95% confidence interval 1.01-1.24; p=0.040) after adjusting for chronological age, comorbidities, and severity of acute illness in the index (first) ICU admission.

CONCLUSION

Biological age was predictive of unplanned ICU readmission during the same hospitalization.

The final decision among the injured elderly, to stop or to continue? Predictors of withdrawal of life supporting treatment

BACKGROUND

There is a paucity of data on factors that influence the decision regarding withdrawal of life supporting treatment (WLST) in geriatric trauma patients. We aimed to identify predictors of WLST in geriatric trauma patients.

METHODS

This retrospective analysis of the American College of Surgeons- Trauma Quality Improvement Program (2017-2019) included all severely injured (Injury Severity Score >15) geriatric trauma patients (≥65 years). Multivariable logistic regression was performed to identify independent predictors of WLST.

RESULTS

There were 155,583 patients included. Mean age was 77 ± 7 years, 55% were male, 97% sustained blunt injury, and the median Injury Severity Score was 17 [16-25]. Overall WLST rate was 10.8%. On MLR analysis, increasing age (adjusted odds ratio [aOR], 1.35; 95% confidence interval [CI], 1.33-1.37; p < 0.001), male sex (aOR, 1.14; 95% CI, 1.09-1.18; p < 0.001), White race (aOR, 1.44; 95% CI, 1.36-1.52; p < 0.001), frailty (aOR, 1.42; 95% CI, 1.34-1.50; p < 0.001), government insurance (aOR, 1.27; 95% CI, 1.20-1.33; p < 0.001), presence of advance directive limiting care (aOR, 2.55; 95% CI, 2.40-2.70; p < 0.001), severe traumatic brain injury (aOR, 1.80; 95% CI, 1.66-1.95; p < 0.001), ventilator requirement (aOR, 12.73; 95% CI, 12.09-13.39; p < 0.001), and treatment at higher level trauma centers (Level I aOR, 1.49; 95% CI, 1.42-1.57; p < 0.001; Level II aOR, 1.43; 95% CI, 1.35-1.51; p < 0.001) were independently associated with higher odds of WLST.

CONCLUSION

Our results suggest that nearly one in 10 severely injured geriatric trauma patients undergo WLST. Multiple patient and hospital related factors contribute to decision making and directed efforts are necessary to create a more standardized process.

LEVEL OF EVIDENCE

Prognostic and Epidemiological; Level III.

The role of clinical phenotypes in decisions to limit life-sustaining treatment for very old patients in the ICU

BACKGROUND

Limiting life-sustaining treatment (LST) in the intensive care unit (ICU) by withholding or withdrawing interventional therapies is considered appropriate if there is no expectation of beneficial outcome. Prognostication for very old patients is challenging due to the substantial biological and functional heterogeneity in that group. We have previously identified seven phenotypes in that cohort with distinct patterns of acute and geriatric characteristics. This study investigates the relationship between these phenotypes and decisions to limit LST in the ICU.

METHODS

This study is a post hoc analysis of the prospective observational VIP2 study in patients aged 80 years or older admitted to ICUs in 22 countries. The VIP2 study documented demographic, acute and geriatric characteristics as well as organ support and decisions to limit LST in the ICU. Phenotypes were identified by clustering analysis of admission characteristics. Patients who were assigned to one of seven phenotypes (n = 1268) were analysed with regard to limitations of LST.

RESULTS

The incidence of decisions to withhold or withdraw LST was 26.5% and 8.1%, respectively. The two phenotypes describing patients with prominent geriatric features and a phenotype representing the oldest old patients with low severity of the critical condition had the largest odds for withholding decisions. The discriminatory performance of logistic regression models in predicting limitations of LST after admission to the ICU was the best after combining phenotype, ventilatory support and country as independent variables.

CONCLUSIONS

Clinical phenotypes on ICU admission predict limitations of LST in the context of cultural norms (country). These findings can guide further research into biases and preferences involved in the decision-making about LST. Trial registration Clinical Trials NCT03370692 registered on 12 December 2017.

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

OBJECTIVES

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

DESIGN

Retrospective observational study.

SETTING AND PARTICIPANTS

9,082 critically ill survivors aged ≥ 65 years.

MEASUREMENTS

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

RESULTS

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

CONCLUSION

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Association between frailty and clinical outcomes in hospitalised patients requiring Code Blue activation

BACKGROUND

Code Blues allow a rapid, hospital wide response to acutely deteriorating patients. The concept of frailty is being increasingly recognised as an important element in determining outcomes of critically ill patients. We hypothesised that increasing frailty would be associated with worse outcomes following a Code Blue.

AIMS

To investigate the association between increasing frailty and outcomes of Code Blues.

METHODS

Single-centre retrospective design of patients admitted to Frankston Hospital in Australia between 1 January 2013 and 31 December 2017 who triggered a Code Blue. Frailty evaluation was made based on electronic medical records as were the details and the outcomes of the Code Blue. The primary outcome measure was a composite of hospital mortality or Cerebral Performance Categories scale ≥3. Secondary outcomes included the immediate outcome of the Code Blue and hospital mortality.

RESULTS

One hundred and forty-eight of 911 screened patients were included in the final analysis. Seventy-three were deemed 'frail' and the remainder deemed 'fit'. Seventy-eight  percent of frail patients reached the primary outcome, compared with 41% of fit patients (P < 0.001). Multivariable analysis demonstrated frailty to be associated with primary outcome (odds ratio = 2.87; 95% confidence interval (CI) 1.28-6.44; P = 0.01). A cardiac aetiology for the Code Blue was also associated with an increased odds of primary outcome (OR = 3.52; 95% CI 1.51-8.05; P = 0.004).

CONCLUSIONS

Frailty is independently associated with the composite outcome of hospital mortality or severe disability following a Code Blue. Frailty is an important tool in prognostication for these patients and might aid in discussions regarding treatment limitations.

Effect of Systemic Lidocaine on Postoperative Early Recovery Quality in Patients Undergoing Supratentorial Tumor Resection

Purpose

Lidocaine has been gradually used in general anesthesia. This study was designed to investigate the effect of systemic lidocaine on postoperative quality of recovery (QoR) in patients undergoing supratentorial tumor resection, and to explore its brain-injury alleviation effect in neurosurgical anesthesia.

Patients and Methods

Sixty adult patients undergoing elective supratentorial tumor resection. Patients were randomly assigned either to receive lidocaine (Group L: 1.5 mg/kg bolus completed 10 min before anesthesia induction followed by an infusion at 2.0 mg/kg/h) or to receive normal saline (Group C: received volume-matched normal saline at the same infusion rate). Primary outcome measures were Quality of Recovery-40 (QoR-40) scores on postoperative day (POD) 1 and 2. Plasma concentrations of S100B protein (S100B), neuron specific enolase (NSE), interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) before anesthesia induction and at the end of surgery were assessed. Visual Analogue Scale (VAS) scores were assessed at 1, 2, 6, 12, 24 and 48 h after surgery. Perioperative parameters and adverse events were also recorded.

Results

Patients between two groups had comparable baseline characteristics. Global QoR-40 scores on POD 1 and POD 2 were significantly higher (P <0.001) in group L (165.5±3.8 vs 173.7±4.7) than those in group C (155.6±4.0 vs 163.2±4.5); and scores of physical comfort, emotional state, and pain in group L were superior to those in group C (P <0.05). In group L, patients possessed lower plasma concentration of pro-inflammatory factors (IL-6, TNF-α) and brain injury-related factors (S100B, NSE) (P <0.05), consumed less remifentanil and propofol, and experienced lower pain intensity. Multiple linear regression analysis demonstrated age and pain were correlated with postperative recovery quality.

Conclusion

Systemic lidocaine improved early recovery quality after supratentorial tumor resection with general anesthesia, and had certain brain-injury alleviation effects. These benefits may be attributed to the inflammation-alleviating and analgesic properties of lidocaine.

Characteristics and resource utilization of high-cost users in the intensive care unit: a population-based cohort study

Background

Healthcare expenditure within the intensive care unit (ICU) is costly. A cost reduction strategy may be to target patients accounting for a disproportionate amount of healthcare spending, or high-cost users. This study aims to describe high-cost users in the ICU, including health outcomes and cost patterns.

Methods

We conducted a population-based retrospective cohort study of patients with ICU admissions in Ontario from 2011 to 2018. Patients with total healthcare costs in the year following ICU admission (including the admission itself) in the upper 10th percentile were defined as high-cost users. We compared characteristics and outcomes including length of stay, mortality, disposition, and costs between groups.

Results

Among 370,061 patients included, 37,006 were high-cost users. High-cost users were 64.2 years old, 58.3% male, and had more comorbidities (41.2% had ≥3) when likened to non-high cost users (66.1 years old, 57.2% male, 27.9% had ≥3 comorbidities). ICU length of stay was four times greater for high-cost users compared to non-high cost users (22.4 days, 95% confidence interval [CI] 22.0–22.7 days vs. 5.56 days, 95% CI 5.54–5.57 days). High-cost users had lower in-hospital mortality (10.0% vs.14.2%), but increased dispositioning outside of home (77.4% vs. 42.2%) compared to non-high-cost users. Total healthcare costs were five-fold higher for high-cost users ($238,231, 95% CI $237,020–$239,442) compared to non-high-cost users ($45,155, 95% CI $45,046–$45,264). High-cost users accounted for 37.0% of total healthcare costs.

Conclusion

High-cost users have increased length of stay, lower in-hospital mortality, and higher total healthcare costs when compared to non-high-cost users. Further studies into cost patterns and predictors of high-cost users are necessary to identify methods of decreasing healthcare expenditure.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-07318-y.

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.

Six-Month Outcomes in COVID-19 ICU Patients and Their Family Members: A Prospective Cohort Study

Background: The COVID-19 pandemic has resulted in a major influx of intensive care unit (ICU) admissions. Currently, there is limited knowledge on the long-term outcomes of COVID-19 ICU-survivors and the impact on family members. This study aimed to gain an insight into the long-term physical, social and psychological functioning of COVID-19 ICU-survivors and their family members at three- and six-months following ICU discharge. Methods: A single-center, prospective cohort study was conducted among COVID-19 ICU-survivors and their family members. Participants received questionnaires at three and six months after ICU discharge. Physical functioning was evaluated using the MOS Short-Form General Health Survey, Clinical Frailty Scale and spirometry tests. Social functioning was determined using the McMaster Family Assessment Device and return to work. Psychological functioning was assessed using the Hospital Anxiety and Depression Scale. Results: Sixty COVID-19 ICU-survivors and 78 family members participated in this study. Physical functioning was impaired in ICU-survivors as reflected by a score of 33.3 (IQR 16.7–66.7) and 50 (IQR 16.7–83.3) out of 100 at 3- and 6-month follow-ups, respectively. Ninety percent of ICU-survivors reported persistent symptoms after 6 months. Social functioning was impaired since 90% of COVID-19 ICU-survivors had not reached their pre-ICU work level 6 months after ICU-discharge. Psychological functioning was unaffected in COVID-19 ICU-survivors. Family members experienced worse work status in 35% and 34% of cases, including a decrease in work rate among 18.3% and 7.4% of cases at 3- and 6-months post ICU-discharge, respectively. Psychologically, 63% of family members reported ongoing impaired well-being due to the COVID-19-related mandatory physical distance from their relatives. Conclusion: COVID-19 ICU-survivors suffer from a prolonged disease burden, which is prominent in physical and social functioning, work status and persisting symptoms among 90% of patients. Family members reported a reduction in return to work and impaired well-being. Further research is needed to extend the follow-up period and study the effects of standardized rehabilitation in COVID-19 patients and their family members.

Association between preoperative frailty and outcomes among adults undergoing cardiac surgery: a prospective cohort study

BACKGROUND

The identification of frailty before complex and invasive procedures may have relevance for prognostic and recovery purposes, to optimally inform patients, caregivers and clinicians about perioperative risk and postoperative care needs. The aim of this study was to estimate the prevalence of frailty and describe the associated clinical course and outcomes of patients referred for nonemergent cardiac surgery.

METHODS

A prospective cohort of patients aged 50 years and older referred for nonemergent cardiac surgery in Alberta, Canada, from November 2011 to March 2014 were screened preoperatively for frailty, defined as a Clinical Frailty Scale (CFS) score of 5 or greater. Postoperatively, patients were followed by telephone to assess CFS score, health services use and vital status. The primary outcome was all-cause hospital mortality. Secondary outcomes included health services use, hospital discharge disposition, 1-year health-related quality of life and all-cause 5-year mortality.

RESULTS

The cohort (n = 529) had a mean age of 67 (standard deviation [SD] 9) years; 25.9% were female, and the prevalence of frailty was 9.6% (n = 51; 95% confidence interval [CI] 7.3%-12.5%). Frail patients were older (median age 75, interquartile range [IQR] 65-80 v. 67, IQR 60-73, yr; p < 0.001), were more likely to be female (51.0% v. 23.2%; p < 0.001), had a higher mean EuroSCORE II (8, SD 3 v. 5, SD 3; p < 0.001) and received combined coronary artery bypass grafting and valve procedures more frequently (29.4% v. 15.9%; p = 0.02) than nonfrail patients. Postoperatively, frail patients had a longer median duration of stay in the cardiovascular intensive care unit (median difference 2.2, 95% CI 1.60-2.79) and hospital (median difference 9.3, 95% CI 8.2-10.3). Hospital mortality was 9.8% among frail patients and 1.0% among nonfrail patients (adjusted hazard ratio 3.84, 95% CI 0.90-16.34).

INTERPRETATION

Preoperative frailty was present in 10% of patients and was associated with a higher risk of morbidity and greater health services use. Preoperative frailty has important implications for the postoperative clinical course and resource utilization of patients undergoing cardiac surgery.

Frailty inclusive care in acute and community-based settings: a systematic review protocol

BACKGROUND

Frailty is a known risk factor for an array of adverse outcomes including more frequent and prolonged health services use and high health care costs. Aging of the population has implications for care provision across the care continuum, particularly for people living with frailty. Despite known risks associated with frailty, there has been limited research on care pathways that address the needs of persons living with frailty. Our study aims to review and examine, in a rigorous way, the quality of evidence for multi-component interventions and care pathways focused on frailty.

METHODS

A comprehensive electronic search strategy will be used to identify studies that evaluate multi-component interventions or care pathways for persons living with frailty. The search strategy will include terms for frailty, multi-component interventions, effectiveness, and cost effectiveness applied to the following databases: MEDLINE (OVID), EMBASE (OVID), CINAHL (EBSCO), Cochrane Central Register of Controlled Trials (CENTRAL), and Cochrane Database of Systematic Reviews. An adapted search for Google Scholar and gray literature databases will also be used. References of included studies will be hand-searched for additional citations of frailty-inclusive care. Known experts and corresponding authors of identified articles will be contacted by email to identify further eligible studies. Risk of bias will be assessed using the Effective Public Health Practice Project Quality Assessment tool. Data will be extracted from eligible studies and it is anticipated that narrative analysis will be used. If studies with sufficient homogeneity are found, then pooled effects will be reported using meta-analysis.

DISCUSSION

This review will appraise the evidence currently available on multi-component frailty interventions. Results will inform on clinical pathway development for people living with frailty across the care continuum and will guide future research to address gaps in the literature and areas in need of further development.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42020166733.

Divergent trajectories of cellular bioenergetics, intermediary metabolism and systemic redox status in survivors and non-survivors of critical illness

Background

Numerous pathologies result in multiple-organ failure, which is thought to be a direct consequence of compromised cellular bioenergetic status. Neither the nature of this phenotype nor its relevance to survival are well understood, limiting the efficacy of modern life-support.

Methods

To explore the hypothesis that survival from critical illness relates to changes in cellular bioenergetics, we combined assessment of mitochondrial respiration with metabolomic, lipidomic and redox profiling in skeletal muscle and blood, at multiple timepoints, in 21 critically ill patients and 12 reference patients.

Results

We demonstrate an end-organ cellular phenotype in critical illness, characterized by preserved total energetic capacity, greater coupling efficiency and selectively lower capacity for complex I and fatty acid oxidation (FAO)-supported respiration in skeletal muscle, compared to health. In survivors, complex I capacity at 48 h was 27% lower than in non-survivors (p = 0.01), but tended to increase by day 7, with no such recovery observed in non-survivors. By day 7, survivors’ FAO enzyme activity was double that of non-survivors (p = 0.048), in whom plasma triacylglycerol accumulated. Increases in both cellular oxidative stress and reductive drive were evident in early critical illness compared to health. Initially, non-survivors demonstrated greater plasma total antioxidant capacity but ultimately higher lipid peroxidation compared to survivors. These alterations were mirrored by greater levels of circulating total free thiol and nitrosated species, consistent with greater reductive stress and vascular inflammation, in non-survivors compared to survivors. In contrast, no clear differences in systemic inflammatory markers were observed between the two groups.

Conclusion

Critical illness is associated with rapid, specific and coordinated alterations in the cellular respiratory machinery, intermediary metabolism and redox response, with different trajectories in survivors and non-survivors. Unravelling the cellular and molecular foundation of human resilience may enable the development of more effective life-support strategies.

Rehabilitation Concerns in the Geriatric Critically Ill and Injured - Part 1

Elderly patients who are critically ill have unique challenges that must be considered when attempting to prognosticate survival and determine expectations for physical rehabilitation and meaningful recovery. Furthermore, frail elderly patients present unique rehabilitation and clinical challenges when suffering from critical illness. There are multiple symptoms and syndromes that affect morbidity and mortality of elderly patients who require intensive care unit management including delirium, dementia, pain, and constipation. Rehabilitation goals should be based on patient values, clinical course, and functional status. Patients and families need accurate prognostic information to choose the appropriate level of care needed after critical illness.

Electronic Medical Record Versus Bedside Assessment: How to Evaluate Frailty in Trauma and Emergency General Surgery Patients?

BACKGROUND

Screening patients for frailty is traditionally done at the bedside. However, recent electronic medical record (EMR)-based, comorbidity-focused frailty assessments have been developed. Our objective was to determine how a common bedside frailty assessment, the trauma and emergency surgery (TEGS) frailty index (FI), compares to an EMR-based frailty assessment in predicting geriatric TEGS outcomes.

MATERIALS AND METHODS

We retrospectively reviewed our quality improvement project database consisting of TEGS patients ≥ 65 y old. Patients were screened with the TEGS FI, a 15-question bedside assessment, including comorbidities, physical activity, emotional health, and nutrition. Six of 15 items were retrievable from the enterprise data warehouse (EDW), storing all EMR data from Northwestern Memorial Hospital, and use to calculate the EDW frailty score. Patient characteristics and outcomes were compared between different groups.

RESULTS

Two hundred thirty-six geriatric TEGS patients were included, of which 75 (31.8%) were TEGS FI frail and 60 (25.4%) were EDW frail. TEGS FI frail patients had increased length of stay (LOS), loss of independence (LOI), and complications compared to TEGS FI nonfrail patients. EDW frail patients had higher LOS and complications than EDW nonfrail patients but similar LOI. TEGS FI and EDW frail patients had similar outcomes except TEGS FI-only patients more often have LOI.

CONCLUSIONS

Bedside frailty assessments and EMR-based assessments are both effective in identifying geriatric TEGS patients at risk for increased LOS and complications. However, bedside frailty screening was better at identifying patients who have LOI and may be a more appropriate choice when screening for frailty.

Implementation of population-level screening for frailty among patients admitted to adult intensive care in Alberta, Canada

PURPOSE

A substantial proportion of patients admitted to intensive care units (ICUs) are frail; however, the epidemiology of frailty has not been explored at a population-level. Following implementation of a validated frailty measure into a provincial ICU clinical information system, we describe the population-based prevalence and outcomes of frailty in patients admitted to ICUs.

METHODS

Retrospective cohort study of adult admissions to 17 ICUs. Data were captured using eCritical Alberta. A Clinical Frailty Scale (CFS) score assigned at ICU admission was used to define the exposure (CFS score ≥ 5). Primary outcome was hospital mortality. Secondary outcomes were ICU and hospital stay, and receipt of organ support.

RESULTS

Fifteen thousand two hundred and thirty-eight patients (81%) were assigned a CFS score at ICU admission. Of these, 28% (95% confidence interval [CI], 27 to 28) were frail. Prevalence of frailty was 9-43% across ICUs. Frail patients were older [mean (standard deviation) 63 (15) vs 56 (17) yr; P < 0.001], more likely to be male (54% vs 46% female; P < 0.001), and had higher APACHE II scores [22 (8) vs 17 (8); P < 0.001] compared with non-frail patients. Frail patients received less mechanical ventilation (62% vs 68%; P < 0.001) and vasoactive therapy (24% vs 57%; P < 0.001), but more non-invasive ventilation (22% vs 9%; P < 0.001). Frail patients had higher hospital mortality (23% vs 9%; adjusted odds ratio, 1.80; 95% CI, 1.64 to 2.05, along with longer ICU stay (median [interquartile range] 4 [2-8] vs 3 [2-6] days; P < 0.001), and longer hospital stay (16 [8-36] vs 10 [5-20] days; P < 0.001) compared with non-frail patients.

CONCLUSION

A validated measure of frailty can be implemented at the population level in ICU. Frailty is common in ICU patients and has implications for health service use and clinical outcomes.

Fifteen years of progress in understanding frailty and health in aging

The notion of frailty has evolved for more than 15 years. Although there is no consensus definition, frailty reflects a state of increased vulnerability to adverse health outcomes for individuals of the same chronological age. Two commonly used clinical tools, the frailty index and the frailty phenotype, both measure health-related deficits. The frailty index is a ratio of the number of deficits that an individual has accumulated divided by all deficits measured, whereas the phenotype specifies frailty as represented by poor performance in three of five criteria (i.e., weight loss, exhaustion, weakness, slowness, lack of activity). From human studies, animal models of both approaches have been developed and are beginning to shed light on mechanisms underlying frailty, the influence of frailty on disease expression, and new interventions to attenuate frailty. Currently, back-translation to humans is occurring. As we start to understand subcellular mechanisms involved in damage and repair as well as their response to treatment, we will begin to understand the molecular basis of aging and, thus, of frailty.