Evidence-Based Review and Discussion Points

IntroductionIdiopathic Pulmonary Fibrosis (IPF) patients are older with impaired physiology, and therefore at risk of frailty syndromes including falls, immobility, and toxicity from polypharmacy. Frailty correlates with quality of life,...

Longitudinal assessments of simple frailty tools can help predict outcomes of patients undergoing chimeric antigen receptor T-cell (CAR-T) therapy: A prospective pilot study at Princess Margaret Cancer Centre

Background: Comprehensive pre-anesthetic evaluation is known to play a crucial role in predicting morbidity and mortality in the perioperative and postoperative periods. Frailty is a condition characterized by reduced physiological reserve and resistance to stressors. It results from the accumulation of deficits in multiple organ systems, leading to physiological decline and subsequent changes in pharmacodynamics and pharmacokinetics. In this study, we aimed to evaluate the frailty scores of patients who underwent head and neck surgery. Material and Methods: This retrospective study included patients who underwent head and neck surgery in the otolaryngology operating rooms of Ankara City Hospital over a 2-year period. The mFI-5 (Modified 5-item Frailty Index) and CFS (Clinical Frailty Scale) were used for assessment. Results: A total of 54 patients were included in the study, with an average age of 57.9 ± 14.4 years. The proportion of patients who underwent neck dissection was 51.9%. A moderate correlation was found between the length of hospital stay and the mFI-5 and CFS scores. Similarly, patients who developed postoperative complications and those readmitted within 30 days had higher mFI-5 and CFS scores. While the mFI-5, CFS, and ASA scores showed similar trends, ASA was not statistically significant in predicting postoperative outcomes. Due to the low number of cases and deceased patients, the relationship with mortality could not be determined. Conclusions: Frailty is characterized by increased vulnerability and reduced reserve. As the population ages and life expectancy continues to rise, doctors and patients will increasingly face difficult decisions regarding treatment. This is particularly true for oncological surgery patients. Identifying patients as frail or high-risk can directly impact treatment decisions. The mFI-5 and CFS can be simple and useful tools for predicting perioperative outcomes in early and mid-term head and neck surgery.

Chronic obstructive pulmonary disease (COPD) is closely associated with frailty, and prevention of acute exacerbations is important for disease management. Moreover, COPD patients with frailty experience a higher risk of acute exacerbations. However, the frailty instruments that can better predict acute exacerbations remain unclear. (1) To explore the factors influencing frailty and acute exacerbations in stable COPD patients, and (2) quantify the ability of multidimensional frailty instruments to predict acute exacerbations within 1 year. In this retrospective longitudinal study, stable COPD patients were recruited from the outpatient department of Sichuan Provincial People's Hospital from July 2022 to June 2023. COPD patients reviewed their frailty one year ago and their acute exacerbations within one year using face-to-face interviews with a self-developed frailty questionnaire. Frailty status was assessed using the Frailty Index (FI), frailty questionnaire (FRAIL), and Clinical Frailty Scale (CFS). One-way logistic regression was used to explore the factors influencing frailty and acute exacerbations. Multivariate logistic regression was used to establish a prediction model for acute exacerbations, and the accuracy of the three frailty instruments was compared by measuring the area under the receiver operating characteristic curve (AUC). A total of 120 individuals were included. Frailty incidence estimates using FI, FRAIL, and CFS were 23.3%, 11.7%, and 15.8%, respectively. The three frailty instruments showed consistency in COPD assessments (P<0.05). After adjusting for covariates, frailty reflected by the FI and CFS score remained an independent risk factor for acute exacerbations. The CFS score was the best predictor of acute exacerbations (AUC, 0.764 (0.663-0.866); sensitivity, 57.9%; specificity, 80.0%). Moreover, the combination of CFS plus FRAIL scores was a better predictor of acute exacerbations (AUC, 0.792 (0.693-0.891); sensitivity, 86.3%; specificity, 60.0%). Multidimensional frailty assessments could improve the identification of COPD patients at high risk of acute exacerbations and facilitate targeted interventions to reduce acute exacerbations in these patients.

Background Evidence indicates frailty before intensive care unit (ICU) admission leads to poor outcomes. However, it is unclear whether quality of life (QOL) and activities of daily living (ADL) for survivors of critical illness admitted to the ICU via the emergency department remain consistent or deteriorate in the long-term compared to baseline. This study aimed to evaluate long-term QOL/ADL outcomes in these patients, categorized by the presence or absence of frailty according to Clinical Frailty Scale (CFS) score, as well as explore factors that influence these outcomes.Methods This was a post-hoc analysis of a prospective, multicenter, observational study conducted across Japan. It included survivors aged 65 years or older who were admitted to the ICU through the emergency department. Based on CFS scores, participants were categorized into either the not frail group or the frail group, using a threshold CFS score of < 4. Our primary outcome was patient-centered outcomes (QOL/ADL) measured by the five-level EuroQol five-dimensional questionnaire (EQ-5D-5L) and the Barthel Index six months post-ICU admission, comparing results from baseline. Secondary outcomes included exploration of factors associated with QOL/ADL six months post-ICU admission using multiple linear regression analyses.Results Of 514 candidates, 390 participants responded to the EQ-5D-5L questionnaire, while 237 responded to the Barthel Index. At six months post-admission, mean EQ-5D-5L values declined in both the not frail and frail groups (0.80 to 0.73, p = 0.003 and 0.58 to 0.50, p = 0.002, respectively); Barthel Index scores also declined in both groups (98 to 83, p < 0.001 and 79 to 61, p < 0.001, respectively). Multiple linear regression analysis revealed that baseline frailty (β coefficient, -0.15; 95% CI, − 0.23 to − 0.07; p < 0.001) and pre-admission EQ-5D-5L scores (β coefficient, 0.14; 95% CI, 0.02 to 0.26; p = 0.016) affected EQ-5D-5L scores at six months. Similarly, baseline frailty (β coefficient, -12.3; 95% CI, − 23.9 to − 0.80; p = 0.036) and Barthel Index scores (β coefficient, 0.54; 95% CI, 0.30 to 0.79; p < 0.001) influenced the Barthel Index score at six months.Conclusions Regardless of frailty, older ICU survivors from the emergency department were more likely to experience reduced QOL and ADL six months after ICU admission compared to baseline.

BackgroundSBO is a potentially life-threatening condition that often affects older patients. Frailty, more than age, is expected to play a crucial role in predicting SBO prognosis in this population. This study aims to define the influence of Clinical Frailty Scale (CFS) on mortality and major complications in patients ≥80 years with diagnosis of SBO at the emergency department (ED). MethodsAll patients aged ≥80 years admitted to our ED for SBO from January 2015 to September 2020 were enrolled. Frailty was assessed through the CFS, and then analyzed both as a continuous and a dichotomous variable. The endpoints were in-hospital mortality and major complications. ResultsA total of 424 patients were enrolled. Higher mortality (20.8% vs 8.6%, p<0.001), longer hospital stay (9 [range 5–14] days vs 7 [range 4–12] days, p=0.014), and higher rate of major complications (29.9% vs 17.9%, p=0.004) were associated with CFS ≥7. CFS score and bloodstream infection were the only independent prognostic factors for mortality (OR 1.72 [CI: 1.29–2.29], p<0.001; OR 4.69 [CI: 1.74–12.6], p=0.002, respectively). Furthermore, CFS score, male sex and surgery were predictive factors for major complications (OR 1.41 [CI: 1.13–1.75], p=0.002; OR 1.67 [CI: 1.03–2.71], p=0.038); OR 1.91 [CI: 1.17–3.12], p=0.01; respectively). At multivariate analysis, for every 1-point increase in CFS score, the odds of mortality and the odds of major complications increased 1.72-fold and 1.41-fold, respectively. ConclusionThe increase in CFS is directly associated with an increased risk of mortality and major complications. The presence of severe frailty could effectively predict an increased risk of in-hospital death regardless of the treatment administered. The employment of CFS in elderly patients could help the identification of the need for closer monitoring and proper goals of care.

Introduction Clinical frailty scale (CFS) is used to generate a score ranging from 1 (very fit) to 9 (terminally ill) for people aged ≥65 years. A CFS of ≥7 correlates with a one-year mortality rate of ~50%, making it useful for identifying individuals potentially approaching last year of life. NICE recommend this patient group are offered Advance care planning (ACP). ACP is paramount to ensuring individuals receive high-quality, personalised end of life care. We aimed to investigate CFS documentation and frequency of ACP discussions following educational interventions. Methods We performed a retrospective analysis of all inpatients admitted to an Elderly Medicine department on a given day. Data for demographics, documented CFS score, and ACP discussions was collected. CFS scores were recalculated to assess accuracy. Following formal education sessions on CFS documentation and ACP delivered to the MDT, data was recollected. Subsequently, CFS scores were recorded within electronic ‘flowsheets’ to ensure scores could automatically populate future clinical notes and be extracted for research purposes. Results The initial sample included 61 patients with 52 in the repeat sample. 36% of patients had CFS recorded in the initial sample compared to 77% in the repeat. In the initial sample, there was an 18.1% difference in documented and recalculated CFS for patients with a CFS ≥ 7 compared to 7.7% in the repeat, showing improved identification of advanced frailty. In the initial cohort, 18% had pre-existing ACP and 16.4% had inpatient ACP discussions, compared to 21.2% in the repeat with pre-existing ACP and 15.4% having inpatient ACP discussions; demonstrating minimal difference. Conclusions CFS documentation improved highlighting effectiveness of education involving the whole MDT to better identify frailty within the inpatient setting. Despite this, ACP discussion rates remained low. Potential barriers include time–pressure and lack of confidence approaching ACP demonstrating a need for further awareness and training.

The primary aim of this study was to investigate how the Clinical Frailty Scale (CFS) associates with survival of patients with diabetes after lower extremity amputation (LEA). This retrospective cohort study included patients with diabetes undergoing nontraumatic LEA at Tampere University Hospital during 2007-2020. Kaplan-Meier and Cox regression analyses were performed to evaluate the effect of CFS on overall survival (OS), amputation-free survival (AFS) and leg salvage (LS). A total of 1043 patients with mean age 71.0years were included. Compared to patients with low CFS (1, 2), scores 3-4 and 5-9 were associated with reduced OS (HR 1.821, p<0.001; HR 4.585, p<0.001), AFS (HR 1.575, p<0.001; HR 4.031, p<0.001) and LS (HR 1.435, p=0.049; HR 2.478, p<0.001). The multivariable Cox regression analysis showed that CFS remained a significant predictor of OS, AFS and LS. This study demonstrates a high prevalence of frailty among patients with diabetes undergoing LEA, suggesting that frailty assessment should be integrated into clinical decision-making for this patient population. The CFS score appears to be a promising tool for evaluating patients facing amputation to enhance survival rates.

With population aging, the number of frail patients with pancreatic cancer has increased. The Clinical Frailty Scale (CFS) is a simple and validated tool to assess frailty, and higher scores predict worse clinical outcomes after cardiovascular surgery. In this retrospective study, we aimed to examine the association of preoperative frailty with prognosis after resection for pancreatic cancer. We retrospectively analyzed data from 142 consecutive patients undergoing resection for pancreatic cancer between April 2010 and December 2018. We used the CFS: 1 (very fit) to 9 (terminally ill) to assess frailty and examined associations of the CFS scores with recurrence-free survival (RFS), cancer-specific survival (CSS), and overall survival (OS). Multivariable Cox proportional hazards models were used to calculate hazard ratios (HRs), controlling for potential confounders. Of the 142 patients, 113 (80%) had CFS scores of ≤ 3, 13 (9.2%) scores of 4, and 16 (11%) scores of ≥ 5. Scores of ≥ 5 on the CFS were associated with worse CSS (univariable HR: 2.62, 95% confidence interval [CI]: 1.19-5.18, P = 0.019; multivariable HR: 2.49, 95% CI 1.05-5.34, P = 0.039) and OS (univariable HR: 2.42, 95% CI 1.19-4.46, P = 0.016; multivariable HR: 2.25, 95% CI 1.05-4.43, P = 0.038). The association between CFS scores and RFS was not significant in multivariable analysis (univariable HR: 2.11, 95% CI 1.08-3.79, P = 0.030; multivariable HR: 1.47, 95% CI 0.71-2.83, P = 0.29). Higher scores on the CFS are associated with worse CSS and OS after resection for pancreatic cancer. Preoperative measurement of frailty may improve risk assessment among patients with pancreatic cancer.

Frailty is a physical condition characterized by increased vulnerability to external stressors. This study investigated the impact of premorbid frailty, as measured by the Clinical Frailty Scale (CFS), on neurological prognosis in patients with out-of-hospital cardiac arrest (OHCA). This is a single-center retrospective study. Data from 2006 to 2020 were analyzed for 595 adult OHCA patients admitted to the intensive care unit of National Taiwan University Hospital following resuscitation. Variables included demographics, medical history, resuscitation details, post-resuscitation data, and frailty assessments based on CFS. The primary outcome was favorable neurological performance, defined as a cerebral performance category (CPC) score of 2 or less at discharge. In total, 523 of the 595 patients were included in the analysis. Among these, 224 survived, and 173 exhibited favorable neurological outcomes. Patients with favorable outcomes had significantly lower CFS scores than those with poor outcomes (3.2 ± 1.5 vs. 4.5 ± 1.8, p < 0.0001). The proportion of favorable neurological outcomes declined as CFS scores increased. Multivariate logistic regression analysis identified several factors independently associated with worse neurological outcomes: CFS >4 (odds ratio (OR): 0.301, 95% confidence interval (CI): 0.163-0.540), age >70 years (OR: 0.969, 95% CI: 0.953-0.986), history of malignancy (OR: 0.421, 95% CI: 0.209-0.813), epinephrine >2 mg during resuscitation (OR: 0.776, 95% CI: 0.712-0.840), and arterial blood gas pH <7.1 (OR: 28.396, 95% CI: 6.487-129.350). The model demonstrated good performance, with an area under the curve (AUC) value of 0.853. No significant relationships were observed between CFS and other variables. CFS values ≤4 were independently associated with favorable neurological outcomes following OHCA.

Background/AimsFrailty increases the risks of in-hospital adverse events such as delirium, falls, and functional decline in older adults. We assessed the feasibility and clinical relevance of frailty status in Korean older inpatients using the Clinical Frailty Scale (CFS) and Korean version of the Fatigue, Resistance, Ambulation, Illnesses, & Loss of Weight scale (K-FRAIL) questionnaires.MethodsFrailty status was measured using the Korean-translated version of the CFS and K-FRAIL questionnaire within 3 days from admission in 144 consecutive patients aged 60 years or older. The correlation between CFS and K-FRAIL score was assessed. The criterion validity of CFS was assessed using receiver operating characteristic analysis. As outcomes, delirium, bedsore, length of stay (LOS), in-hospital mortality, and unplanned 30-day readmission were measured by reviewing medical records.ResultsThe mean age of the study population was 70.1 years (range, 60 to 91), and 75 (52.1%) were men. By linear regression analysis, CFS and K-FRAIL were positively correlated (B = 0.72, p < 0.001). A CFS cutoff of ≥ 5 maximized sensitivity + specificity to classify frailty using K-FRAIL as a reference (C-index = 0.893). Higher frailty burden by both CFS and K-FRAIL was associated with higher LOS and bedsores. Unplanned readmission and in-hospital mortality were associated with higher CFS score but not with K-FRAIL score, after adjusting for age, gender, polypharmacy, and multimorbidity.ConclusionsFrailty status by CFS was associated with LOS, bedsores, unplanned readmission, and in-hospital mortality. CFS can be used to screen high-risk patients who may benefit from geriatric interventions and discharge planning in acutely hospitalized older adults.

Elderly patients (≥ 75years) often require resuscitation room (RR) care in the emergency department (ED), yet decisions regarding intensive care unit (ICU) admission remain complex. Assessment of quality of life and frailty is necessary to determine the level of care required for elderly patients. The Clinical Frailty Scale (CFS) is a validated tool for assessing frailty and predicting mortality, but its role in ICU triage remains unclear. The aim of this study was to compare the CFS of patients admitted to the ICU with those admitted to the general inpatient unit (GIU) after receiving initial intensive care. This was a retrospective, single-center study including patients aged ≥ 75years admitted to the ED RR from November 1, 2023, to March 31, 2024. The primary outcome was the comparison of CFS between ICU and GIU admissions after RR management. Secondary outcomes included predictive performance of CFS for ICU admission and in-hospital mortality. Of the 392 patients enrolled, 170 (43%) were admitted to the ICU and 222 (57%) to the GIU. The median CFS was 3 (2-4) in ICU-admitted patients and 4 (3-5) in GIU-admitted patients (p < 0.001). In-hospital mortality rate was 30/170 (18%) in the ICU-admitted group and 35/222 (16%) in the GIU-admitted group (p = 0.72). CFS predictive value for ICU admission had an area under the curve of 0.68 (95% confidence interval (95%CI): 0.63-0.73) and for in-hospital mortality of 0.62 (95%CI: 0.55-0.69). In elderly patients admitted to the RR, CFS values differed between those admitted to ICU and those admitted to GIU. However, the discriminative performance of CFS for hospital orientation and in-hospital mortality was limited. These findings suggest that frailty assessment may contribute to the overall evaluation of elderly patients in the ED RR but should be interpreted in conjunction with acute severity scores and clinical judgment.

As the older population increases, more older people are exposed to trauma. Frailty can be used to highlight patients at risk of a poorer outcome. The objectives of this study were to compare 2 frailty measures with regard to concordance, floor and ceiling effects, and construct and predictive validity and to determine which is more valid and clinically applicable in a critically ill trauma population. This was a prospective observational study. Patients were included if admitted to an intensive care unit (ICU) under a trauma medical unit and ≥ 50 years old. Frailty was determined using 2 frailty measures, the Frailty Phenotype (FP) and Clinical Frailty Scale (CFS). One hundred people were enrolled; their mean age was 69.2 years (SD=10.4) and 81% had major trauma (as determined with the Injury Severity Score). Frailty was identified with the FP in 22 participants and with the CFS in 13 participants. The 2 frailty measures had an excellent correlation (Spearman rank correlation coefficient=0.77; 95% confidence interval=0.66-0.85). Both the FP and the CFS had large floor effects but no ceiling effects. The FP and CFS showed construct validity, with frailty being significantly associated with increasing age, requiring an aid to mobilize, and more falls and hospital admissions. Frailty on the FP was predictive of ICU and hospital mortality, whereas frailty on the CFS was predictive of hospital mortality. The limitations of this study include the use of a single site, small sample size, and collection of frailty measures retrospectively. Measuring frailty in a trauma ICU population was feasible, with excellent correlation between the 2 frailty measures. Both showed aspects of construct and predictive validity; however, the FP identified frailty in more participants and was associated with more comorbidities and higher mortality at ICU discharge. Therefore, the FP might be more clinically relevant in this population.

BackgroundCoronavirus disease 2019 (COVID‐19) is associated with excess mortality after hospital discharge. Identification of patients at increased risk of death following hospital discharge is needed to guide clinical monitoring and early intervention. Herein, we aimed to identify predictors of early vs. late mortality in COVID‐19 patients.MethodsA total of 471 patients with polymerase chain reaction‐confirmed COVID‐19 were followed up for 9 months [median (inter‐quartile range) of follow‐up time: 271 (14) days] after hospital admission. COVID‐19‐related signs and symptoms, laboratory features, co‐morbidities, Coronavirus Clinical Characterisation Consortium (4C) mortality and Clinical Frailty Scale (CFS) scores were analysed by logistic regression for association with early (28 day) vs. late mortality. Receiver operating characteristic (ROC) analysis was used to determine the discriminative value of 4C and CFS scores for early vs. late mortality.ResultsA total of 120 patients died within 28 days from hospital admission. Of the remaining 351 patients, 41 died within the next 8 months. Respiratory failure, systemic inflammation, and renal impairment were associated with early mortality, while active cancer and dementia were associated with late mortality, after adjustment for age and sex. 4C mortality score and CFS were associated with both early [odds ratio (OR) (95% confidence interval—CI): 4C: 1.34 (1.25–1.45); CFS: 1.49 (1.33–1.66)] and late [OR (95% CI): 4C: 1.23 (1.12–1.36); CFS: 2.04 (1.62–2.56)] mortality. After adjustment for CFS, the association between 4C and late mortality was lost. By ROC analysis, 4C mortality score was superior to CFS for 28 day mortality [area under the curve (AUC) (95% CI): 0.779 (0.732–0.825) vs. 0.723 (0.673–0.773), respectively; P = 0.039]. In contrast, CFS had higher predictive value for late mortality compared with 4C mortality score [AUC (95% CI): 0.830 (0.776–0.883) vs. 0.724 (0.650–0.798), respectively; P = 0.007].ConclusionsIn our cohort, late mortality in COVID‐19 patients is more strongly associated with premorbid clinical frailty than with severity of the acute infection phase.

Background Although interest in frailty has expanded among cardiology experts over the past 2 decades, its integration, as part of cardiovascular disease management, is still lacking, above all in the acute cardiac care setting. The Clinical Frailty Scale (CFS) is a brief guided tool to assess frailty in hospital settings without specialist equipment. Purpose Our objective was to test the performance of the CFS in an older, unselected population, admitted to an Intensive Cardiac Care Unit (ICCU) during the year 2019. Methods The study sample included 431 patients ≥65 years old, admitted to an ICCU of a tertiary cardiac center in Italy. The CFS ranged from “very fit: 1” to “terminally ill: 9”, but it was considered present at a score ≥5. Our primary endpoint was defined by a combination of severe complications requiring critical care and in-hospital death. The data were collected from the hospital discharge summary and the electronic chart records. Results 158 patients (36.7%) were frail. These individuals had greater comorbidity and higher in-hospital mortality (Table 1). After a multivariable logistic regression analysis, 4 predictors were identified: signs of congestive heart failure (OR: 8.51, 95% Confidence Interval-CI: 4.63–14.6; p&amp;lt;0,001), systolic blood pressure (OR per 1 mmHg increasing: 0.98, 95% CI: 0.97–0.99; p&amp;lt;0,001), smoking habit (OR: 0.49, 95% CI: 0.22–1.11; p=0.09) and the CFS ≥5 (OR: 1.86, 95% CI: 1.08–3.23: p=0,026). Conclusions The CFS is a simple guided frailty tool that may enhance outcome prediction in the acute cardiac care setting. These findings merit evaluation in larger cohorts of unselected patients. Funding Acknowledgement Type of funding sources: None.