Incorporating the Rockwood Clinical Frailty Scale into the admission clerking for patients admitted to the oncology ward

Abstract There are over 3 million people in sub-Saharan Africa (SSA) aged 50 and over living with HIV. HIV and combined antiretroviral therapy (cART) exposure may accelerate the ageing in this population, and thus increase the prevalence of premature frailty. There is a paucity of data on the prevalence of frailty in an older HIV + population in SSA and screening and diagnostic tools to identify frailty in SSA. Patients aged ≥ 50 were recruited from a free Government HIV clinic in Tanzania. Frailty assessments were completed, using 3 diagnostic and screening tools: the Fried frailty phenotype (FFP), Clinical Frailty Scale (CFS) and Brief Frailty Instrument for Tanzania (B-FIT 2). The 145 patients recruited had a mean CD4 + of 494.84 cells/µL, 99.3% were receiving cART and 72.6% were virally suppressed. The prevalence of frailty by FFP was 2.758%. FFP frailty was significantly associated with female gender (p = 0.006), marital status (p = 0.007) and age (p = 0.038). Weight loss was the most common FFP domain failure. The prevalence of frailty using the B-FIT 2 and the CFS was 0.68%. The B-FIT 2 correlated with BMI (r = − 0.467, p = 0.0001) and CD4 count in females (r = − 0.244, p = 0.02). There is an absence of frailty in this population, as compared to other clinical studies. This may be due to the high standard of HIV care at this Government clinic. Undernutrition may be an important contributor to frailty. It is unclear which tool is most accurate for detecting the prevalence of frailty in this setting as levels of correlation are low.

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

Critical Care ◽

10.1186/s13054-021-03510-y ◽

2021 ◽

Vol 25 (1) ◽

Author(s):

William Beaubien-Souligny ◽

Alan Yang ◽

Gerald Lebovic ◽

Ron Wald ◽

Sean M. Bagshaw

Keyword(s):

Acute Kidney Injury ◽

Critically Ill ◽

Critically Ill Patients ◽

Multivariable Analysis ◽

Kidney Injury ◽

Multivariable Logistic Regression Analysis ◽

Clinical Frailty Scale ◽

Factors Associated ◽

Frailty Status ◽

Physiological Variables

Abstract Background Frailty status among critically ill patients with acute kidney injury (AKI) is not well described despite its importance for prognostication and informed decision-making on life-sustaining therapies. In this study, we aim to describe the epidemiology of frailty in a cohort of older critically ill patients with severe AKI, the outcomes of patients with pre-existing frailty before AKI and the factors associated with a worsening frailty status among survivors. Methods This was a secondary analysis of a prospective multicentre observational study that enrolled older (age > 65 years) critically ill patients with AKI. The clinical frailty scale (CFS) score was captured at baseline, at 6 months and at 12 months among survivors. Frailty was defined as a CFS score of ≥ 5. Demographic, clinical and physiological variables associated with frailty as baseline were described. Multivariable Cox proportional hazard models were constructed to describe the association between frailty and 90-day mortality. Demographic and clinical factors associated with worsening frailty status at 6 months and 12 months were described using multivariable logistic regression analysis and multistate models. Results Among the 462 patients in our cohort, median (IQR) baseline CFS score was 4 (3–5), with 141 (31%) patients considered frail. Pre-existing frailty was associated with greater hazard of 90-day mortality (59% (n = 83) for frail vs. 31% (n = 100) for non-frail; adjusted hazards ratio [HR] 1.49; 95% CI 1.11–2.01, p = 0.008). At 6 months, 68 patients (28% of survivors) were frail. Of these, 57% (n = 39) were not classified as frail at baseline. Between 6 and 12 months of follow-up, 9 (4% of survivors) patients transitioned from a frail to a not frail status while 10 (4% of survivors) patients became frail and 11 (5% of survivors) patients died. In multivariable analysis, age was independently associated with worsening CFS score from baseline to 6 months (adjusted odds ratio [OR] 1.08; 95% CI 1.03–1.13, p = 0.003). Conclusions Pre-existing frailty is an independent risk factor for mortality among older critically ill patients with severe AKI. A substantial proportion of survivors experience declining function and worsened frailty status within one year.

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Bedside Ultrasound Measures of Muscle Mass and Frailty Measures in Community-Dwelling Older Adults

Innovation in Aging ◽

10.1093/geroni/igaa057.861 ◽

2020 ◽

Vol 4 (Supplement_1) ◽

pp. 269-269

Author(s):

Kenneth Madden ◽

Boris Feldman ◽

Shane Arishenkoff ◽

Graydon Meneilly

Keyword(s):

Older Adults ◽

Muscle Mass ◽

Frailty Index ◽

Geriatric Medicine ◽

Muscle Thickness ◽

Vancouver General Hospital ◽

Community Dwelling ◽

Point Of Care Ultrasound ◽

Clinical Frailty Scale ◽

Community Dwelling Older Adults

Abstract The age-associated loss of muscle mass and strength in older adults is called sarcopenia, and it is associated with increased rates of falls, fractures, hospitalizations and death. Sarcopenia is one of the most common physical etiologies for increased frailty in older adults, and some recent work has suggested the use of Point-of care ultrasound (PoCUS) measures as a potential measure of muscle mass. The objective of this study was to examine the association of PoCUS measures of muscle thickness (MT) with measures of frailty in community-dwelling older adults. We recruited 150 older adults (age >= 65; mean age 80.0±0.5 years, 66 women, 84 men) sequentially from 5 geriatric medicine clinics (Vancouver General Hospital). We measured lean muscle mass (LMM, by bioimpedance assay) and an ultrasonic measure of muscle quantity (MT, vastus medialis muscle thickness) in all subjects, as well as two outcome measures of frailty (FFI, Fried Frailty Index; RCFS, Rockwood Clinical Frailty Scale). In our models, MT showed an inverse correlation with the FFI (Standardized β=-0.2320±0.107, p=0.032) but no significant correlation with the RCFS (Standardized β = -0.025±0.086, p=0.776). LMM showed no significant association with either FFI (Standardized β=-0.232±0.120, p=0.055) or RCFS (Standardized β = -0.043±0.119, p=0.719). Our findings indicate that PoCUS measures show potential as a way to screen for physical manifestations of frailty and might be superior to other bedside methods such as bioimpedance assay. However, PoCUS measures of muscle thickness will likely miss patients showing frailty in the much broader context captured by the RCFS.

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Effect of frailty on treatment, hospitalisation and death in patients with chronic heart failure

Clinical Research in Cardiology ◽

10.1007/s00392-020-01792-w ◽

2021 ◽

Author(s):

S. Sze ◽

P. Pellicori ◽

J. Zhang ◽

J. Weston ◽

I. B. Squire ◽

...

Keyword(s):

Heart Failure ◽

Chronic Heart Failure ◽

Clinical Frailty Scale ◽

Mineralocorticoid Receptor Antagonist ◽

Reduced Ejection Fraction ◽

Frail Patients ◽

History Of ◽

Poor Outcomes ◽

To Receive

Abstract Background Frailty is common in patients with chronic heart failure (CHF) and is associated with poor outcomes. The natural history of frail patients with CHF is unknown. Methods Frailty was assessed using the clinical frailty scale (CFS) in 467 consecutive patients with CHF (67% male, median age 76 years, median NT-proBNP 1156 ng/L) attending a routine follow-up visit. Those with CFS > 4 were classified as frail. We investigated the relation between frailty and treatments, hospitalisation and death in patients with CHF. Results 206 patients (44%) were frail. Of 291 patients with HF with reduced ejection fraction (HeFREF), those who were frail (N = 117; 40%) were less likely to receive optimal treatment, with many not receiving a renin–angiotensin–aldosterone system inhibitor (frail: 25% vs. non-frail: 4%), a beta-blocker (16% vs. 8%) or a mineralocorticoid receptor antagonist (50% vs 41%). By 1 year, there were 56 deaths and 322 hospitalisations, of which 25 (45%) and 198 (61%), respectively, were due to non-cardiovascular (non-CV) causes. Most deaths (N = 46, 82%) and hospitalisations (N = 215, 67%) occurred in frail patients. Amongst frail patients, 43% of deaths and 64% of hospitalisations were for non-CV causes; 58% of cardiovascular (CV) deaths were due to advancing HF. Among non-frail patients, 50% of deaths and 57% of hospitalisations were for non-CV causes; all CV deaths were due to advancing HF. Conclusion Frailty in patients with HeFREF is associated with sub-optimal medical treatment. Frail patients are more likely to die or be admitted to hospital, but whether frail or not, many events are non-CV. Graphical abstract

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The impact of frailty on trauma outcomes using the Clinical Frailty Scale

European Journal of Trauma and Emergency Surgery ◽

10.1007/s00068-021-01627-x ◽

2021 ◽

Author(s):

Amari Thompson ◽

Sunil Gida ◽

Yasar Nassif ◽

Carla Hope ◽

Adam Brooks

Keyword(s):

Clinical Frailty Scale ◽

Trauma Outcomes ◽

The Impact

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Clinical pharmacy services in a pediatric hematology/oncology ward of Tikur Anbessa Specialized hospital, Addis Ababa, Ethiopia: Prospective audit and feedback

Pediatric Hematology Oncology Journal ◽

10.1016/j.phoj.2021.04.024 ◽

2020 ◽

Vol 5 (4) ◽

pp. S10

Author(s):

Daniel Hailu ◽

Atalay Mulu Fentie

Keyword(s):

Clinical Pharmacy ◽

Addis Ababa ◽

Audit And Feedback ◽

Pharmacy Services ◽

Prospective Audit ◽

Pediatric Hematology ◽

Specialized Hospital ◽

Tikur Anbessa Specialized Hospital ◽

Oncology Ward ◽

Prospective Audit And Feedback

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160 The Effect of Frailty and COVID-19 Infection on Clinical Outcomes in Older Adults—A Single Centre Retrospective Study

Age and Ageing ◽

10.1093/ageing/afab030.121 ◽

2021 ◽

Vol 50 (Supplement_1) ◽

pp. i12-i42

Author(s):

O Okuwoga ◽

S Mufti

Keyword(s):

Older Patients ◽

Single Centre ◽

Clinical Frailty Scale ◽

Health Records ◽

Frail Patients ◽

Nice Guidance ◽

Data Points ◽

Continued Use ◽

Support Decision Making ◽

Frailty Score

Abstract Introduction It was anticipated that the COVID-19 pandemic would put a strain on our healthcare system, disproportionately affecting older people. NICE guidance recommended using frailty scoring to support decision making around escalation of care. This study aimed to assess frailty, demographics and COVID-19 infection and to investigate how these related to outcomes of patients aged over 65 years admitted to hospital. Methods A single centre retrospective cohort study was carried out by reviewing the electronic health records of all admissions over 65 years. Data points collected included length of stay (LOS), frailty score using the Rockwood Clinical Frailty Scale (CFS) and mortality. Patients were stratified into COVID and non-COVID based on health records and into non-frail (CFS 1–4) and frail (CFS 5–9). Results A total of 257 patients admitted between 30th March and 30th April 2020 were included in the study (mean age 79 years, 43% female). 141 (54.9%) of patients were diagnosed with COVID-19 infection. 120 patients had CFS 1–4 and 136 has CFS 5–9. 1 patient did not have a frailty score due to insufficient information. 68 (26.8%) of all patients died during the admission. The relative risk (RR) of mortality of patients with coronavirus was 6.3 (95% CI 3.1–12.6, p < 0.0001). The RR of mortality for frail patients compared to the non-frail was 2.1 (95% CI 1.3–3.2, p = 0.002). The median LOS for patients with COVID-19 was 5 days, compared to 4 days for patients who did not have coronavirus. Frailty did not predict longer admission, with median LOS of 5 days for both non-frail and frail patients. Conclusion The results demonstrated in this study show that COVID-19 infection and frailty were significantly associated with increased mortality in older patients. This validates the continued use of frailty scoring of older patients on admission to support care planning.

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