472 A PILOT COLORECTAL AND GERIATRIC MEDICINE (CGM) CLINIC FOR OLDER, FRAIL PATIENTS REFERRED VIA A 2 WEEK WAIT PATHWAY

2021 ◽  
Vol 50 (Supplement_2) ◽  
pp. ii8-ii13
Author(s):  
M Thomas ◽  
K Cookson ◽  
R Clark ◽  
L Pearce ◽  
J Fox ◽  
...  
Keyword(s):  
Virtual Colonoscopy ◽  
Geriatric Medicine ◽  
Clinical Frailty Scale ◽  
Specialist Nurse ◽  
Telephone Consultation ◽  
Frail Patients ◽  
Advance Care ◽  
Holistic Assessment ◽  
Endoscopic Investigation ◽  
Prompt Diagnosis

Abstract Introduction The two week wait (2ww) colorectal referral pathway was introduced to expedite referrals where cancer is suspected, facilitating prompt diagnosis +/− intervention. Older frail patients are referred via this 2ww pathway even when invasive testing and intervention may not be appropriate. These patients may benefit more from holistic assessment than a universally surgical approach. A Colorectal and Geriatric Medicine (CGM) 2ww referral clinic was piloted, delivered by an urgent referral colorectal specialist nurse and an advanced clinical practitioner in geriatric medicine. Method Patients >65 years with a Clinical Frailty Scale (CFS) score of 5 or more at referral were directed to the CGM clinic. A telephone consultation was undertaken, incorporating both 2ww assessment and aspects of comprehensive geriatric assessment. Results 42-patients were reviewed in the clinic. Mean age was 86.1 years and mean CFS 6. 12-patients underwent CT, and 2 CT virtual colonoscopy. No patients underwent endoscopic investigation and 28-patients declined any investigation. Of those who underwent investigation, no cancers were identified. 1 patient was referred on for endosocpic mucosal resection of polyps. 5-patients had severe diverticular disease, which accounted for their symptoms. Medication recommendations were made for 30-patients, some of which led to symptom cessation. Onward referrals were made to a community geriatrician, diabetes and continence teams, and palliative care specialists. 9-patients were identified as meeting criteria for advance care planning. This was commenced during the consultation and communicated back to the referring clinician for further action. Conclusion Older, frail patients are often not able, nor wish to undergo, invasive investigations but should not be disadvantaged or delayed in their pathway. Further work is needed to determine the most appropriate referral pathway for this group of patients. Holistic assessment that leads to improvement in symptoms and future planning may not be achievable through a solely surgical assessment.

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

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.

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

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

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

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.

scholarly journals Why do frail patients with chronic heart failure die and become hospitalised?

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
S Sze ◽  
P Pellicori ◽  
J Zhang ◽  
J Weston ◽  
A.L Clark
Keyword(s):  
Heart Failure ◽  
Cause Of Death ◽  
Hospital Admissions ◽  
Average Length ◽  
Significant Proportion ◽  
Length Of Hospital Stay ◽  
Clinical Frailty Scale ◽  
Frail Patients ◽  
Increased Risk

Abstract Background Frailty is common in patients with heart failure (HF) and is associated with increased morbidity and mortality. A better understanding of the causes of hospitalisations and death in frail patients might help to tailor interventional strategies for these at-risk patients. Purpose We studied the cause of death and hospitalisations in ambulatory patients with HF and frailty. Methods We assessed frailty using the clinical frailty scale (CFS) in consecutive HF patients attending a routine follow-up visit. Those with CFS ≥5 were classified as frail. Mortality and hospitalisations were ascertained from medical records (updated systematically using an NHS electronic database), discharge letters, autopsy reports and death certificates. We studied the primary cause of death and hospitalisations within one year of enrolment. Results 467 patients (67% male, median (IQR) age 76 (69–82) years, median (IQR) NT-proBNP 1156 (469–2463) ng/L) were enrolled. 206 (44%) patients were frail. Frail patients were more likely to not receive or receive suboptimal doses of ACEi/ARB and Beta-blockers; while non-frail patients were more likely to be treated with optimal doses. At 1-year follow up, there were 56 deaths and 322 hospitalisations, of which 46 (82%) and 215 (67%) occurred in frail patients. Frailty was associated with an increased risk of all-cause mortality (HR (95% CI): 4.27 (2.60–7.01)) and combined mortality/ hospitalisation (HR (95% CI): 2.85 (2.14–3.80)), all p<0.001. 57% (n=26) of frail patients died of cardiovascular causes (of which 58% were due to HF progression); although deaths due to non-cardiovascular causes (43%, n=20), especially severe infections, were also common (26%, n=12). (Figure 1) The proportion of frail patients who had non-elective hospital admissions within 1 year was more than double that of non-frail patients (46% (n=96) vs 21% (n=54); p<0.001). Compared to non-frail patients, frail patients had more recurrent (≥2) hospitalisations (28% (n=59) vs 9% (n=24); p<0.001) but median (IQR) average length of hospital stay was not significantly different (frail: 6 (4–11) vs non-frail: 6 (2–12) days, p=0.50). A large proportion of hospitalisations (64%, n=137) in frail patients were due to non-cardiovascular causes (of which 34%, 30% and 20% were due to infections, falls and comorbidities respectively). Of cardiovascular hospitalisations (36%, n=78), the majority were due to decompensated HF (67%, n=46). (Figure 1) Conclusion Frailty is common in patients with HF and is associated with an increased risk of mortality and recurrent hospitalisations. A significant proportion suffered non-cardiovascular deaths and hospitalisations. This implies that interventions targeted at HF alone can only have limited impact on outcomes in frail patients. Figure 1 Funding Acknowledgement Type of funding source: None

scholarly journals Characteristics and Outcomes of Frail Patients with COVID-19 Admitted to ICU: An Individual Patient Data Meta-Analysis

2021 ◽  
Author(s):  
Ashwin Subramaniam ◽  
Christopher Anstey ◽  
J Randall Curtis ◽  
Sushma Ashwin ◽  
Mallikarjuna PONNAPA REDDY ◽  
...  
Keyword(s):  
Hospital Mortality ◽  
Clinical Decision Making ◽  
Individual Patient Data ◽  
Meta Analysis ◽  
Multivariable Analysis ◽  
Patient Data ◽  
Clinical Frailty Scale ◽  
Risk Of Death ◽  
Frail Patients ◽  
Bed Days

Abstract Purpose: Frailty is often used in clinical decision-making for patients with COVID-19, yet studies have found variable influence of frailty on outcomes in those admitted to the intensive care unit (ICU). In this individual patient data meta-analysis, we evaluated the characteristics, and outcomes of frail patients admitted to ICU with COVID-19.Methods: We contacted the corresponding authors of sixteen eligible studies published between December 1st 2019 and February 28th 2021 reporting the clinical frailty scale (CFS) in patients with confirmed COVID-19 admitted to ICU. Individual patient data was obtained from 7 studies. We classified patients as non-frail (CFS=1-4) or frail (CFS=5-8). The primary outcome was hospital mortality. We also compared the use of mechanical ventilation (MV) and the proportion of ICU bed-days between frailty categories. Results: Of the 2001 patients admitted to ICU, 388 (19.4%) were frail. Increasing age and sequential organ failure assessment (SOFA) score, CFS ≥4, use of MV, vasopressors, renal replacement therapy and hyperlactatemia were risk factors for death in a multivariable analysis. Hospital mortality was higher in frail patients (65.2% vs. 41.8%; p<0.001), with adjusted mortality increasing with a rising CFS score beyond 3. Younger and non-frail patients were more likely to receive MV. Frail patients spent less time on MV (median days [IQR] 9 [5-16] vs. 11 [6-18]; p=0.012) and accounted for only 12.3% of total ICU bed-days. Conclusion: Frail patients with COVID-19 were commonly admitted to ICU and had greater hospital mortality but spent relatively fewer days in ICU when compared with non-frail patients. Frail patients receiving MV were at greater risk of death than non-frail patients. Systematic review registration: Registration protocol in PROSPERO (CRD42020224255).

scholarly journals Age Alone is not Adequate to Determine Healthcare Resource Allocation during the COVID-19 Pandemic

2020 ◽  
Vol 23 (1) ◽  
pp. 152-154 ◽  
Author(s):  
Manuel Montero-Odasso ◽  
David B. Hogan ◽  
Robert Lam ◽  
Kenneth Madden ◽  
Christopher MacKnight ◽  
...  
Keyword(s):  
Older Adults ◽  
Health Care ◽  
Resource Allocation ◽  
Critical Care ◽  
Critical Care Unit ◽  
Geriatric Medicine ◽  
Well Being ◽  
Health Care Resource ◽  
Clinical Frailty Scale ◽  
Sole Criterion

Background The Canadian Geriatrics Society (CGS) fosters the health and well-being of older Canadians and older adults worldwide. Although severe COVID-19 illness and significant mortality occur across the lifespan, the fatality rate increases with age, especially for people over 65 years of age. The dichotomization of COVID-19 patients by age has been proposed as a way to decide who will receive intensive care admission when critical care unit beds or ventilators are limited. We provide perspectives and evidence why alternatives approaches should be used Methods   Practitioners and researchers in geriatric medicine and gerontology have led in the development of alternative approaches to using chronological age as the sole criterion for allocating medical resources. Evidence and ethical based recommendations are provided. Results Age alone should not drive decisions for health-care resource allocation during the COVID-19 pandemic. Decisions on health-care resource allocation should take into consideration the preferences of the patient and their goals of care, as well as patient factors like the Clinical Frailty Scale score based on their status two weeks before the onset of symptoms. Conclusions Age alone does not accurately capture the variability of functional capacities and physiological reserve seen in older adults. A threshold of 5 or greater on the Clinical Frailty Scale is recommended if this scale is utilized in helping to decide on access to limited health-care resources such as admission to a critical care unit and/or intubation during the COVID-19 pandemic.

scholarly journals 261 Sleep and Frailty: Examining the Effects of Frailty on Sleep Disturbance in Hospitalised Older Adults

2019 ◽  
Vol 48 (Supplement_3) ◽  
pp. iii1-iii16
Author(s):  
Helen Mannion ◽  
Rónán O'Caoimh
Keyword(s):  
Older Adults ◽  
Sleep Quality ◽  
Sleep Disturbance ◽  
Cognitive Status ◽  
University Hospital ◽  
Charlson Comorbidity Index Score ◽  
Night Time ◽  
Clinical Frailty Scale ◽  
Prolonged Length ◽  
Frail Patients

Abstract Background Sleep disturbance is common in hospital, potentially resulting in poor clinical outcomes. Frailty is similarly prevalent and associated with multiple adverse events. Despite this, little is known about the interaction between frailty and sleep among older hospital inpatients. Methods Consecutive, non-critically ill patients aged ≥70, admitted medically through a large university hospital emergency department (ED) during the preceding 24 hours, were evaluated with measures assessing overnight sleep quality (Richards Campbell Sleep Questionnaire/RCSQ), baseline sleep (Pittsburgh Sleep Quality Index/PSQI) and insomnia (Insomnia Severity Index/ISI). Additional variables included medications, frailty (PRISMA-7 scores ≥3 and Clinical Frailty Scale/CFS scores ≥5), functional and cognitive status, and night-time noise levels. Patients were reassessed 48 hours later. Results Over four weeks, 152 patients, mean age 80 (±6.8) years were included; 61% were male (n=92). In all, 43% were frail (mean CFS score 4.23±1.6), median PRISMA-7 score 4±4; a further 24% were pre-frail. The median Charlson Comorbidity Index score was 6±2. The majority, 72% (110/152), reported impaired baseline sleep quality (PSQI ≥5) and 13% (20/152) had clinical insomnia (ISI ≥15). The median time spent in ED was 23±13 hours, median duration asleep was only one hour (range 0-8). After adjusting for possible confounders, frailty status was significantly associated with lower PSQI (p<0.001) but not ISI (p=0.07) and RCSQ (p=0.07) scores. Frail patients were twice as likely to report poor baseline sleep OR 2, (95% CI:1.3-3.2). Baseline and overnight sleep disturbance were not associated with prolonged length of stay (LOS) or 30-day readmission rates. Conclusion The prevalence of sleep disturbance and clinical insomnia among older adults admitted through ED is high and overnight sleep quality low, although these did not impact on LOS or 30-day re-admission rates. Frail patients reported significantly poorer baseline sleep but did not have higher rates of insomnia or experience worse overnight sleep.

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