scholarly journals Management of Frailty and its Challenges in Geriatric Patients on General Abdominal Anesthesia.

2021 ◽  
Vol 5 (1) ◽  
pp. 785-790
Author(s):  
Majlinda Naço ◽  
Haxhire Gani ◽  
Monika Belba ◽  
Suzana Mukaj ◽  
Nertila Kodra ◽  
...  
Keyword(s):  
Geriatric Patients ◽  
Strong Predictor ◽  
Frailty Index ◽  
Early Mobilization ◽  
Adverse Outcomes ◽  
Clinical Frailty Scale ◽  
Operative Morbidity ◽  
Operative Care ◽  
Patient Will ◽  
Organ Specific

Introduction: In that material, we are doing to informed for frailty, how we can measure it, surgical outcome and its management from the anesthesiologist. Frailty is a condition of decreased physiological reserves that often increases with increasing age and decided in adverse outcomes. Frailty in elderly surgical patients may be varied from 25,5 -56.1% and is a strong predictor for surgical outcomes. The anesthetist needs to predict how a geriatric patient will tolerate the stress of surgery and to do what is necessary to protect and save elderly lives. In Albania, there are almost 439 000 elderly people in 2021 and suspect to 626 000 in 2051. According to the WHO, 1 in 25 persons performed surgery, so the number of geriatric patients that done surgery will be very high. According to deficits’ in function, mobility, cognition, chronic diseases, and geriatric syndromes we can use the clinical frailty scale, the Edmonton Frailty Scale, or frailty index for calculation of frailty. We need frailty patients to evaluated preoperative risk-classification, intra-operative care, management of general anesthesia, early immobilization as well as treatment of postoperative delirium because frailty increased intra-operative morbidity, increased postoperative complications especially delirium, extends hospitalization, non – home discharge, and mortality. Anesthesiologists would be always aware to prepare the geriatric patients for surgery, to maintain the intra-operative functional reserve of frailty patients, to manage perfect anesthesia, to realized early mobilization, and discharge back home. Conclusion: Many geriatric patients have multi-organ problems. Frailty is a practical, unifying concept in the care of these older people that directs attention away from organ-specific diagnoses towards a more holistic viewpoint of the patient and their medical medicament. All geriatric patients need to screen for frailty.

scholarly journals Using an electronic frailty index to predict adverse outcomes in geriatric COVID-19 patients: data from the Stockholm GeroCovid study

2021 ◽  
Author(s):  
Jonathan K. L. Mak ◽  
Maria Eriksdotter ◽  
Martin Annetorp ◽  
Ralf Kuja-Halkola ◽  
Laura Kananen ◽  
...  
Keyword(s):  
Length Of Stay ◽  
Hospital Mortality ◽  
Cox Regression ◽  
Predictive Accuracy ◽  
Strong Predictor ◽  
Characteristic Curve ◽  
Frailty Index ◽  
Predictive Ability ◽  
Adverse Outcomes ◽  
Clinical Frailty Scale

ABSTRACTBackgroundThe Clinical Frailty Scale (CFS) is a strong predictor for worse outcomes in geriatric COVID-19 patients, but it is less clear whether an electronic frailty index (eFI) constructed from routinely collected electronic health records (EHRs) provides similar predictive value. This study aimed to investigate the predictive ability of an eFI in comparison to other frailty and comorbidity measures, using mortality, readmission, and the length of stay as outcomes in geriatric COVID-19 patients.MethodsWe conducted a retrospective cohort study using EHRs from nine geriatric clinics in Stockholm, Sweden, comprising 3,405 COVID-19 patients (mean age 81.9 years) between 1/3/2020 and 31/10/2021. Frailty was assessed using a 48-item eFI developed for Swedish geriatric patients, the CFS, and Hospital Frailty Risk Score (HFRS). Comorbidity was measured using the Charlson Comorbidity Index (CCI). We analyzed in-hospital mortality and 30-day readmission using logistic regression and area under receiver operating characteristic curve (AUC). 30-day and 6-month mortality were modelled by Cox regression, and the length of stay by linear regression.ResultsControlling for age and sex, a 10% increase in the eFI was associated with higher risks of in-hospital mortality (odds ratio [OR]=2.84; 95% confidence interval=2.31-3.51), 30-day mortality (hazard ratio [HR]=2.30; 1.99-2.65), 6-month mortality (HR=2.33; 2.07-2.62), 30-day readmission (OR=1.34; 1.06-1.68), and longer length of stay (β=2.28; 1.90-2.66).The CFS, HFRS and CCI similarly predicted these outcomes, but the eFI had the best predictive accuracy for in-hospital mortality (AUC=0.775).ConclusionsAn eFI based on routinely collected EHRs can be applied in identifying high-risk geriatric COVID-19 patients.

scholarly journals Development of an electronic frailty index for hospitalized geriatric patients in Sweden

2021 ◽  
Author(s):  
Jonathan K. L. Mak ◽  
Sara Hagg ◽  
Maria Eriksdotter ◽  
Martin Annetorp ◽  
Ralf Kuja-Halkola ◽  
...  
Keyword(s):  
Length Of Stay ◽  
Hospital Mortality ◽  
Geriatric Patients ◽  
Cox Regression ◽  
Predictive Accuracy ◽  
Characteristic Curve ◽  
Frailty Index ◽  
Laboratory Data ◽  
Adverse Outcomes ◽  
Clinical Frailty Scale

Background: Frailty assessment in the Swedish health system relies on the Clinical Frailty Scale (CFS), but it requires training, in-person evaluation, and is often missing in medical records. We aimed to develop an electronic frailty index (eFI) from routinely collected electronic health records (EHRs) and assess its predictive ability for adverse outcomes in geriatric patients. Methods: EHRs were extracted for 18,225 geriatric patients with unplanned admissions between 1/3/2020 and 17/6/2021 from nine geriatric clinics in Stockholm, Sweden. A 48-item eFI was constructed using diagnostic codes, functioning and other health indicators, and laboratory data. The CFS, Hospital Frailty Risk Score, and Charlson Comorbidity Index were used for comparative assessment of the eFI. We modelled in-hospital mortality and 30-day readmission using logistic regression; 30-day and 6-month mortality using Cox regression; and length of stay using linear regression. Results: 13,188 patients were included in analyses (mean age 83.1 years). A 10% increment in the eFI was associated with higher risks of in-hospital (odds ratio: 5.34; 95% confidence interval: 4.20-6.82), 30-day (hazard ratio [HR]: 3.28; 2.91-3.69), and 6-month mortality (HR: 2.70; 2.52-2.90) adjusted for age and sex. Of the frailty and comorbidity measures, the eFI had the best predictive accuracy for in-hospital mortality, yielding an area under receiver operating characteristic curve of 0.813. Higher eFI also predicted a longer length of stay, but had a rather poor discrimination for 30-day readmission. Conclusions: An EHR-based eFI has good predictive accuracy for adverse outcomes, suggesting that it can be used in risk stratification in geriatric patients.

scholarly journals Drivers of Frailty from Adulthood into Old Age: Results from a 27-Year Longitudinal Population-Based Study in Sweden

2020 ◽  
Vol 75 (10) ◽  
pp. 1943-1950 ◽  
Author(s):  
Emma Raymond ◽  
Chandra A Reynolds ◽  
Anna K Dahl Aslan ◽  
Deborah Finkel ◽  
Malin Ericsson ◽  
...  
Keyword(s):  
Social Support ◽  
Strong Predictor ◽  
Frailty Index ◽  
Overweight And Obesity ◽  
Adverse Outcomes ◽  
Rate Of Change ◽  
Growth Curve Analysis ◽  
Factors Associated ◽  
Age Related ◽  
Time Varying Covariates

Abstract Background Frailty is a strong predictor of adverse outcomes. However, longitudinal drivers of frailty are not well understood. This study aimed at investigating the longitudinal trajectories of a frailty index (FI) from adulthood to late life and identifying the factors associated with the level and rate of change in FI. Methods An age-based latent growth curve analysis was performed in the Swedish Adoption/Twin Study of Aging (N = 1,842; aged 29–102 years) using data from up to 15 measurement waves across 27 years. A 42-item FI was used to measure frailty at each wave. Results A bilinear, two-slope model with a turning point at age 65 best described the age-related change in FI, showing that the increase in frailty was more than twice as fast after age 65. Underweight, obesity, female sex, overweight, being separated from one’s co-twin during childhood, smoking, poor social support, and low physical activity were associated with a higher FI at age 65, with underweight having the largest effect size. When tested as time-varying covariates, underweight and higher social support were associated with a steeper increase in FI before age 65, whereas overweight and obesity were associated with less steep increase in FI after age 65. Conclusions Factors associated with the level and rate of change in frailty are largely actionable and could provide targets for intervention. As deviations from normal weight showed the strongest associations with frailty, future public health programs could benefit from monitoring of individuals with abnormal BMI, especially those who are underweight.

scholarly journals Diagnostic and predictive accuracy of the Clinical Frailty Scale among hospitalised older medical patients: a systematic review and meta-analysis protocol

BMJ Open ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. e040765
Author(s):  
Aoife Leahy ◽  
Margaret O’Connor ◽  
Jennifer Condon ◽  
Sarah Heywood ◽  
Elaine Shanahan ◽  
...  
Keyword(s):  
Systematic Review ◽  
Older Adults ◽  
Diagnostic Accuracy ◽  
Meta Analysis ◽  
Frailty Index ◽  
Adverse Outcomes ◽  
Nursing Home Admission ◽  
Reference Standard ◽  
Clinical Frailty Scale ◽  
Frailty Phenotype

IntroductionFrailty is a common condition affecting older adults and is associated with increased mortality and adverse outcomes. Identification of older adults at risk of adverse outcomes is central to subsequent resource planning and targeted interventions. This systematic review and meta-analysis will examine the: (1) diagnostic accuracy of the Clinical Frailty Scale (CFS) in identifying hospitalised adults ≥65 years with frailty and a medical diagnosis compared with the reference standard Frailty Index or Frailty Phenotype and (2) predictive value of the CFS in determining those at increased risk of subsequent adverse outcomes.Methods and analysisWe will include cross-sectional, retrospective and prospective cohort studies, and randomised controlled trials that assess either the diagnostic accuracy of the CFS when compared with the reference standard Frailty Index/Frailty Phenotype or the predictive validity of the CFS to predict subsequent adverse outcomes in hospitalised adults over 65 years with medical complaints. Adverse outcomes include falls, functional decline, unplanned Emergency Department attendance, emergency rehospitalisation, nursing home admission or death. A systematic search will be conducted in Embase, AMED, MEDLINE (Ebsco, Ovid, Pubmed), CINAHL, PsycINFO, Cochrane Library. Studies will be limited to those published from 2005 to 30 October 2019. Two independent reviewers will screen all titles and abstracts to identify relevant studies. The methodological quality of studies will be independently assessed using the Quality Assessment of Diagnostic Accuracy Studies-2. A CFS score of >4 will be used to identify frailty. We will construct 2×2 tables and determine true positives, true negatives, false positives and false negatives for each study when compared with the reference standard and for each adverse outcome. A bivariate random effects model will be applied to generate pooled summary estimates of sensitivity and specificity.Ethics and disseminationEthical approval is not required for this systematic review. We will disseminate our findings through a peer-reviewed journal.

scholarly journals PREDICTING ADVERSE OUTCOMES IN ED PATIENTS USING THE CLINICAL FRAILTY SCALE AND A FRAILTY INDEX

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S781-S782
Author(s):  
Kenneth Rockwood ◽  
Mohammad Pulok ◽  
Alex van der Valk ◽  
Olga Theou
Keyword(s):  
Confidence Interval ◽  
Odds Ratio ◽  
Average Length ◽  
Frailty Index ◽  
Hazard Ratio ◽  
Adverse Outcomes ◽  
Care Plan ◽  
Prognostic Information ◽  
Clinical Frailty Scale ◽  
Average Length Of Stay

Abstract Our aim was to use the Comprehensive Geriatric Assessment (CGA) database to investigate whether the Clinical Frailty Scale (CFS) measuring the baseline state, and a Frailty Index (FI) based on a CGA (current state, with acute illness) can predict adverse outcomes in acutely ill Emergency Department (ED) patients. It contains CFS and FI scores on 1028 ED patients referred to internal medicine at the Halifax Infirmary between 2009-2019 (Mage 80.69 ± SD 8.28, range 57-103; 54.9% female). The mean scores were 0.44±0.14 (FI) and 5.58±1.66 (CFS). Most patients (72%) arrived via ambulance. The average length of stay was 27.0±20.5 hours. Overall, 22% were discharged home, and 63.5% had died by December 2017 with a mean survival time of 1.98±2.01 years. Controlling for age, sex, and Canadian Triage Acuity Score, the odds ratio (95% Confidence Interval) of being discharged home and the hazard ratio (95% Confidence Interval) for mortality was 0.94 (0.92-0.95) and 1.02 (1.02-1.03), respectively per 0.01-point increase in FI. For the CFS, using score ≤4 as the reference, the odds ratio and the hazard ratio were 0.70 (0.42-1.16) and 2.02 (1.51-2.69), respectively for the CFS 5 group, 0.47 (0.27-0.81) and 2.72 (2.05-3.61), respectively for the CFS 6 group, and 0.38 (0.21-0.70) and 4.67 (3.51-6.20), respectively for the CFS 7-9 group. Even controlling for acuity, both the CFS and the FI independently predict adverse outcomes in ED patients. These add prognostic information to the routinely collected ED assessments, and establish targets for care plan based on recovery to baseline.

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.

Canadian Study of Health and Aging Clinical Frailty Scale: Does It Predict Adverse Outcomes among Geriatric Trauma Patients?

2017 ◽  
Vol 225 (5) ◽  
pp. 658-665.e3 ◽  
Author(s):  
Annie Cheung ◽  
Barbara Haas ◽  
Thom J. Ringer ◽  
Amanda McFarlan ◽  
Camilla L. Wong
Keyword(s):  
Adverse Outcomes ◽  
Geriatric Trauma ◽  
Trauma Patients ◽  
Canadian Study ◽  
Clinical Frailty Scale

scholarly journals Comparison of Sarcopenia with Modified Frailty Index as a Predictor of Adverse Outcomes in Critically Ill Elderly Patients

2021 ◽  
pp. 200-206
Author(s):  
Shrirang Bhurchandi ◽  
Sachin Agrawal ◽  
Sunil Kumar ◽  
Sourya Acharya
Keyword(s):  
Elderly Patients ◽  
Critically Ill ◽  
Health Care Cost ◽  
Frailty Index ◽  
The Elderly ◽  
Time Frame ◽  
Adverse Outcomes ◽  
Cross Sectional ◽  
Parametric Data ◽  
Modified Frailty Index

Background: Ageing is a global fact affecting both developed and developing countries.It brings out various catabolic changes in body resulting in frailty(i.e. the person is not able to with stand minor stresses of the environment, due to reduced reserves in psychologicalreserve of several organ system).Thus causing a great burden of disease, dependence & health care cost. Sarcopenia is the leading component for frailty in the elderly population, but very few studies have been done in India for correlating frailty with sarcopenia. Aim: To compare sarcopenia with modified frailty index (MFI) as a predictor of adverse outcomes in critically ill elderly patients. Methodology: Cross-sectional study will be performed on all the critically ill geriatric subjects/patients coming to all the ICU's of AVBRH, Sawangi (M), Wardha who will satisfy various inclusion and exclusion criteria for selection and all standard parametric & non-parametric data will be assessed by using standard descriptive & inferential statistics. Expected Results: In our study, we are anticipating that the Modified frailty index to be a better predictor of adverse outcomes in terms of mortality as compared to sarcopenia in the critically ill elderly patients. Also, we are anticipating that sarcopenia to be the most important contributor of frailty in critically ill elderly patients and the prevalence of frailty will be high in critically ill elderly patients. Limitation: Due to limited time frame & resources we will not be able to follow up the patients.

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