scholarly journals 20 Comparison of Six Frailty Screening Tools in Patients Aged 65+ with An Arm Fragility Fracture

2021 ◽  
Vol 50 (Supplement_1) ◽  
pp. i1-i6
Author(s):  
K Ibrahim ◽  
T Lim ◽  
M A Mullee ◽  
G L Yao ◽  
S Zhu ◽  
...  
Keyword(s):  
Fragility Fracture ◽  
Frailty Index ◽  
Screening Tools ◽  
Frailty Phenotype ◽  
Fracture Clinic ◽  
Increased Risk ◽  
Sensitivity Range ◽  
Practical Tool ◽  
Acute Trust ◽  
Medication Changes

Abstract Introduction Frailty is associated with an increased risk of falling and fracture, but not routinely assessed in fracture clinic. Early identification and management of frailty among older people with arm fragility fracture could help avoid further falls and fractures, especially of the hip. We evaluated the feasibility of assessing frailty in a busy fracture clinic. Methods People aged 65+ years with an arm fracture in one acute trust were recruited. Frailty was assessed in fracture clinics using six tools: Fried Frailty Phenotype (FFP), FRAIL scale, PRISMA-7, electronic Frailty Index (e-FI), Clinical Frailty Score (CFS), and Study of Osteoporotic Fracture (SOF). The sensitivity and specificity of each tool was compared against FFP as a reference. Participants identified as frail by 2+ tools were referred for Comprehensive Geriatric Assessment (CGA). Results 100 patients (mean age 75 years±7.2; 20 men) were recruited. Frailty prevalence was 9% (FRAIL scale), 13% (SOF), 14% (CFS > 6), 15% (FFP; e-FI > 0.25), and 25% (PRISMA-7). Men were more likely to be frail than women. Data were complete for all assessments and completion time ranged from one minute (PRISMA-7; CFS) to six minutes for the FFP which required most equipment. Comparing with FFP, the most accurate instrument for stratifying frail from non-frail was the PRISMA-7 (sensitivity = 93%, specificity = 87%) while the remaining tools had good specificity (range 93%–100%) but average sensitivity (range 40%–60%). Twenty patients were eligible for CGA. Five had recently had CGA and 11/15 referred were assessed. CGA led to 3–6 interventions per participant including medication changes, life-style advice, investigations, and onward referrals. Conclusion It was feasible to assess frailty in fracture clinic and to identify patients who benefitted from CGA. Frailty prevalence was 9%—25% depending on the tool used and was higher among men. PRISMA-7 could be a practical tool for routine use in fracture clinics.

scholarly journals 444Frailty status and all-cause mortality in the community-dwelling individuals: An umbrella review

2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
A R M Saifuddin Ekram ◽  
Joanne Ryan ◽  
Carlene Britt ◽  
Sara Espinoza ◽  
Robyn Woods
Keyword(s):  
Systematic Reviews ◽  
Critical Appraisal ◽  
Frailty Index ◽  
Community Dwelling ◽  
Umbrella Review ◽  
Deficit Accumulation ◽  
Frailty Phenotype ◽  
Essential Information ◽  
Increased Risk ◽  
All Cause Mortality

Abstract Background Frailty is increasingly recognised for its association with adverse health outcomes, including mortality. However, various measures are used to assess frailty, and the strength of association could vary depending on the specific definition used. This umbrella review aims to map which frailty scale can best predict the relationship between frailty and all-cause mortality among community-dwelling older people. Methods A protocol was registered at PROSPERO, and it was conducted following the PRISMA statement. MEDLINE, Embase, PubMed, Cochrane Database of Systematic Reviews, Joanna Briggs Institute (JBI) EBP database, and Web of Science database was searched. Methodological quality was assessed using the JBI critical appraisal checklist and online AMSTAR-2 critical appraisal checklist. For eligible studies, essential information was extracted and synthesized qualitatively. Results Five systematic reviews were included, with a total of 434,115 participants. Three systematic reviews focused on single frailty scales; one evaluated Fried's physical frailty phenotype and its modifications; another focused on the deficit accumulation frailty index. The third evaluated the FRAIL (Fatigue, Resistance, Ambulation, Illness, and Loss of weight) scale. The two other systematic reviews determined the association between frailty and mortality using different frailty scales. All of the systematic reviews found that frailty was significantly associated with all-cause mortality. Conclusion This umbrella review demonstrates that frailty is a significant predictor of all-cause mortality, irrespective of the specific frailty scale. Key messages Frailty is associated with an increased risk of all-cause mortality in community-dwelling individuals signifying the importance of assessment in the primary healthcare setting.

scholarly journals The prevalence of frailty, measured with different diagnostic tools, and autonomy decline: Results of the Crystal study

2021 ◽  
Vol 25 (1) ◽  
pp. 35-43
Author(s):  
Anna V. Turusheva ◽  
Elena V. Frolova ◽  
Tatiana A. Bogdanova
Keyword(s):  
Vision Loss ◽  
Factor Model ◽  
Frailty Index ◽  
Screening Tools ◽  
Diagnostic Tools ◽  
Geriatric Syndromes ◽  
Frailty Phenotype ◽  
Groningen Frailty Indicator ◽  
Blocking Factor ◽  
Frailty Indicator

INTRODUCTION: Frailty prevalence differs across different population depending on the models used to assess, age, economic situation, social status, and the proportion of men and women in the study. The diagnostic value of different models of frailty varies from population to population. OBJECTIVES: To assess the prevalence of frailty using 4 different diagnostic models and their sensitivity for identifying persons with autonomy decline. MATERIAL AND METHODS: A random sample of 611 people aged 65 and over. Models used: the Age is not a blocking factor model, the SOF Frailty Index, the Groningen Frailty Indicator, L. Fried model. Covariates: nutritional status, anemia, functional status, depression, dementia, chronic diseases, grip strength, physical function. RESULTS: The prevalence of the Frailty Phenotype ranged from 16.6 to 20.4% and the Frailty Index was 32.6%. Frailty, regardless of the used models was associated with an increase in the prevalence of the geriatric syndromes: urinary incontinence, hearing and vision loss, physical decline, malnutrition and the risk of malnutrition, low cognitive functions and autonomy decline (p 0.05). The negative predictive value (NPV) of the Age is not a blocking factor model, the SOF Frailty Index, the Groningen Frailty Indicator for identifying individuals with autonomy decline was 8690%. CONCLUSION: The prevalence of frailty depended on the operational definition and varied from 16.6 to 32.6%. The Age is not a blocking factor model, the SOF Frailty Index, the Groningen Frailty Indicator, L. Fried model can be used as screening tools to identify older patient with autonomy decline. Regardless of the model used, frailty is closely associated with an increase in the prevalence of major geriatric syndromes.

scholarly journals Polypharmacy Is Significantly and Positively Associated with the Frailty Status Assessed Using the 5-Item FRAIL Scale, Cardiovascular Health Phenotypic Classification of Frailty Index, and Study of Osteoporotic Fractures Scale

2021 ◽  
Vol 10 (19) ◽  
pp. 4413
Author(s):  
Chi-Di Hung ◽  
Chen-Cheng Yang ◽  
Chun-Ying Lee ◽  
Stephen Chu-Sung Hu ◽  
Szu-Chia Chen ◽  
...  
Keyword(s):  
Cardiovascular Health ◽  
Frailty Index ◽  
Osteoporotic Fractures ◽  
Cross Sectional Study ◽  
Screening Tools ◽  
Future Research ◽  
Frailty Phenotype ◽  
Cross Sectional ◽  
Phenotypic Classification

The aim of this study was to investigate the association between frailty and polypharmacy using three different frailty screening tools. This was a cross-sectional study of people aged ≥65 years. Participants were included and interviewed using questionnaires. Polypharmacy was defined as the daily use of eight or more pills. Frailty was assessed using a screening tool, including (1) the Fatigue, Resistance, Ambulation, Illness and Loss of Weight Index (5-item FRAIL scale), (2) the Cardiovascular Health Phenotypic Classification of Frailty (CHS_PCF) index (Fried’s Frailty Phenotype), and (3) the Study of Osteoporotic Fracture (SOF) scale. A total of 205 participants (mean age: 71.1 years; 53.7% female) fulfilled our inclusion criteria. The proportion of patients with polypharmacy was 14.1%. After adjustments were made for comorbidity or potential confounders, polypharmacy was associated with frailty on the 5-item FRAIL scale (adjusted odds ratio [aOR]: 9.12; 95% confidence interval [CI]: 3.6–23.16), CHS_PCF index (aOR: 8.98; 95% CI: 2.51–32.11), and SOF scale (aOR: 6.10; 95% CI: 1.47–25.3). Polypharmacy was associated with frailty using three frailty screening tools. Future research is required to further enhance our understanding of the risk of frailty among older adults.

scholarly journals Toward Using a Smartwatch to Monitor Frailty in a Hospital Setting: Using a Single Wrist-Wearable Sensor to Assess Frailty in Bedbound Inpatients

Gerontology ◽  
2017 ◽  
Vol 64 (4) ◽  
pp. 389-400 ◽  
Author(s):  
Hyoki Lee ◽  
Bellal Joseph ◽  
Ana Enriquez ◽  
Bijan Najafi
Keyword(s):  
Frailty Index ◽  
Hospital Setting ◽  
Area Under The Curve ◽  
Screening Tools ◽  
Recursive Feature Elimination ◽  
Physical Frailty ◽  
Frailty Phenotype ◽  
Frailty Status ◽  
Flexion Extension ◽  
Sensor Configuration

Background: While various objective tools have been validated for assessing physical frailty in the geriatric population, these are often unsuitable for busy clinics and mobility-impaired patients. Recently, we have developed a frailty meter (FM) using two wearable sensors, which allows capturing key frailty phenotypes (weakness, slowness, and exhaustion), by testing 20-s rapid elbow flexion-extension test. Objective: In this study, we proposed an enhanced automated algorithm to identify frailty using a single wrist-worn sensor. Methods: The data collected from 100 geriatric inpatients (age: 78.9 ± 9.1 years, 49% frail) were reanalyzed to validate the new algorithm. The frailty status of the participants was determined using a validated modified frailty index. Different FM phenotypes (31 features) including velocity of elbow rotation, decline in velocity of elbow rotation over 20 s, range of motion, etc. were extracted. A regression model, bootstrap with 2,000 iterations, and recursive feature elimination technique were used for optimizing the FM parameters and identifying frailty using a single wrist-worn sensor. Results: A strong agreement was observed between two-sensor and wrist-worn sensor configuration (r = 0.87, p < 0.001). Results suggest that the wrist-worn FM with no demographic information still yields a high accuracy of 80.0% (95% CI: 79.7-80.3%) and an area under the curve of 87.7% (95% CI: 87.4-87.9%) to identify frailty status. Results are comparable with two-sensor configuration, where the observed accuracy and area under the curve were 80.6% (95% CI: 80.4-80.9%) and 87.4% (95% CI: 87.1-87.6%), respectively. Conclusion: The simplicity of FM may open new avenues to integrate wearable technology and mobile health to capture frailty status in a busy hospital setting. Furthermore, the reduction of needed sensors to a single wrist-worn sensor allows deployment of the proposed algorithm in the form of a smartwatch application. From the application standpoint, the proposed FM is superior to traditional physical frailty-screening tools in which the walking test is a key frailty phenotype, and thus they cannot be used for bedbound patients or in busy clinics where administration of gait test as a part of routine assessment is impractical.

scholarly journals CONSTRUCT VALIDITY OF FOUR FRAILTY MEASURES IN AN OLDER AUSTRALIAN POPULATION: A RASCH ANALYSIS

2016 ◽  
pp. 1-4
Author(s):  
I.S. WIDAGDO ◽  
N. PRATT ◽  
M. RUSSELL ◽  
E.E. ROUGHEAD
Keyword(s):  
Construct Validity ◽  
Rasch Analysis ◽  
Frailty Index ◽  
Principal Component ◽  
Older Population ◽  
Frailty Phenotype ◽  
Frailty Status ◽  
Increased Risk ◽  
Explained Variance ◽  
Unexplained Variance

Individuals identified as frail have been shown to be at an increased risk of adverse health outcomes. However, there is no gold standard frailty measure and frailty status can vary depending on the measure used, suggesting the measures perform differently. Construct validity can be used to assess a measure’s performance. This study aimed to examine the construct validity of four frailty measures in an Australian older population using Rasch analysis. Frailty status among the 2087 participants aged 65 years and above from the Australian Longitudinal Study of Ageing (ALSA) was assessed using: frailty phenotype - FP, simplified frailty phenotype - SFP, frailty index - FI, and prognostic frailty score – PFS. Rasch analysis was used to assess the unidimensionality of the measures, which is the extent to which the underlying characteristic of frailty is assessed. The criteria for unidimensionality from principal component analysis of the residuals was when 50% or more of the raw variance was explained by the measures, and less than 5% was unexplained variance. Only FI meet the unidimensionality criteria with 74% of explained variance and 2.1% of unexplained variance. SFP did not show a unidimensional construct with 13.3% of explained variance and 47.1% of unexplained variance. FP and PFS had 39.6%, 18.1% and 46.5%, 8.7% of explained and unexplained variance, respectively. Our findings showed that FI has better construct validity than the other three measures in assessing frailty among the Australian older population.

scholarly journals Feasibility, acceptability and diagnostic test accuracy of frailty screening instruments in community-dwelling older people within the Australian general practice setting: a study protocol for a cross-sectional study

BMJ Open ◽  
2017 ◽  
Vol 7 (8) ◽  
pp. e016663 ◽  
Author(s):  
Rachel Ambagtsheer ◽  
Renuka Visvanathan ◽  
Matteo Cesari ◽  
Solomon Yu ◽  
Mandy Archibald ◽  
...  
Keyword(s):  
General Practice ◽  
Diagnostic Test ◽  
Frailty Index ◽  
Community Dwelling ◽  
Diagnostic Test Accuracy ◽  
Test Accuracy ◽  
Screening Instruments ◽  
Frailty Phenotype ◽  
Predictive Values ◽  
Increased Risk

IntroductionFrailty is one of the most challenging aspects of population ageing due to its association with increased risk of poor health outcomes and quality of life. General practice provides an ideal setting for the prevention and management of frailty via the implementation of preventive measures such as early identification through screening.Methods and analysisOur study will evaluate the feasibility, acceptability and diagnostic test accuracy of several screening instruments in diagnosing frailty among community-dwelling Australians aged 75+ years who have recently made an appointment to see their general practitioner (GP). We will recruit 240 participants across 2 general practice sites within South Australia. We will invite eligible patients to participate and consent to the study via mail. Consenting participants will attend a screening appointment to undertake the index tests: 2 self-reported (Reported Edmonton Frail Scale and Kihon Checklist) and 5 (Frail Scale, Groningen Frailty Index, Program on Research for Integrating Services for the Maintenance of Autonomy (PRISMA-7), Edmonton Frail Scale and Gait Speed Test) administered by a practice nurse (a Registered Nurse working in general practice). We will randomise test order to reduce bias. Psychosocial measures will also be collected via questionnaire at the appointment. A blinded researcher will then administer two reference standards (the Frailty Phenotype and Adelaide Frailty Index). We will determine frailty by a cut-point of 3 of 5 criteria for the Phenotype and 9 of 42 items for the AFI. We will determine accuracy by analysis of sensitivity, specificity, predictive values and likelihood ratios. We will assess feasibility and acceptability by: 1) collecting data about the instruments prior to collection; 2) interviewing screeners after data collection; 3) conducting a pilot survey with a 10% sample of participants.Ethics and disseminationThe Torrens University Higher Research Ethics Committee has approved this study. We will disseminate findings via publication in peer-reviewed journals and presentation at relevant conferences.

scholarly journals The Measurements of Frailty and Their Possible Application to Spinal Conditions. A Systematic Review

2021 ◽  
Author(s):  
Eryck Moskven ◽  
Raphaële Charest-Morin ◽  
Alana M. Flexman ◽  
John T. Street
Keyword(s):  
Systematic Review ◽  
Risk Stratification ◽  
Spine Surgery ◽  
Adult Spinal Deformity ◽  
Frailty Index ◽  
Primary Objective ◽  
Screening Tools ◽  
Effective Interventions ◽  
Increased Risk ◽  
Cumulative Deficit

Abstract Background: Frailty is associated with an increased risk of postoperative adverse events (AEs) within the surgical spine population. Multiple frailty tools have been reported in the surgical spine literature. However, the applicability of these tools remains unclear. The primary objective of this systematic review is to appraise the construct, feasibility, objectivity, and clinimetric properties of frailty tools reported in the surgical spine literature. Secondary objectives included determining the applicability and the most sensitive surgical spine population for each tool. Methods: This systematic review was registered with PROSPERO: CRD42019109045. Publications from January 1950 to December 2020 were identified by a comprehensive search of PubMed, Ovid, Embase, and Cochrane, supplemented by manual screening. Studies reporting and validating a frailty tool in the surgical spine population with a measurable outcome were included. Each tool and its respective clinimetric properties were evaluated using validated criteria and definitions. The applicability of each tool and its most sensitive surgical spine population was determined by panel consensus. Bias was assessed using the Newcastle-Ottawa Scale.Results: 47 studies were included in the final qualitative analysis. A total of 14 separate frailty tools were identified, in which nine tools assessed frailty according to the cumulative deficit definition, while four instruments utilized phenotypic or weighted frailty models. One instrument assessed frailty according to the comprehensive geriatric assessment (CGA) model. Twelve measures were validated as risk stratification tools for predicting postoperative AEs, while one tool investigated the effect of spine surgery on postoperative frailty trajectory. The modified frailty index (mFI), 5-item mFI, adult spinal deformity frailty index (ASD-FI), FRAIL Scale, and CGA had the most positive ratings for clinimetric properties assessed. Conclusions: The assessment of frailty is important in the surgical decision-making process. Cumulative deficit and weighted frailty instruments are appropriate risk stratification tools. Phenotypic tools are sensitive for capturing the relationship between spinal pathology, spine surgery, and prehabilitation on frailty trajectory. CGA instruments are appropriate screening tools for identifying health deficits susceptible to improvement and guiding optimization strategies. Studies are needed to determine whether spine surgery and prehabilitation are effective interventions to reverse frailty.

scholarly journals Frailty and comorbidity in predicting community COVID-19 mortality in the UK Biobank: the effect of sampling

2020 ◽  
Author(s):  
Jonathan K. L. Mak ◽  
Ralf Kuja-Halkola ◽  
Yunzhang Wang ◽  
Sara Hägg ◽  
Juulia Jylhävä
Keyword(s):  
Community Sample ◽  
Frailty Index ◽  
Predictive Ability ◽  
Population Level ◽  
Added Value ◽  
Older Individuals ◽  
Uk Biobank ◽  
Frailty Phenotype ◽  
Full Sample ◽  
Increased Risk

AbstractFrailty has been linked to increased risk of COVID-19 mortality, but evidence is mainly limited to hospitalized older individuals and analyses in community samples are scarce. This study aims to assess and compare the predictive abilities of different frailty measures – the frailty phenotype (FP), frailty index (FI), and Hospital Frailty Risk Score (HFRS), and comorbidity, measured using the Charlson Comorbidity Index (CCI), on COVID-19 mortality in a UK community sample of adults aged 52–86 years. We analyzed (i) the full sample of 428,754 UK Biobank participants and (ii) a subsample of 2,287 COVID-19 positive UK Biobank participants with data on COVID-19 outcomes between March 1 and September 21, 2020. COVID-19 positivity was confirmed by PCR, hospital records and/or death registers. Logistic regression models adjusted for age, sex, smoking, ethnicity, and socioeconomic variables with areas under the receiver operating characteristic curves (AUCs) were used in the modelling. Overall, 391 individuals died of COVID-19. In the full sample, all frailty measures and the CCI were associated with COVID-19 mortality but only the HFRS and CCI improved the predictive ability of a model including age and sex, yielding AUCs>0.80. However, when restricting analyses to the COVID-19 positive subsample, which had an over-representation of frail individuals, similar improvement in AUCs was not observed in which only the CCI was significantly associated with COVID-19 mortality. Our results suggest that HFRS and CCI can be used in COVID-19 mortality risk stratification at the population level, but they show limited added value in COVID-19 positive individuals.

scholarly journals Low levels of frailty in HIV-positive older adults on antiretroviral therapy in northern Tanzania

2021 ◽  
Author(s):  
Clare Bristow ◽  
Grace George ◽  
Grace Hillsmith ◽  
Emma Rainey ◽  
Sarah Urasa ◽  
...  
Keyword(s):  
Antiretroviral Therapy ◽  
High Standard ◽  
Female Gender ◽  
Screening Tools ◽  
Sub Saharan Africa ◽  
Hiv Care ◽  
Diagnostic Tools ◽  
Clinical Frailty Scale ◽  
Frailty Phenotype ◽  
Sub Saharan

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.

scholarly journals Frailty Status and All-Cause Mortality in the Community-Dwelling Older People: An Umbrella Review

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 488-489
Author(s):  
A R M Saifuddin Ekram ◽  
Joanne Ryan ◽  
Carlene Britt ◽  
Sara Espinoza ◽  
Robyn Woods
Keyword(s):  
Older People ◽  
Systematic Reviews ◽  
Community Dwelling ◽  
Umbrella Review ◽  
Frailty Phenotype ◽  
Frailty Status ◽  
Increased Risk ◽  
All Cause Mortality ◽  
Community Dwelling Older People ◽  
Meta Analyses

Abstract Frailty is increasingly recognised for its association with adverse health outcomes including mortality. However, various measures are used to assess frailty, and the strength of association could vary depending on the specific definition used. This umbrella review aimed to map which frailty scale could best predict the relationship between frailty and all-cause mortality among community-dwelling older people. According to the PRISMA guidelines, Medline, Embase, EBSCOhost and Web of Science databases were searched to identify eligible systematic reviews and meta-analyses which examined the association between frailty and all-cause mortality in the community-dwelling older people. Relevant data were extracted and summarised qualitatively. Methodological quality was assessed by AMSTAR-2 checklist. Five moderate-quality systematic reviews with a total of 374,529 participants were identified. Of these, two examined the frailty phenotype and its derivatives, two examined the cumulative deficit models and the other predominantly included studies assessing frailty with the FRAIL scale. All of the reviews found a significant association between frailty status and all-cause mortality. The magnitude of association varied between individual studies, with no consistent pattern related to the frailty measures that were used. In conclusion, regardless of the measure used to assess frailty status, it is associated with an increased risk of all-cause mortality.

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