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.

LETTER TO THE EDITOR : HOW USEFUL ARE MULTIDOMAIN FRAILTY MEASURES IN RESEARCH AND CLINICAL PRACTICE?

2014 ◽  
pp. 1-2
Author(s):  
E.O. Hoogendijk
Keyword(s):  
Clinical Practice ◽  
Frailty Index ◽  
Assessment Tools ◽  
Consensus Definition ◽  
Frailty Phenotype ◽  
Groningen Frailty Indicator ◽  
Physiologic Function ◽  
Definition Of ◽  
International Experts ◽  
Frailty Indicator

To the Editor: There is increasing attention for the conceptof frailty in research and clinical practice. However, there arestill issues with regard to the conceptualization of frailty thatneed to be solved. Recently, international experts havemanaged to formulate a consensus definition of physical frailty:“A medical syndrome with multiple causes and contributorsthat is characterized by diminished strength, endurance, andreduced physiologic function that increases an individual’svulnerability for developing increased dependency and/ordeath” (1). This definition is in line with some commonly usedfrailty assessment tools, such as the frailty phenotype, theFRAIL questionnaire, and the Frailty Index (1). At the sametime, this frailty definition does not fully cover multidomainfrailty measures. These are frailty measures consisting ofsubscores for different frailty domains, such as thepsychological and social domain (Table 1). The Tilburg FrailtyIndicator (TFI) and the Groningen Frailty Indicator (GFI) areexamples of multidomain frailty measures (the Frailty Indexmay not be considered a multidomain frailty measure, butmultidimensional, since the global score derived from theFrailty Index does not distinguish different domains). Thequestion arises how multidomain frailty measures relate to thephysical frailty concept, and how they should be used inresearch and clinical practice. For what concerns the feasibilityof implementing multidomain frailty measures in the researchand clinical se

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 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 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 Identifying frailty: do the Frailty Index and Groningen Frailty Indicator cover different clinical perspectives? a cross-sectional study

2013 ◽  
Vol 14 (1) ◽  
Author(s):  
Irene Drubbel ◽  
Nienke Bleijenberg ◽  
Guido Kranenburg ◽  
René JC Eijkemans ◽  
Marieke J Schuurmans ◽  
...  
Keyword(s):  
Frailty Index ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Cross Sectional ◽  
Groningen Frailty Indicator ◽  
Frailty Indicator

scholarly journals Evaluation of the Groningen Frailty Indicator and the G8 questionnaire as screening tools for frailty in older patients with cancer

2013 ◽  
Vol 4 (1) ◽  
pp. 32-38 ◽  
Author(s):  
Abdelbari Baitar ◽  
Frank Van Fraeyenhove ◽  
An Vandebroek ◽  
Els De Droogh ◽  
Daniella Galdermans ◽  
...  
Keyword(s):  
Older Patients ◽  
Screening Tools ◽  
Patients With Cancer ◽  
Groningen Frailty Indicator ◽  
Frailty Indicator

scholarly journals Frailty Phenotype and Healthcare Costs in Women in Late Life: The SOF study

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 778-778
Author(s):  
Lisa Langsetmo ◽  
Allyson Kats ◽  
John Schousboe ◽  
Tien Vo ◽  
Brent Taylor ◽  
...  
Keyword(s):  
Healthcare Costs ◽  
Functional Limitations ◽  
Late Life ◽  
Cost Ratio ◽  
Deficit Accumulation ◽  
Frailty Phenotype ◽  
Medicare Claims ◽  
Accumulation Index ◽  
Direct Healthcare Costs ◽  
Frailty Indicator

Abstract We used data from 1324 women (mean age 83) at the 2002-2004 exam linked with their Medicare claims to determine the association of the frailty phenotype with healthcare costs. The frailty phenotype was categorized as robust, pre-frail or frail. Multimorbidity and a frailty indicator (approximating the deficit accumulation index) were derived from claims. Functional limitations were assessed by asking about difficulty performing IADL. Total direct healthcare costs were ascertained during 36 months following the exam. Compared with robust, pre-frailty and frailty were associated with higher costs after accounting for demographics, multimorbidity, functional limitations and the frailty indicator (cost ratio 1.37 [1.10-1.71] among pre-frail and 1.63 [1.28-2.08] among frail). Discrimination of high-cost (top decile) women was improved by adding the phenotype and functional limitations to a model containing demographics and the claims-based measures. Findings suggest that assessment of the phenotype may improve identification of individuals at higher risk of costly care.

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.

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