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 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 AB0556 PRIMARY SYSTEMIC SCLEROSIS HEART INVOLVEMENT (PSSCHI): A SYSTEMATIC LITERATURE REVIEW (SLR), CONSENSUS-BASED DEFINITION AND PRELIMINARY VALIDATION.

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1574.1-1575
Author(s):  
C. Bruni ◽  
M. H. Buch ◽  
P. Seferovic ◽  
M. Matucci-Cerinic
Keyword(s):  
Clinical Practice ◽  
Criterion Validity ◽  
Face Validity ◽  
Nominal Group ◽  
Rater Agreement ◽  
Validation Process ◽  
Research Support ◽  
Consensus Definition ◽  
Heart Involvement ◽  
Definition Of

Background:pSScHI may cause tissue, functional and conduction abnormalities with varied clinical manifestations. The absence of a clear definition of pSScHI impairs the significance and ability of focussed research, frequently not allowing the distinction between primary and secondary involvement.Objectives:We aimed to establish an expert consensus definition for pSScHI, to be used in clinical trials and everyday clinical practice, and to start its validation process.Methods:A SLR for cardiac manifestations and alterations in SSc was conducted using PubMed, Web of Science and Embase. Articles published from inception to December 31st, 2018 were identified. Inclusion criteria included papers in English on adult SSc patients, with heart involvement as outcome. We excluded non-human studies, secondary heart involvement (eg PAH, drugs, infections), reviews and case reports. PRISMA recommendations were followed where applicable. Extracted data were categorized into relevant domains (signs, symptoms, anatomical site involved, physiological abnormalities, pathological changes, prognostic outcomes), which informed the consensus definition. Sixteen senior experts (7 rheumatologists, 8 cardiologists, 1 pathologist) discussed the data and, using a nominal group technique, added expert opinion, provided statements to consider and ranked them. Consensus was attained for agreement >70%. Sixteen clinical cases were evaluated in two rounds to test for face validity, feasibility, inter- and intra-rater reliability and criterion validity (gold standard set by agreed evaluation between expert rheumatologist, cardiologist and methodologist).Results:2593 publications were identified and screened, 251 full texts were evaluated,172 met eligibility criteria. Data from the 7 domains were extracted and used to develop the World Scleroderma Foundation – Heart Failure Association (WSF-HFA) consensus-derived definition of pSSc-HI, as follows:“pSScHI comprises cardiac abnormalities that are predominantly attributable to SSc rather than other causes and/or complications*. pSScHI may be sub-clinical and must be confirmed through diagnostic investigation. The pathogenesis of pSScHI comprises one or more of inflammation, fibrosis and vasculopathy. *Non SSc-specific cardiac conditions (e.g. Ischaemic heart disease, arterial hypertension, drug toxicity, other cardiomyopathy, primary valvular disease) and/or SSc non cardiac conditions (e.g. PAH, Renal involvement, ILD).”Face validity was determined by a 100% agreement on credibility; application was feasible, with a median 60 (5-600) seconds taken per case; inter rater agreement was moderate [mKappa (95%CI) 0.56 (0.46-1.00) and 0.55 (0.44-1.00) for the two rounds] and intra rater agreement was good [mKappa (95%CI) 0.77 (0.47-1,00)]. Content validity was reached based on the wide variety of patients in the SLR, criterion validity was reached with 78 (73-84) % correctness.Conclusion:Using a SLR and modified nominal technique, we have developed a preliminary pSScHI consensus-based definition and started a validation process for it to be used in clinical research and clinical practice.Acknowledgments:Aleksandra Djokovic, Giacomo De Luca, Raluca B. Dumitru,Alessandro Giollo, Marija Polovina, Yossra Atef Suliman, Kostantinos Bratis, Alexia Steelandt, Ivan Milinkovic, Anna Baritussio, Ghadeer Hasan, Anastasia Xintarakou, Yohei Isomura, George Markousis-Mavrogenis, Silvia Bellando-Randone, Lorenzo Tofani, Sophie Mavrogeni, Luna Gargani, Alida L.P. Caforio, Carsten Tschoepe, Arsen Ristic, Karin Klingel, Sven Plein, Elijah Behr, Yannick Allanore, Masataka Kuwana, Christopher Denton, Daniel E. Furst, Dinesh Khanna, Thomas Krieg, Renzo Marcolongo.Disclosure of Interests:Cosimo Bruni Speakers bureau: Actelion, Eli Lilly, Maya H Buch Grant/research support from: Pfizer, Roche, and UCB, Consultant of: Pfizer; AbbVie; Eli Lilly; Gilead Sciences, Inc.; Merck-Serono; Sandoz; and Sanofi, Petar Seferovic: None declared, Marco Matucci-Cerinic Grant/research support from: Actelion, MSD, Bristol-Myers Squibb, Speakers bureau: Acetelion, Lilly, Boehringer Ingelheim

Functional and Psychosocial Consequences of Major Depressive Disorder

2019 ◽  
pp. 1-14
Author(s):  
Tracy L. Greer ◽  
Jeethu K. Joseph
Keyword(s):  
Functional Recovery ◽  
Functional Assessment ◽  
Functional Outcomes ◽  
Antidepressant Treatment ◽  
Great Part ◽  
Assessment Tools ◽  
Consensus Definition ◽  
Psychosocial Consequences ◽  
Home Work ◽  
Definition Of

Depression is associated with profound personal and societal costs worldwide, in great part due to negative functional and psychosocial consequences. These consequences can range from minimally disruptive to life-altering, and they occur across a wide variety of life domains (e.g. home, work, school, social). Despite patient preference for the inclusion of functional outcomes as the desired endpoint of antidepressant treatment and goal for the achievement of wellness, functional outcomes are still infrequently measured. This is likely due, at least in part, to the wide variety of assessment tools that are available and lack of consensus definitions of functional recovery. This chapter reviews several measures that are available to assess functioning; describes the functional impairment associated with depression and related symptoms, such as cognition, sleep, and pain; and briefly discusses issues associated with treating disrupted functioning in depression. Future directions include the need to develop and utilize a consensus definition of functional recovery, as well as consistent incorporation of functional assessment in both clinical monitoring and research outcomes.

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 Prevalence of frailty in patients referred to the kidney transplant waitlist

Kidney360 ◽  
2021 ◽  
pp. 10.34067/KID.0001892021
Author(s):  
George Worthen ◽  
Amanda Vinson ◽  
Héloise Cardinal ◽  
Steve Doucette ◽  
Nessa Gogan ◽  
...  
Keyword(s):  
Kidney Transplant ◽  
Proportional Hazards Model ◽  
Frailty Index ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Assessment Tools ◽  
Measurement Tool ◽  
Clinical Frailty Scale ◽  
Frailty Phenotype ◽  
The Mean

Background: Comparisons between frailty assessment tools for waitlist candidates are a recognized priority area for kidney transplantation. We compared the prevalence of frailty using three established tools in a cohort of waitlist candidates. Methods: Waitlist candidates were prospectively enrolled from 2016-2020 across five centers. Frailty was measured using the Frailty Phenotype (FP, as well as a 37 variable Frailty Index (FI), and the Clinical Frailty Scale (CFS). The FI and CFS were dichotomized using established cut-offs. Agreement was compared using kappa coefficients. Area under the receiver operator characteristic curves were generated to compare the FI and CFS (treated as continuous measures) to the FP. Unadjusted associations between each frailty measure and time to death or waitlist withdrawal were determined using an unadjusted Cox proportional hazards model. Results: Of 542 enrolled patients, 64% were male, 80% were white, and the mean age was 54+/-14. The prevalence of frailty by the FP was 16%. The mean FI score was 0.23+/-0.14 and the prevalence of frailty was 38% (score of >0.25). The median CFS score was 3 (IQR 2,3), and the prevalence was 15% (score of ≥4). Kappa values comparing the FP to the FI (0.438) and CFS (0.272) showed fair to moderate agreement. Area under the ROC curve for the FP and FI/CFS were 0.86 (good) and 0.69 (poor) respectively. Frailty by the CFS (HR 2.10; 95% CI (1.04, 4.24) and FI (HR 1.79; 95% CI 1.00,3.21) was associated with death or permanent withdrawal. The association between frailty by the FP and death/withdrawal was not statistically significant (HR 1.78; CI 0.786, 3.71). Conclusion: Frailty prevalence varies by measurement tool used, and agreement between these measurements is fair to moderate. This has implications for determining the optimal frailty screening tool for use in those being evaluated for kidney transplant.

scholarly journals Toward a consensus definition of pathological video-gaming: A systematic review of psychometric assessment tools

2013 ◽  
Vol 33 (3) ◽  
pp. 331-342 ◽  
Author(s):  
Daniel L. King ◽  
Maria C. Haagsma ◽  
Paul H. Delfabbro ◽  
Michael Gradisar ◽  
Mark D. Griffiths
Keyword(s):  
Systematic Review ◽  
Assessment Tools ◽  
Video Gaming ◽  
Psychometric Assessment ◽  
Consensus Definition ◽  
Definition Of

Preclinical models of frailty: Focus on interventions and their translational impact: A review

2020 ◽  
pp. 1-17
Author(s):  
Manish Mishra ◽  
Susan E. Howlett
Keyword(s):  
Frailty Index ◽  
Experimental Studies ◽  
Adverse Outcomes ◽  
The Body ◽  
Assessment Tools ◽  
Preclinical Models ◽  
Frailty Phenotype ◽  
The Past ◽  
Pharmaceutical Agents ◽  
The Impact

The concept of frailty refers to heterogeneity in the risk of adverse outcomes for people of the same age. It is traditionally thought of as the inability of the body to maintain homeostasis. It can help explain differences between chronological and biological age and can quantify healthspan in experimental studies. Although clinical studies have developed tools to quantify frailty over the past two decades, preclinical models of frailty have only recently been introduced. This review describes the notion of frailty and outlines two commonly used clinical approaches to quantify frailty: the frailty phenotype and the frailty index. Translation of these methodologies for use in animals is introduced and studies that use these models to evaluate interventions designed to attenuate or exacerbate frailty are discussed. These include studies involving manipulation of diet, implementation of exercise regimens and tests of pharmaceutical agents to exacerbate or attenuate frailty. Together, this body of work suggests that preclinical frailty assessment tools are a valuable new resource to quantify the impact of interventions on overall health. Future studies could deploy these models to evaluate new frailty therapies, test combinations of interventions and assess interventions to enhance the ability to resist stressors in the setting of ageing.

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