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      Commonly Used Screening Instruments to Identify Frailty Among Community-Dwelling Older People in a General Practice (Primary Care) Setting: A Study of Diagnostic Test Accuracy

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          Abstract

          Background

          Rapid frailty screening remains problematic in primary care. The diagnostic test accuracy (DTA) of several screening instruments has not been sufficiently established. We evaluated the DTA of several screening instruments against two reference standards: Fried’s Frailty Phenotype [FP] and the Adelaide Frailty Index [AFI]), a self-reported questionnaire.

          Methods

          DTA study within three general practices in South Australia. We randomly recruited 243 general practice patients aged 75+ years. Eligible participants were 75+ years, proficient in English and community-dwelling. We excluded those who were receiving palliative care, hospitalized or living in a residential care facility.

          We calculated sensitivity, specificity, predictive values, likelihood ratios, Youden Index and area under the curve (AUC) for: Edmonton Frail Scale [EFS], FRAIL Scale Questionnaire [FQ], Gait Speed Test [GST], Groningen Frailty Indicator [GFI], Kihon Checklist [KC], Polypharmacy [POLY], PRISMA-7 [P7], Reported Edmonton Frail Scale [REFS], Self-Rated Health [SRH] and Timed Up and Go [TUG]) against FP [3+ criteria] and AFI [>0.21].

          Results

          We obtained valid data for 228 participants, with missing scores for index tests multiply imputed. Frailty prevalence was 17.5% frail, 56.6% prefrail [FP], and 48.7% frail, 29.0% prefrail [AFI]. Of the index tests KC (Se: 85.0% [70.2–94.3]; Sp: 73.4% [66.5–79.6]) and REFS (Se: 87.5% [73.2–95.8]; Sp: 75.5% [68.8–81.5]), both against FP, showed sufficient diagnostic accuracy according to our prespecified criteria.

          Conclusions

          Two screening instruments—the KC and REFS, show the most promise for wider implementation within general practice, enabling a personalized approach to care for older people with frailty.

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          Most cited references29

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          The frailty phenotype and the frailty index: different instruments for different purposes.

          The integration of frailty measures in clinical practice is crucial for the development of interventions against disabling conditions in older persons. The frailty phenotype (proposed and validated by Fried and colleagues in the Cardiovascular Health Study) and the Frailty Index (proposed and validated by Rockwood and colleagues in the Canadian Study of Health and Aging) represent the most known operational definitions of frailty in older persons. Unfortunately, they are often wrongly considered as alternatives and/or substitutables. These two instruments are indeed very different and should rather be considered as complementary. In the present paper, we discuss about the designs and rationals of the two instruments, proposing the correct ways for having them implemented in the clinical setting.
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            ROC-ing along: Evaluation and interpretation of receiver operating characteristic curves.

            It is vital for clinicians to understand and interpret correctly medical statistics as used in clinical studies. In this review, we address current issues and focus on delivering a simple, yet comprehensive, explanation of common research methodology involving receiver operating characteristic (ROC) curves. ROC curves are used most commonly in medicine as a means of evaluating diagnostic tests.
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              Frailty prevalence and slow walking speed in persons age 65 and older: implications for primary care

              Background Frailty in the elderly increases their vulnerability and leads to a greater risk of adverse events. According to various studies, the prevalence of the frailty syndrome in persons age 65 and over ranges between 3% and 37%, depending on age and sex. Walking speed in itself is considered a simple indicator of health status and of survival in older persons. Detecting frailty in primary care consultations can help improve care of the elderly, and walking speed may be an indicator that could facilitate the early diagnosis of frailty in primary care. The objective of this work was to estimate frailty-syndrome prevalence and walking speed in an urban population aged 65 years and over, and to analyze the relationship between the two indicators from the perspective of early diagnosis of frailty in the primary care setting. Methods Population cohort of persons age 65 and over from two urban neighborhoods in northern Madrid (Spain). Cross-sectional analysis. Bivariate and multivariate analysis with binary logistic regression to study the variables associated with frailty. Different cut-off points between 0.4 and 1.4 m/s were used to study walking speed in this population. The relationship between frailty and walking speed was analyzed using likelihood ratios. Results The study sample comprised 1,327 individuals age 65 and older with mean age 75.41 ± 7.41 years; 53.4% were women. Estimated frailty in the study population was 10.5% [95% CI: 8.9-12.3]. Frailty increased with age (OR = 1.14; 95% CI: 1.10-1.19) and was associated with poor self-rated health (OR = 2.52; 95% CI: 1.43-4.44), number of drugs prescribed (OR = 1.17; 95% CI: 1.08-1.26) and disability (OR = 6.58; 95% CI: 3.92-11.05). Walking speed less than 0.8 m/s was found in 42.6% of cases and in 56.4% of persons age 75 and over. Walking speed greater than 0.9 m/s ruled out frailty in the study sample. Persons age 75 and older with walking speed <0.8 m/s are at particularly high risk of frailty (32.1%). Conclusions Frailty-syndrome prevalence is high in persons aged 75 and over. Detection of walking speed <0.8 m/s is a simple approach to the diagnosis of frailty in the primary care setting.
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                Author and article information

                Journal
                The Journals of Gerontology: Series A
                Oxford University Press (OUP)
                1079-5006
                1758-535X
                June 2020
                May 22 2020
                November 05 2019
                June 2020
                May 22 2020
                November 05 2019
                : 75
                : 6
                : 1134-1142
                Affiliations
                [1 ]National Health and Medical Research Council Centre of Research Excellence in Trans-Disciplinary Frailty Research to Achieve Healthy Ageing, Adelaide, South Australia, Australia
                [2 ]Torrens University Australia, Adelaide, South Australia, Australia
                [3 ]Adelaide Medical School, Faculty of Health and Medical Sciences, University of Adelaide, Adelaide, South Australia, Australia
                [4 ]Baker Heart and Diabetes Institute, Melbourne, Victoria
                [5 ]Adelaide Nursing School, Faculty of Health and Medical Sciences, University of Adelaide, Adelaide, South Australia, Australia
                Article
                10.1093/gerona/glz260
                31689342
                6b9fc1bd-9e3c-4b09-bc3c-ac48aaf1a887
                © 2019

                https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model

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