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      Development of an Electronic Frailty Index for Hospitalized Older Adults in Sweden

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          Abstract

          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 association with adverse outcomes in hospitalized older adults.

          Methods

          EHRs were extracted for 18 225 patients with unplanned admissions between 1 March 2020 and 17 June 2021 from 9 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 modeled 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

          Thirteen thousand one hundred and eighty-eight patients were included in analyses (mean age 83.1 years). A 0.03 increment in the eFI was associated with higher risks of in-hospital (odds ratio: 1.65; 95% confidence interval: 1.54–1.78), 30-day (hazard ratio [HR]: 1.43; 1.38–1.48), and 6-month mortality (HR: 1.34; 1.31–1.37) adjusted for age and sex. Of the frailty and comorbidity measures, the eFI had the highest area under receiver operating characteristic curve for in-hospital mortality of 0.813. Higher eFI was associated with longer length of stay, but had a rather poor discrimination for 30-day readmission.

          Conclusions

          An EHR-based eFI has robust associations with adverse outcomes, suggesting that it can be used in risk stratification in hospitalized older adults.

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          Most cited references48

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          A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation

          The objective of this study was to develop a prospectively applicable method for classifying comorbid conditions which might alter the risk of mortality for use in longitudinal studies. A weighted index that takes into account the number and the seriousness of comorbid disease was developed in a cohort of 559 medical patients. The 1-yr mortality rates for the different scores were: "0", 12% (181); "1-2", 26% (225); "3-4", 52% (71); and "greater than or equal to 5", 85% (82). The index was tested for its ability to predict risk of death from comorbid disease in the second cohort of 685 patients during a 10-yr follow-up. The percent of patients who died of comorbid disease for the different scores were: "0", 8% (588); "1", 25% (54); "2", 48% (25); "greater than or equal to 3", 59% (18). With each increased level of the comorbidity index, there were stepwise increases in the cumulative mortality attributable to comorbid disease (log rank chi 2 = 165; p less than 0.0001). In this longer follow-up, age was also a predictor of mortality (p less than 0.001). The new index performed similarly to a previous system devised by Kaplan and Feinstein. The method of classifying comorbidity provides a simple, readily applicable and valid method of estimating risk of death from comorbid disease for use in longitudinal studies. Further work in larger populations is still required to refine the approach because the number of patients with any given condition in this study was relatively small.
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            Frailty in Older Adults: Evidence for a Phenotype

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              A global clinical measure of fitness and frailty in elderly people.

              There is no single generally accepted clinical definition of frailty. Previously developed tools to assess frailty that have been shown to be predictive of death or need for entry into an institutional facility have not gained acceptance among practising clinicians. We aimed to develop a tool that would be both predictive and easy to use. We developed the 7-point Clinical Frailty Scale and applied it and other established tools that measure frailty to 2305 elderly patients who participated in the second stage of the Canadian Study of Health and Aging (CSHA). We followed this cohort prospectively; after 5 years, we determined the ability of the Clinical Frailty Scale to predict death or need for institutional care, and correlated the results with those obtained from other established tools. The CSHA Clinical Frailty Scale was highly correlated (r = 0.80) with the Frailty Index. Each 1-category increment of our scale significantly increased the medium-term risks of death (21.2% within about 70 mo, 95% confidence interval [CI] 12.5%-30.6%) and entry into an institution (23.9%, 95% CI 8.8%-41.2%) in multivariable models that adjusted for age, sex and education. Analyses of receiver operating characteristic curves showed that our Clinical Frailty Scale performed better than measures of cognition, function or comorbidity in assessing risk for death (area under the curve 0.77 for 18-month and 0.70 for 70-month mortality). Frailty is a valid and clinically important construct that is recognizable by physicians. Clinical judgments about frailty can yield useful predictive information.
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                Author and article information

                Contributors
                Role: Decision Editor
                Journal
                J Gerontol A Biol Sci Med Sci
                J Gerontol A Biol Sci Med Sci
                gerona
                The Journals of Gerontology Series A: Biological Sciences and Medical Sciences
                Oxford University Press (US )
                1079-5006
                1758-535X
                November 2022
                18 March 2022
                18 March 2022
                : 77
                : 11
                : 2311-2319
                Affiliations
                Department of Medical Epidemiology and Biostatistics, Karolinska Institutet , Stockholm, Sweden
                Department of Medical Epidemiology and Biostatistics, Karolinska Institutet , Stockholm, Sweden
                Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet , Stockholm, Sweden
                Theme Inflammation and Aging, Karolinska University Hospital , Huddinge, Sweden
                Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet , Stockholm, Sweden
                Theme Inflammation and Aging, Karolinska University Hospital , Huddinge, Sweden
                Department of Medical Epidemiology and Biostatistics, Karolinska Institutet , Stockholm, Sweden
                Department of Medical Epidemiology and Biostatistics, Karolinska Institutet , Stockholm, Sweden
                Faculty of Social Sciences (Health Sciences) and Gerontology Research Center (GEREC), University of Tampere , Tampere, Finland
                Theme Inflammation and Aging, Karolinska University Hospital , Huddinge, Sweden
                Division of Nursing, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet , Stockholm, Sweden
                Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet , Stockholm, Sweden
                Theme Inflammation and Aging, Karolinska University Hospital , Huddinge, Sweden
                Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet , Stockholm, Sweden
                Theme Inflammation and Aging, Karolinska University Hospital , Huddinge, Sweden
                Department of Geriatric Medicine, Jakobsbergsgeriatriken , Stockholm, Sweden
                Department of Geriatric Medicine, Sabbatsbergsgeriatriken , Stockholm, Sweden
                Department of Geriatric Medicine, Capio Geriatrik Nacka AB , Nacka, Sweden
                Department of Geriatric Medicine, Dalengeriatriken Aleris Närsjukvård AB , Stockholm, Sweden
                Research and Development Unit, Stockholms Sjukhem , Stockholm, Sweden
                Division of Neurogeriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet , Stockholm, Sweden
                Department of Geriatric Medicine, Handengeriatriken, Aleris Närsjukvård AB , Stockholm, Sweden
                Department of Geriatric Medicine, Capio Geriatrik Löwet , Stockholm, Sweden
                Department of Geriatric Medicine, Capio Geriatrik Sollentuna , Stockholm, Sweden
                Theme Inflammation and Aging, Karolinska University Hospital , Huddinge, Sweden
                Department of Public Health and Caring Sciences, Uppsala University , Uppsala, Sweden
                Department of Medical Epidemiology and Biostatistics, Karolinska Institutet , Stockholm, Sweden
                Faculty of Social Sciences (Health Sciences) and Gerontology Research Center (GEREC), University of Tampere , Tampere, Finland
                Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet , Stockholm, Sweden
                Theme Inflammation and Aging, Karolinska University Hospital , Huddinge, Sweden
                Author notes
                Address Correspondence to: Jonathan K. L. Mak, MSc, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels väg 12A, 171 77 Stockholm, Sweden. E-mail: jonathan.mak@ 123456ki.se
                Author information
                https://orcid.org/0000-0003-4454-8580
                https://orcid.org/0000-0002-2452-1500
                https://orcid.org/0000-0002-3765-2067
                https://orcid.org/0000-0003-0250-4491
                Article
                glac069
                10.1093/gerona/glac069
                9678204
                35303746
                d036c784-1c50-4fc4-b054-fc0ae98359a6
                © The Author(s) 2022. Published by Oxford University Press on behalf of The Gerontological Society of America.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence ( https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                : 01 December 2021
                : 10 March 2022
                : 25 April 2022
                Page count
                Pages: 9
                Funding
                Funded by: Swedish Research Council, DOI 10.13039/501100004359;
                Award ID: 2018-02077
                Award ID: 2020-02014
                Award ID: 2020-06101
                Award ID: 335870
                Award ID: 326567
                Award ID: 336670
                Funded by: Läkarsällskapet and Gösta Miltons Donationsfond;
                Funded by: Stockholm University—Region Stockholm;
                Funded by: Centre of Excellence in Research of Ageing and Care;
                Award ID: 335870
                Award ID: 326567
                Award ID: 336670
                Categories
                THE JOURNAL OF GERONTOLOGY: Medical Sciences
                Health Systems
                AcademicSubjects/MED00280
                AcademicSubjects/SCI00960

                Geriatric medicine
                comorbidity,electronic frailty index,frailty,geriatrics
                Geriatric medicine
                comorbidity, electronic frailty index, frailty, geriatrics

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