Prognosis for older people at presentation to emergency department based on frailty and aggregated vital signs.

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Abstract

Risk stratification for older people based on aggregated vital signs lack the accuracy to predict mortality at presentation to the Emergency Department (ED). We aimed to develop and internally validate the Frailty adjusted Prognosis in ED tool (FaP-ED) for 30-day mortality combining frailty and aggregated vital signs.

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

Kenneth Rockwood, Xiaowei Song, Chris MacKnight … (2005)

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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Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study.

Karen Barnett, Stewart Mercer, Michael Norbury … (2012)

Long-term disorders are the main challenge facing health-care systems worldwide, but health systems are largely configured for individual diseases rather than multimorbidity. We examined the distribution of multimorbidity, and of comorbidity of physical and mental health disorders, in relation to age and socioeconomic deprivation. In a cross-sectional study we extracted data on 40 morbidities from a database of 1,751,841 people registered with 314 medical practices in Scotland as of March, 2007. We analysed the data according to the number of morbidities, disorder type (physical or mental), sex, age, and socioeconomic status. We defined multimorbidity as the presence of two or more disorders. 42·2% (95% CI 42·1-42·3) of all patients had one or more morbidities, and 23·2% (23·08-23·21) were multimorbid. Although the prevalence of multimorbidity increased substantially with age and was present in most people aged 65 years and older, the absolute number of people with multimorbidity was higher in those younger than 65 years (210,500 vs 194,996). Onset of multimorbidity occurred 10-15 years earlier in people living in the most deprived areas compared with the most affluent, with socioeconomic deprivation particularly associated with multimorbidity that included mental health disorders (prevalence of both physical and mental health disorder 11·0%, 95% CI 10·9-11·2% in most deprived area vs 5·9%, 5·8%-6·0% in least deprived). The presence of a mental health disorder increased as the number of physical morbidities increased (adjusted odds ratio 6·74, 95% CI 6·59-6·90 for five or more disorders vs 1·95, 1·93-1·98 for one disorder), and was much greater in more deprived than in less deprived people (2·28, 2·21-2·32 vs 1·08, 1·05-1·11). Our findings challenge the single-disease framework by which most health care, medical research, and medical education is configured. A complementary strategy is needed, supporting generalist clinicians to provide personalised, comprehensive continuity of care, especially in socioeconomically deprived areas. Scottish Government Chief Scientist Office. Copyright © 2012 Elsevier Ltd. All rights reserved.

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Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): the TRIPOD statement.

Gary S. Collins, Johannes Reitsma, Douglas G. Altman … (2015)

Prediction models are developed to aid health care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, health care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org).

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Author and article information

Journal

Journal ID (iso-abbrev): J Am Geriatr Soc

Title: Journal of the American Geriatrics Society

Publisher: Wiley

ISSN (Electronic): 1532-5415

ISSN (Print): 0002-8614

Publication date (Electronic): Apr 2023

Volume: 71

Issue: 4

Affiliations

[1 ] Institute of Regional Health Research, University of Southern Denmark, Esbjerg, Denmark.

[2 ] Department of Emergency Medicine, Hospital South West Jutland, University hospital of Southern Denmark, Esbjerg, Denmark.

[3 ] Department of Emergency Medicine, University Hospital Basel, University of Basel, Basel, Switzerland.

[4 ] Department of Emergency Medicine, Washington University in St. Louis School of Medicine, Emergency Care Research Core, St. Louis, Michigan, USA.

[5 ] Department of Cross-sectoral Collaboration, Region of Southern Denmark, Vejle, Denmark.

[6 ] Epidemiology, Biostatistics and Biodemography, Department of Public Health, University of Southern Denmark, Odense, Denmark.

[7 ] Geriatric Research Unit, Department of Geriatric Medicine, Odense University Hospital, Odense, Denmark.

[8 ] Department of Emergency Medicine, Odense University Hospital, Odense, Denmark.

Article

DOI: 10.1111/jgs.18170

PubMed ID: 36511431

SO-VID: 8bedcf88-abcc-4155-b79d-f889892a7410

History

Keywords: prognosis,vital Signs,frailty,geriatric emergency medicinea,Emergency Departments

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Keywords: prognosis, vital Signs, frailty, geriatric emergency medicinea, Emergency Departments

Prognosis for older people at presentation to emergency department based on frailty and aggregated vital signs.

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Preventive and Emergency Medicine Insights

Most cited references 30

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

Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study.

Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): the TRIPOD statement.

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