Daniel Stow
Evaluating frailty scores to predict mortality in older adults using data from population based electronic health records: Case control study
Stow, Daniel; Matthews, Fiona E.; Barclay, Stephen; Iliffe, Steve; Clegg, Andrew; De Biase, Sarah; Robinson, Louise; Hanratty, Barbara
Authors
Professor Fiona Matthews F.Matthews@hull.ac.uk
Pro-Vice-Chancellor Research and Enterprise
Stephen Barclay
Steve Iliffe
Andrew Clegg
Sarah De Biase
Louise Robinson
Barbara Hanratty
Abstract
Background: recognising that a patient is nearing the end of life is essential, to enable professional carers to discuss prognosis and preferences for end of life care. Objective: investigate whether an electronic frailty index (eFI) generated from routinely collected data, can be used to predict mortality at an individual level. Design: historical prospective case control study. Setting: UK primary care electronic health records. Subjects: 13,149 individuals age 75 and over who died between 01/01/2015 and 01/01/2016, 1:1 matched by age and sex to individuals with no record of death in the same time period. Methods: two subsamples were randomly selected to enable development and validation of the association between eFI 3 months prior to death and mortality. Receiver operator characteristic (ROC) analyses were used to examine diagnostic accuracy of eFI at 3 months prior to death. Results: an eFI > 0.19 predicted mortality in the development sample at 75% sensitivity and 69% area under received operating curve (AUC). In the validation dataset this cut point gave 76% sensitivity, 53% specificity. Conclusions: the eFI measured at a single time point has low predictive value for individual risk of death, even 3 months prior to death. Although the eFI is a strong predictor or mortality at a population level, its use for individuals is far less clear.
Citation
Stow, D., Matthews, F. E., Barclay, S., Iliffe, S., Clegg, A., De Biase, S., …Hanratty, B. (2018). Evaluating frailty scores to predict mortality in older adults using data from population based electronic health records: Case control study. Age and ageing, 47(4), 564-569. https://doi.org/10.1093/ageing/afy022
Journal Article Type | Article |
---|---|
Publication Date | Jul 1, 2018 |
Deposit Date | Dec 8, 2023 |
Journal | Age and Ageing |
Print ISSN | 0002-0729 |
Electronic ISSN | 1468-2834 |
Publisher | Oxford University Press |
Volume | 47 |
Issue | 4 |
Pages | 564-569 |
DOI | https://doi.org/10.1093/ageing/afy022 |
Public URL | https://hull-repository.worktribe.com/output/4452665 |
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