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Evaluating frailty scores to predict mortality in older adults using data from population based electronic health records: case control study

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 mo...

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Autores principales: Stow, Daniel, Matthews, Fiona E, Barclay, Stephen, Iliffe, Steve, Clegg, Andrew, De Biase, Sarah, Robinson, Louise, Hanratty, Barbara
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6014267/
https://www.ncbi.nlm.nih.gov/pubmed/29546362
http://dx.doi.org/10.1093/ageing/afy022
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author Stow, Daniel
Matthews, Fiona E
Barclay, Stephen
Iliffe, Steve
Clegg, Andrew
De Biase, Sarah
Robinson, Louise
Hanratty, Barbara
author_facet Stow, Daniel
Matthews, Fiona E
Barclay, Stephen
Iliffe, Steve
Clegg, Andrew
De Biase, Sarah
Robinson, Louise
Hanratty, Barbara
author_sort Stow, Daniel
collection PubMed
description 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
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spelling pubmed-60142672018-06-27 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 Age Ageing Research Paper 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 Oxford University Press 2018-07 2018-03-13 /pmc/articles/PMC6014267/ /pubmed/29546362 http://dx.doi.org/10.1093/ageing/afy022 Text en © The Author(s) 2018. Published by Oxford University Press on behalf of the British Geriatrics Society. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Research Paper
Stow, Daniel
Matthews, Fiona E
Barclay, Stephen
Iliffe, Steve
Clegg, Andrew
De Biase, Sarah
Robinson, Louise
Hanratty, Barbara
Evaluating frailty scores to predict mortality in older adults using data from population based electronic health records: case control study
title Evaluating frailty scores to predict mortality in older adults using data from population based electronic health records: case control study
title_full Evaluating frailty scores to predict mortality in older adults using data from population based electronic health records: case control study
title_fullStr Evaluating frailty scores to predict mortality in older adults using data from population based electronic health records: case control study
title_full_unstemmed Evaluating frailty scores to predict mortality in older adults using data from population based electronic health records: case control study
title_short Evaluating frailty scores to predict mortality in older adults using data from population based electronic health records: case control study
title_sort evaluating frailty scores to predict mortality in older adults using data from population based electronic health records: case control study
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6014267/
https://www.ncbi.nlm.nih.gov/pubmed/29546362
http://dx.doi.org/10.1093/ageing/afy022
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