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dc.contributor.authorStow, Danielen
dc.contributor.authorMatthews, Fiona Een
dc.contributor.authorBarclay, Stephenen
dc.contributor.authorIliffe, Steveen
dc.contributor.authorClegg, Andrewen
dc.contributor.authorDe Biase, Sarahen
dc.contributor.authorRobinson, Louiseen
dc.contributor.authorHanratty, Barbaraen
dc.date.accessioned2018-02-09T14:46:05Z
dc.date.available2018-02-09T14:46:05Z
dc.date.issued2018-07en
dc.identifier.issn0002-0729
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/271862
dc.description.abstractBackground: 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.
dc.format.mediumPrinten
dc.languageengen
dc.rightsAttribution-NonCommercial 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/
dc.subjectHumansen
dc.subjectPrognosisen
dc.subjectGeriatric Assessmenten
dc.subjectSeverity of Illness Indexen
dc.subjectRisk Assessmenten
dc.subjectRisk Factorsen
dc.subjectCase-Control Studiesen
dc.subjectProspective Studiesen
dc.subjectReproducibility of Resultsen
dc.subjectPredictive Value of Testsen
dc.subjectAge Factorsen
dc.subjectAgingen
dc.subjectTime Factorsen
dc.subjectAgeden
dc.subjectAged, 80 and overen
dc.subjectFemaleen
dc.subjectMaleen
dc.subjectElectronic Health Recordsen
dc.subjectUnited Kingdomen
dc.subjectFrailtyen
dc.titleEvaluating frailty scores to predict mortality in older adults using data from population based electronic health records: case control study.en
dc.typeArticle
prism.endingPage569
prism.issueIdentifier4en
prism.publicationDate2018en
prism.publicationNameAge and ageingen
prism.startingPage564
prism.volume47en
dc.identifier.doi10.17863/CAM.18869
dcterms.dateAccepted2018-01-24en
rioxxterms.versionofrecord10.1093/ageing/afy022en
rioxxterms.versionAMen
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.licenseref.startdate2018-07en
dc.contributor.orcidBarclay, Stephen [0000-0002-4505-7743]
dc.contributor.orcidHanratty, Barbara [0000-0002-3122-7190]
dc.identifier.eissn1468-2834
rioxxterms.typeJournal Article/Reviewen
cam.orpheus.successThu Jan 30 12:59:42 GMT 2020 - The item has an open VoR version.*
rioxxterms.freetoread.startdate2100-01-01


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Attribution-NonCommercial 4.0 International
Except where otherwise noted, this item's licence is described as Attribution-NonCommercial 4.0 International