Evidence map›Paper›PMID 42166742›Full record

ArticleThe journals of gerontology. Series A, Biological sciences and medical sciences2026

Development and validation of an electronic health record-based frailty index in the UK Biobank.

Grace I Bowman, Nigel Seymour, Chandra Reynolds, Luke M Evans

Abstract readValidation Study
In one paragraph

Article in The journals of gerontology. Series A, Biological sciences and medical sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Grace I BowmanInstitute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, United States.ORCID 0009-0007-5394-7520
Nigel SeymourDepartment of Mathematics and Statistics, College of Natural and Mathematical Sciences, University of Maryland, Baltimore County, Baltimore, Maryland, United States.
Chandra ReynoldsInstitute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, United States.ORCID 0000-0001-6502-7173
Luke M EvansInstitute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, United States.

Funding

PetaLibrary and computational analysis was supported by the Blanca and Alpine high performance computing resources at the University of Colorado BoulderUniversity of Colorado Boulder, the University of Colorado Anschutz, and Colorado State University
6 · The paper itself

Abstract

backgroundFrailty, an age-related loss of the ability to withstand stressors, is commonly measured using health deficit indices, often using survey or questionnaire data. We aimed to develop an electronic frailty index (eFI) using electronic health record (EHR) data linkages in the UK Biobank and assess its association with mortality.

methodsWe calculated an eFI using 43 deficits, each corresponding to phecodes mapped to the United Kingdom (UK) and international classification coding systems. We compared this eFI to a validated 49-item survey-based FI for the UK Biobank (UKB) and assessed associations of the eFI with risk of all-cause mortality (follow-up ≤ 10.2 years) and mortality following a stressor (heart attack or stroke) using Cox proportional hazard models.

resultsMean eFI in this cohort (N = 208,982) was 0.058 (SD = 0.06) and was higher in females than males. A 10% higher baseline frailty was associated with higher risk of all-cause mortality (HR (95% CI)=2.00 (1.93-2.07)), although the magnitude of this association decreased when adjusting for socioeconomic-related covariates (HR (95% CI)=1.44 (1.38-1.51)). Associations were stronger in men than women. Electronic frailty index predicted mortality following both heart attack and stroke (HR (95% CI) = 1.59 (1.25-2.04) and HR = 1.33 (1.13-1.57), respectively).

conclusionsThis EHR-based eFI has robust associations with mortality, suggesting that it can be used as a valid measure of frailty in the UKB and can potentially be applied to other datasets with EHR data.

Indexed as

Electronic Health RecordsFrailtyGeriatric AssessmentAgedBiological Specimen BanksFemaleHumansMaleProportional Hazards ModelsUK BiobankUnited KingdomDeficit accumulationElectronic health recordsFrailty

Identifiers

PMID42166742
PMCPMC13643490

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.