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Measuring Frailty in HIV-infected Individuals. Identification of Frail Patients is the First Step to Amelioration and Reversal of Frailty
Published on: July 24, 2013
Development and validation of an electronic health record-based frailty index in the UK Biobank
Grace I Bowman1,2,3, Nigel Seymour4,5, Chandra Reynolds1,6
1Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, United States.
Background:
Frailty, 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.
Methods:
We 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.
Results:
Mean 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).
Conclusions:
This 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.
