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BACKGROUND: frailty has only recently been recognised as important in patients with heart failure (HF), but little has been done to predict the first hospitalisation after diagnosis in unselected primary care populations. OBJECTIVES: to predict the first unplanned HF or all-cause admission after diagnosis, comparing the effects of co-morbidity and frailty, the latter measured by the recently validated electronic frailty index (eFI). DESIGN: observational study. SETTING: primary care in England. SUBJECTS: all adult patients diagnosed with HF in primary care between 2010 and 2013. METHODS: we used electronic health records of patients registered with primary care practices sending records to the Clinical Practice Research Datalink (CPRD) in England with linkage to national hospital admissions and death data. Competing-risk time-to-event analyses identified predictors of first unplanned hospitalisation for HF or for any condition after diagnosis. RESULTS: of 6,360 patients, 9% had an emergency hospitalisation for their HF, and 39% had one for any cause within a year of diagnosis; 578 (9.1%) died within a year without having any emergency admission. The main predictors of HF admission were older age, elevated serum creatinine and not being on a beta-blocker. The main predictors of all-cause admission were age, co-morbidity, frailty, prior admission, not being on a beta-blocker, low haematocrit and living alone. Frailty effects were largest in patients aged under 85. CONCLUSIONS: this study suggests that frailty has predictive power beyond its co-morbidity components. HF patients in the community should be assessed for frailty, which should be reflected in future HF guidelines.

Original publication




Journal article


Age Ageing

Publication Date





347 - 354


CPRD, emergency hospitalisation, frailty, heart failure, older people, Adult, Age Factors, Aged, Aged, 80 and over, Comorbidity, Creatinine, Female, Frail Elderly, Heart Failure, Hospitalization, Humans, Male, Middle Aged, Primary Health Care, Risk Factors, Time Factors