An electronic health record-wide association study to identify populations at increased risk of E. coli bacteraemia

Abstract

Objectives

Escherichia coli bacteraemias have been under mandatory surveillance in the UK for fifteen years, but cases continue to rise. Systematic searches of all features present within electronic healthcare records (EHRs), described here as an EHR-wide association study (EHR-WAS), could potentially identify under-appreciated factors that could be targeted to reduce infections.

Methods

We used data from Oxfordshire, UK, and an EHR-WAS method developed for use with large-scale COVID-19 data to estimate associations between E. coli bacteraemia cases, hospital-exposed controls, and 377 potential risk factors using Poisson regression models adjusted for potential confounders for three two-year financial year (FY) periods.

Results

FY2022/23–2023/24 analysis included 757 (0.3%) cases and 276,758 (99.7%) controls. We identified six broad disease areas associated with increased or decreased E. coli bacteraemia risk. Renal/urological/urinary tract infection-related variables had the largest impact, with 47% of cases theoretically removed if these factors could be minimised. Cancer-related variables were associated with higher E. coli bacteraemia risk (1.20 times higher (95%CI 1.08–1.34) per three months closer to chemotherapy in the last year), as were gastrointestinal- and infectious disease-related variables. Cardiac/respiratory-related variables were associated with lower E. coli bacteraemia risk, whereas greater healthcare exposure showed no consistent effect. Associated factors varied across periods, but broad groups remained similar.

Conclusions

Applying an EHR-WAS approach, we show E. coli bacteraemias are largely driven by known risk factors and frailty, highlighting the importance of monitoring these factors and targeting modifiable risks where possible.