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BACKGROUND: Studies often ignore time-varying confounding or may use inappropriate methodology to adjust for time-varying confounding. AIM: To estimate the effect of intensive care unit (ICU)-acquired bacteraemia on ICU mortality and discharge using appropriate methodology. METHODS: Marginal structural models with inverse probability weighting were used to estimate the ICU mortality and discharge associated with ICU-acquired bacteraemia among patients who stayed more than two days at the general ICU of a London teaching hospital and remained bacteraemia-free during those first two days. For comparison, the same associations were evaluated with (i) a conventional Cox model, adjusting only for baseline confounders and (ii) a Cox model adjusting for baseline and time-varying confounders. FINDINGS: Using the marginal structural model with inverse probability weighting, bacteraemia was associated with an increase in ICU mortality (cause-specific hazard ratio (CSHR): 1.29; 95% confidence interval (CI): 1.02-1.63) and a decrease in discharge (CSHR: 0.52; 95% CI: 0.45-0.60). By 60 days, among patients still in the ICU after two days and without prior bacteraemia, 8.0% of ICU deaths could be prevented by preventing all ICU-acquired bacteraemia cases. The conventional Cox model adjusting for time-varying confounders gave substantially different results [for ICU mortality, CSHR: 1.08 (95% CI: 0.88-1.32); for discharge, CSHR: 0.68 (95% CI: 0.60-0.77)]. CONCLUSION: In this study, even after adjusting for the timing of acquiring bacteraemia and time-varying confounding using inverse probability weighting for marginal structural models, ICU-acquired bacteraemia was associated with a decreased daily ICU discharge risk and an increased risk of ICU mortality.

Original publication

DOI

10.1016/j.jhin.2017.11.011

Type

Journal

J Hosp Infect

Publication Date

05/2018

Volume

99

Pages

42 - 47

Keywords

Bacteraemia, Bias, Burden, Intensive care units, Inverse probability weighting, Adult, Aged, Aged, 80 and over, Bacteremia, Cohort Studies, Cross Infection, Female, Hospitals, Teaching, Humans, Intensive Care Units, London, Male, Middle Aged, Survival Analysis