ArticleBMC infectious diseases2021
Mortality in Escherichia coli bloodstream infections: a multinational population-based cohort study.
Article in BMC infectious diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 1 of them a synthesis that pooled it.
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Who cites it
40 citing papers in PubMed, 1 synthesis or guideline pooled it, 60 citations in OpenAlex.
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- Development and validation of a predictive mortality scoring model for bloodstream infections due to Escherichia coli in the PROBAC cohort.Infection · 2025Article
- Escherichia coli Type III Secretion System 2 Is Associated With Patient Mortality in Bloodstream Infections.The Journal of infectious diseases · 2025Article
- Outcomes of Hospitalized Octogenarians withPathogens (Basel, Switzerland) · 2025Article
- Bacteraemia due to E.coli in urinary tract infections in adults: a prospective epidemiological study following implementation of guidelines in a regional hospital.BMC infectious diseases · 2025Article
- Impact of community-acquired invasive Escherichia coli disease on mortality and readmissions in elderly patients: a multi-center study in Germany.BMC infectious diseases · 2025Article
- Tourism and the Global Vectoring of Antimicrobial-Resistant Disease: What Countries Are Most Impacted?Antibiotics (Basel, Switzerland) · 2025Article
- Epidemiology and risk factors ofEuro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2025Article
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Authors and funding
9 authors at 7 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEscherichia coli is the most common cause of bloodstream infections (BSIs) and mortality is an important aspect of burden of disease. Using a multinational population-based cohort of E. coli BSIs, our objectives were to evaluate 30-day case fatality risk and mortality rate, and determine factors associated with each.
methodsDuring 2014-2018, we identified 30-day deaths from all incident E. coli BSIs from surveillance nationally in Finland, and regionally in Sweden (Skaraborg) and Canada (Calgary, Sherbrooke, western interior). We used a multivariable logistic regression model to estimate factors associated with 30-day case fatality risk. The explanatory variables considered for inclusion were year (2014-2018), region (five areas), age (< 70-years-old, ≥70-years-old), sex (female, male), third-generation cephalosporin (3GC) resistance (susceptible, resistant), and location of onset (community-onset, hospital-onset). The European Union 28-country 2018 population was used to directly age and sex standardize mortality rates. We used a multivariable Poisson model to estimate factors associated with mortality rate, and year, region, age and sex were considered for inclusion.
resultsFrom 38.7 million person-years of surveillance, we identified 2961 30-day deaths in 30,923 incident E. coli BSIs. The overall 30-day case fatality risk was 9.6% (2961/30923). Calgary, Skaraborg, and western interior had significantly increased odds of 30-day mortality compared to Finland. Hospital-onset and 3GC-resistant E. coli BSIs had significantly increased odds of mortality compared to community-onset and 3GC-susceptible. The significant association between age and odds of mortality varied with sex, and contrasts were used to interpret this interaction relationship. The overall standardized 30-day mortality rate was 8.5 deaths/100,000 person-years. Sherbrooke had a significantly lower 30-day mortality rate compared to Finland. Patients that were either ≥70-years-old or male both experienced significantly higher mortality rates than those < 70-years-old or female.
conclusionsIn our study populations, region, age, and sex were significantly associated with both 30-day case fatality risk and mortality rate. Additionally, 3GC resistance and location of onset were significantly associated with 30-day case fatality risk. Escherichia coli BSIs caused a considerable burden of disease from 30-day mortality. When analyzing population-based mortality data, it is important to explore mortality through two lenses, mortality rate and case fatality risk.
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