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Published on: February 16, 2024
Candidaemia and a risk predictive model for overall mortality: a prospective multicentre study
C Keighley1,2,3, S C-A Chen4,5,6, D Marriott7
1Centre for Infectious Diseases and Microbiology Laboratory Services, ICPMR, New South Wales Health Pathology, Westmead Hospital, Darcy Rd, 3rd Level, ICPMR Building, Westmead, Sydney, New South Wales, 2145, Australia. Caitlin.keighley@sydney.edu.au.
Background:
Candidaemia is associated with high mortality. Variables associated with mortality have been published previously, but not developed into a risk predictive model for mortality. We sought to describe the current epidemiology of candidaemia in Australia, analyse predictors of 30-day all-cause mortality, and develop and validate a mortality risk predictive model.
Methods:
Adults with candidaemia were studied prospectively over 12 months at eight institutions. Clinical and laboratory variables at time of blood culture-positivity were subject to multivariate analysis for association with 30-day all-cause mortality. A predictive score for mortality was examined by area under receiver operator characteristic curves and a historical data set was used for validation.
Results:
The median age of 133 patients with candidaemia was 62 years; 76 (57%) were male and 57 (43%) were female. Co-morbidities included underlying haematologic malignancy (n = 20; 15%), and solid organ malignancy in (n = 25; 19%); 55 (41%) were in an intensive care unit (ICU). Non-albicans Candida spp. accounted for 61% of cases (81/133). All-cause 30-day mortality was 31%. A gastrointestinal or unknown source was associated with higher overall mortality than an intravascular or urologic source (p < 0.01). A risk predictive score based on age > 65 years, ICU admission, chronic organ dysfunction, preceding surgery within 30 days, haematological malignancy, source of candidaemia and antibiotic therapy for ≥10 days stratified patients into < 20% or ≥ 20% predicted mortality. The model retained accuracy when validated against a historical dataset (n = 741).
Conclusions:
Mortality in patients with candidaemia remains high. A simple mortality risk predictive score stratifying patients with candidaemia into < 20% and ≥ 20% 30-day mortality is presented. This model uses information available at time of candidaemia diagnosis is easy to incorporate into decision support systems. Further validation of this model is warranted.
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