CLABSI seasonal variation
Abstract:
Background: Hospital-acquired bloodstream infections (HABSIs) cause increased morbidity, mortality, and hospital costs that are partially preventable. HABSI seasonality has been described for gram-negative bacteria but has not been stratified per infection origin.
Objective: To assess seasonality among all types of HABSIs and their associations with climate.
Methods: Hospitals performing surveillance for at least 1 full calendar year between 2000 and 2014 were included. Mixed-effects negative binomial regression analysis calculated the peak-to-low monthly ratio as an adjusted HABSI incidence rate ratio (IRR) with 95% confidence intervals (CIs). Another regression model examined associations between HABSI rates and climate variables. These analyses were stratified by microorganism and infectious origin.
Results: The study population included 104 hospitals comprising 44,111 HABSIs. Regression analysis identified an incidence rate ratio (IRR) peak in August for gram-negative HABSIs (IRR, 1.59; 95% CI, 1.49-1.71), CLABSIs (IRR, 1.49; 95% CI, 1.30-1.70), and urinary tract HABSI (IRR, 1.52; 95% CI, 1.34-1.74). The gram-negative incidence increased by 13.1% (95% CI, 9.9%-16.4%) for every 5°C increase in temperature. Seasonality was most present among E. coli, K. pneumoniae, E. cloacae, and the nonfermenters. Gram-positive and pulmonary HABSIs did not demonstrate seasonal variation.
Conclusions: Seasonality with summer spikes occurred among gram-negative bacteria, CLABSIs, and urinary tract HABSIs. Higher ambient temperature was associated with gram-negative HABSI rates. The preventable causative factors for seasonality, such as the nurse-to-patient ratio, indoor room temperature or device-utilization, need to be examined to assess areas for improving patient safety.
Reference:
Blot K, Hammami N, Blot S, Vogelaers D, Lambert ML. Seasonal variation of hospital-acquired bloodstream infections: A national cohort study. Infect Control Hosp Epidemiol. 2021 May 12:1-7. doi: 10.1017/ice.2021.85. Epub ahead of print. PMID: 33975668.