Standardized infection ratio: Can we still reliably use the national invasive device- associated infection models in intensive care units in Turkey?
Abstract
Objective: Standardized infection ratio (SIR) for ventilator-associated pneumonia (VAP), central line-associated bloodstream infection (CLABSI) and catheter-associated urinary tract infection (CAUTI) has been calculated using formulas obtained from the national models in Turkey since 2016. we aimed to evaluate the current usability of the national models by using 2020 data and whether the models need to be updated. Methods: The database used for The National HAI Surveillance Network Summary Report 2020 was used for remodelling. For each type of infection, remodeling was performed with 2020 data using the variables in the national models. The number of CLABSIs, CAUTIs and VAPs was the dependent variable for each negative binomial model with a logarithmic link function. Incidence rate ratios (IRRs) from the repeated models were compared with the national models using 95% confidence intervals. Results: In each model, all variables in the national models were again statistically significant (ps<0.05). Although the IRRs were similar for most of the risk factors, the size of the risk for some of them changed significantly between the national models and our models. In the national VAP and CAUTI model, the reference category for hospital type was private hospitals, while in our models, it was state hospitals. In addition, the IRRs for CAUTI in state hospitals, training and research hospitals and university hospitals were significantly lower than in the national model. Conclusion: It is necessary to update the coefficients used in the calculation of the predicted infection numbers in the SIR formulas, especially for VAP and CAUTI.
Keywords
central line-associated bloodstream infection, ventilator-associated pneumonia, catheter-associated urinary tract infection
Thanks
The authors thank to all infection control nurses and physicians in all hospitals in Turkey for providing these data.
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