Predictors of healthcare associated infections and their role on mortality in an intensive care unit

Background: Healthcare associated Infections (HAIs) represent a significant burden in terms of mortality, morbidity, length of stay and costs for patients in intensive care units (ICUs). In this study, we analyzed the predictors of HAIs development and assessed the HAIs association with mortality. Data were retrieved from a general ICU active surveillance system of a large teaching hospital in Rome. Methods: Logistic regression models were built to quantify the association between demographic and clinical factors and the development of HAIs, device-related HAIs and Multi Drug Resistant (MDR)-associated HAIs. The HAIs independent predictors were used to create propensity scores (PS) specific for each model, that was subsequently used to adjust the association between these conditions and mortality in logistic regression models. Results: From May 2016 to September 2019, 864 patients were included in the surveillance system, 236 (27.3%) of which had at least one HAI during their hospitalization. Specifically, 162 (18.8%) patients had at least a device-related HAI and the overall mortality rate was 34.3%. Factors associated with the HAIs and the device-related HAIs were mechanical ventilation and admission for trauma. The PS-adjusted logistic models showed an association between HAI and device-related HAI and mortality (OR 1.82, 95%CI 1.30-2.54; OR 2.03, 95%CI 1.40-2.95, respectively). MDR-associated HAIs had a significant association with diabetes mellitus; however, these infections weren’t associated with mortality (OR 1.42, 95%CI 0.98-2.08), even in the subgroup of infected patients (OR 0.99, 95%CI 0.56-1.73). Conclusions: The study confirms the association between HAIs and devicerelated HAIs with mortality in ICUs. Apparently, MDRassociated infection subset appears not having a specific association with mortality. However, given the extra effort that these infections require to be managed, they should be adequately surveilled and contrasted.