Key Predictive Features in the Emergency Department for Healthcare-Associated Infections

Background Overcrowding, prolonged stays and invasive interventions could increase the risk of healthcare-associated infections (HAIs) in Emergency Departments (ED). Aim of study was to investigate whether the risk of developing a HAI can be estimated in patients at entry on the basis of ED visit data, and whether they are associated with poorer outcome. Methods This retrospective single centre study included subjects who required urgent hospitalisation following ED visit between 2017 and 2022. Main outcome measures considered were the occurrence of late HAIs and the cumulative survival rate at 30 days. The key predictive features tested in a logistic model were age, sex, vital parameters as measured by the National Early Warning Score (NEWS), priority levels upon entry, comorbidities by the Charlson Comorbidity Index (CCI), trauma related diseases, main diagnosis and ED length of stay. Results In 2,556 (8,9%) out of 28,803 hospitalised patients aged 73 [17] years (mean [SD]) a diagnosis of HAI was recorded during hospital stays. In order of frequency, HAIs occurred in bloodstream (4.7%), in urinary (3.4%), respiratory (2.9%), gastrointestinal (0.4%) tract, or in surgical (0.3%) and skin and soft tissue (0.05%) sites. Main features selected by the logistic model in the prediction of HAI were infectious and parasitic diseases, CCI > 4, genitourinary system diseases, CCI 3 to 4, COVID period, priority level at arrival in ED. In-hospital cumulative survival rate in HAI group was reduced, namely for subjects with pneumonia and bloodstream infections. Conclusions A group of key characteristics in subjects visiting the ED can predict the onset of nosocomial infections that negatively affect survival, particularly for patients who develop pneumonia or bloodstream infections.