Effectiveness of an Active and Continuous Surveillance Program for Intensive Care Units Infections Based on the EPIC III (Extended Prevalence of Infection in Intensive Care) Approach.
Giorgia MontrucchioGabriele SalesGiulia CatozziStefano BossoMartina ScanuTitty Vita VignolaAndrea CostamagnaSilvia CorcioneRosario UrbinoClaudia FilippiniFrancesco Giuseppe De RosaLuca BrazziPublished in: Journal of clinical medicine (2022)
We evaluated the effectiveness of the Extended Prevalence of Infection in Intensive Care (EPIC) III data collection protocol as an active surveillance tool in the eight Intensive Care Units (ICUs) of the Intensive and Critical Care Department of the University Hospital of Turin. A total of 435 patients were included in a six-day study over 72 ICU beds. 42% had at least one infection: 69% at one site, 26% at two sites and 5% at three or more sites. ICU-acquired infections were the most common (64%), followed by hospital-associated infections (22%) and community-acquired (20%), considering that each patient may have developed more than one infection type. 72% of patients were receiving at least one antibiotic: 48% for prophylaxis and 52% for treatment. Mortality, the length of ICU and hospital stays were 13%, 14 and 29 days, respectively, being all estimated to be significantly different in patients without and with infection (8% vs. 20%; 4 vs. 20 and 11 vs. 50 ( p < 0.001). Our data confirm a high prevalence of infections, sepsis and the use of antimicrobials. The repeated punctual prevalence survey seems an effective method to carry out the surveillance of infections and the use of antimicrobials in the ICU. The use of the European Centre for Disease Prevention and Control (ECDC) definitions and the EPIC III protocol seems strategic to allow comparisons with national and international contexts.
Keyphrases
- intensive care unit
- end stage renal disease
- randomized controlled trial
- newly diagnosed
- chronic kidney disease
- healthcare
- risk factors
- systematic review
- emergency department
- acute kidney injury
- cardiovascular disease
- mental health
- machine learning
- quality improvement
- big data
- patient reported
- smoking cessation
- extracorporeal membrane oxygenation
- artificial intelligence
- acute care