Prediction of risk of acquiring urinary tract infection during hospital stay based on machine-learning: A retrospective cohort study.
Journal:
PloS one
PMID:
33788888
Abstract
BACKGROUND: Healthcare associated infections (HAI) are a major burden for the healthcare system and associated with prolonged hospital stay, increased morbidity, mortality and costs. Healthcare associated urinary tract infections (HA-UTI) accounts for about 20-30% of all HAI's, and with the emergence of multi-resistant urinary tract pathogens, the total burden of HA-UTI will most likely increase.