BACTERIUM: Study for a Machine-learning-based Model to Predict Bloodstream Infections

Condition(s) studied

Investigational drug(s) / intervention(s)

antibiotic treatments: The outcome of the study will be to implement Prediction Models to support clinicians for the assessment of risk of having a bloodstream infection.

Study summary

An increase of healthcare-associated infections caused by multidrug- resistant organisms (MRDO) is currently observed. One of the main causes of the emergence of a MDRO infection is an overuse of antibiotics. Therefore, saving useless antibiotic treatment is currently a priority from a public health point of view. The evaluation of the risk of having a bloodstream infection will allow both activating faster treatment decisions (when the risk is significantly high) or to save useless resources in terms of diagnostic tests and treatments, also limiting the potential for side effects (when the risk is significantly low).

Eligibility

Primary outcome measure(s)

• Rate of appropriate antibiotic therapy in patients with bloodstream infections — 24 months
  1\) number of patients with bloodstream infections with appropriate antibiotic therapy before and after the application of the predictive model "Bacterium"
• Blood cultures — 24 months
  number of blood cultures done before and after the application of the predictive model "Bacterium"

Trial sites (1)

More Fondazione Policlinico Universitario Agostino Gemelli IRCCS trials in Italy