Nosocomial Infections Clinical Trial
Official title:
Optimal Antibiotic Treatment of Moderate to Severe Bacterial Infections: Integration of PCR Technology and Medical Informatics/Artificial Intelligence
Severe bacterial infections are associated with mortality of about 30%. Patients with moderate to severe bacterial infections given early and appropriate empirical antibiotic treatment are at a lesser risk for a fatal outcome, with odds ratios ranging from 1.6 to 6.9. However only about 2/3 of patients worldwide are given early and appropriate empirical antibiotic treatment. About 40% of patients treated with antibiotics are given superfluous treatment. TREAT is a computerized decision support system for antibiotic treatment in inpatients with common bacterial infections. TREAT is based on a state of the art stochastic model of the domain (a causal probabilistic network) and uses a cost benefit model for antibiotic treatment, including costs assigned to future resistance. It was tested in a randomized controlled trial in 3 countries and shown to improve the percentage of appropriate empirical antibiotic treatment while at the same time reduce hospital stay and the use of broad-spectrum antibiotics. The main limitation of TREAT is inherent in the limited information available within hours of presentation. A second attractive approach to improve antibiotic treatment is to use techniques that do not depend on cultures, and thus shorten the time to identification of the pathogen to a few hours only. The LightCycler® SeptiFast test from Roche performs in vitro nucleic acid amplification test for pathogens causing bloodstream infections. The purpose of the clinical trial is to show that the combined system TREAT/PCR assays will improve the outcome of inpatients with moderate to severe bacterial infections, while at the same time reducing the use of broad-spectrum antibiotics, with no or little additional costs. A secondary objective will be to assess the sensitivity and specificity of whole blood PCR, using TREAT as the reference standard.
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