Bacterial Infection Clinical Trial
Official title:
Contribution of Computerized Real Time Analyses of Cardio-respiratory Signals to the Diagnosis of Infection in Preterm Infants
Hospital-acquired infections are common complications in preterm infants. The diagnosis has
to be fast and accurate. Indeed, the early identification of a suspected infection is very
important, since the early administration of antibiotics lowers the risk of septic shock and
improves long term outcome in the infected newborns who survive. Besides, a high specificity
in the diagnosis of infection allows for the reduction of inappropriate treatment and thus
prevents the emergence of antibiotic resistance.
The aim of this study is to develop a computer-assisted diagnosis tool, based on the real
time analysis of cardio-respiratory signals, to aid the neonatologist in the diagnosis of
infection of the preterm infant, at the bedside.
Hospital-acquired infections increase morbidity and mortality in the preterm infants. Early
diagnosis of infection is difficult mainly due to the poor performance of clinical signs and
to the need for invasive procedure to get blood tests. However, early administration of
antibiotics lowers the risk of septic shock and improves long term outcome in the infected
newborns who survive. Many clinical features have been described, associated with an ongoing
infection but they are inconsistent, variable and nonspecific. Similarly, many invasive
laboratory tests have been proposed for the diagnosis of infection in the newborn but they
all need blood sampling and none has a good predictive value.
The combined analysis of the heart rate and respiratory characteristics appears to be a
promising tool for the diagnosis of infection in the preterm infants. These signals are
non-invasively recorded and their computerized real time analyses would allow for a
continuous assessment of the risk of infection.
The main objective is to test the hypothesis that the analyses of the variability of the
cardiac cycle duration, the variability of the respiratory cycle amplitude and duration, and
their relationships, can significantly improve the performance of the diagnosis of late onset
infection in the preterm infant at the bedside in neonatal units.
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