Computerized vital signs analysis and late onset infections in extremely low gestational age infants.

AIM: Current clinical and laboratory diagnostics for neonatal infection are inadequate. An infant's systemic inflammatory response may be identified earlier than clinical suspicion by a computerized algorithm (RALIS) incorporating multiple vital signs (VS). We tested the ability of RALIS to detect late onset infection (LOI) earlier than clinically suspected.

METHODS: We conducted a retrospective review of infants enrolled in a birth cohort study at Prentice Women's Hospital. VS data (heart rate, respirations, temperature, desaturation, bradycardia) were extracted from electronic records of 73 premature infants (born ≤28 weeks' gestation; survived first month). RALIS generated a continuous output for the first 28 days of life. A score ≥5 for 6 h triggered an alert. The time of RALIS alert to time of clinical suspicion of infection (time culture sent) was measured for each episode of suspected and/or confirmed LOI.

RESULTS: Among the 73 infants followed with RALIS, there were 34 episodes of culture-positive LOI, seven culture-negative but treated episodes, and 13 false-positive culture (untreated) episodes. Twenty-five infants had no culture-positive or treated sepsis events during the observation period. There was a positive linear association between alert and culture (β=0.88, P<0.001). Mean absolute time difference between alert and culture was 59.4 h before culture. Sensitivity and specificity of RALIS for LOI were 0.82 and 0.44.

CONCLUSION: The RALIS algorithm is a sensitive indicator for early detection of infection in preterm infants. Further modifications to improve the specificity of the algorithm are needed prior to application of VS modeling to patient antibiotic treatment decisions.