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Background: Current strategies for risk stratification and prediction of neonatal early-onset sepsis (EOS) are inefficient and lack diagnostic performance. The aim of this study was to use machine learning to analyze the diagnostic accuracy of risk factors (RFs), clinical signs and biomarkers and to develop a prediction model for culture-proven EOS. We hypothesized that the contribution to diagnostic accuracy of biomarkers is higher than of RFs or clinical signs.Study Design: Secondary analysis of the prospective international multicenter NeoPInS study. Neonates born after completed 34 weeks of gestation with antibiotic therapy due to suspected EOS within the first 72 hours of life participated. Primary outcome was defined as predictive performance for culture-proven EOS with variables known at the start of antibiotic therapy. Machine learning was used in form of a random forest classifier.Results: One thousand six hundred eighty-five neonates treated for suspected infection were analyzed. Biomarkers were superior to clinical signs and RFs for prediction of culture-proven EOS. C-reactive protein and white blood cells were most important for the prediction of the culture result. Our full model achieved an area-under-the-receiver-operating-characteristic-curve of 83.41% (±8.8%) and an area-under-the-precision-recall-curve of 28.42% (±11.5%). The predictive performance of the model with RFs alone was comparable with random.Conclusions: Biomarkers have to be considered in algorithms for the management of neonates suspected of EOS. A 2-step approach with a screening tool for all neonates in combination with our model in the preselected population with an increased risk for EOS may have the potential to reduce the start of unnecessary antibiotics.

Backgrounds The large, international, randomized controlled NeoPInS trial showed that procalcitonin (PCT)-guided decision making was superior to standard care in reducing the duration of antibiotic therapy and hospitalization in neonates suspected of early-onset sepsis (EOS), without increased adverse events. This study aimed to perform a cost-minimization study of the NeoPInS trial, comparing health care costs of standard care and PCT-guided decision making based on the NeoPInS algorithm, and to analyze subgroups based on country, risk category and gestational age. Methods Data from the NeoPInS trial in neonates born after 34 weeks of gestational age with suspected EOS in the first 72 h of life requiring antibiotic therapy were used. We performed a cost-minimization study of health care costs, comparing standard care to PCT-guided decision making. Results In total, 1489 neonates were included in the study, of which 754 were treated according to PCT-guided decision making and 735 received standard care. Mean health care costs of PCT-guided decision making were not significantly different from costs of standard care (€3649 vs. €3616). Considering subgroups, we found a significant reduction in health care costs of PCT-guided decision making for risk category ‘infection unlikely’ and for gestational age ≥ 37 weeks in the Netherlands, Switzerland and the Czech Republic, and for gestational age Conclusions Health care costs of PCT-guided decision making of term and late-preterm neonates with suspected EOS are not significantly different from costs of standard care. Significant cost reduction was found for risk category ‘infection unlikely,’ and is affected by both the price of PCT-testing and (prolonged) hospitalization due to SAEs.

BACKGROUND Neonatal early-onset sepsis (EOS) is one of the main causes of global neonatal mortality and morbidity, and initiation of early antibiotic treatment is key. However, antibiotics may be harmful. METHODS We performed a secondary analysis of results from the Neonatal Procalcitonin Intervention Study, a prospective, multicenter, randomized, controlled intervention study. The primary outcome was the diagnostic accuracy of serial measurements of C-reactive protein (CRP), procalcitonin (PCT), and white blood count (WBC) within different time windows to rule out culture-positive EOS (proven sepsis). RESULTS We analyzed 1678 neonates with 10 899 biomarker measurements (4654 CRP, 2047 PCT, and 4198 WBC) obtained within the first 48 hours after the start of antibiotic therapy due to suspected EOS. The areas under the curve (AUC) comparing no sepsis vs proven sepsis for maximum values of CRP, PCT, and WBC within 36 hours were 0.986, 0.921, and 0.360, respectively. The AUCs for CRP and PCT increased with extended time frames up to 36 hours, but there was no further difference between start to 36 hours vs start to 48 hours. Cutoff values at 16 mg/L for CRP and 2.8 ng/L for PCT provided a sensitivity of 100% for discriminating no sepsis vs proven sepsis. CONCLUSIONS Normal serial CRP and PCT measurements within 36 hours after the start of empiric antibiotic therapy can exclude the presence of neonatal EOS with a high probability. The negative predictive values of CRP and PCT do not increase after 36 hours., + ID der Publikation: unilu_51625 + Sprache: Englisch + Letzte Aktualisierung: 2021-04-26 13:29:30

Biomarkers have become an integral part of the clinical decision-making process of clinicians dealing with febrile children. C-reactive protein, procalcitonin and white blood cell count are probably the most studied ones. Crucial to using biomarkers is the understanding of how a test result will alter post-test probabilities and then impact on clinical decision making. Improved analytical and computational platforms have enabled the next generation of advanced biomarker discovery studies. Promising combinations of candidate biomarkers for a diverse spectrum of febrile illnesses, such as viral and bacterial infections, have been identified using proteomics, RNA gene expression and metabolomics.

Background Up to 7% of term and late-preterm neonates in high-income countries receive antibiotics during the first 3 days of life because of suspected early-onset sepsis. The prevalence of culture-proven early-onset sepsis is 0·1% or less in high-income countries, suggesting substantial overtreatment. We assess whether procalcitonin-guided decision making for suspected early-onset sepsis can safely reduce the duration of antibiotic treatment. Methods We did this randomised controlled intervention trial in Dutch (n=11), Swiss (n=4), Canadian (n=2), and Czech (n=1) hospitals. Neonates of gestational age 34 weeks or older, with suspected early-onset sepsis requiring antibiotic treatment were stratified into four risk categories by their treating physicians and randomly assigned [1:1] using a computer-generated list stratified per centre to procalcitonin-guided decision making or standard care-based antibiotic treatment. Neonates who underwent surgery within the first week of life or had major congenital malformations that would have required hospital admission were excluded. Only principal investigators were masked for group assignment. Co-primary outcomes were non-inferiority for re-infection or death in the first month of life (margin 2·0%) and superiority for duration of antibiotic therapy. Intention-to-treat and per-protocol analyses were done. This trial was registered with ClinicalTrials.gov, number NCT00854932. Findings Between May 21, 2009, and Feb 14, 2015, we screened 2440 neonates with suspected early-onset sepsis. 622 infants were excluded due to lack of parental consent, 93 were ineligible for reasons unknown (68), congenital malformation (22), or surgery in the first week of life (3). 14 neonates were excluded as 100% data monitoring or retrieval was not feasible, and one neonate was excluded because their procalcitonin measurements could not be taken. 1710 neonates were enrolled and randomly assigned to either procalcitonin-guided therapy (n=866) or standard therapy (n=844). 1408 neonates underwent per-protocol analysis (745 in the procalcitonin group and 663 standard group). For the procalcitonin group, the duration of antibiotic therapy was reduced (intention to treat: 55·1 vs 65·0 h, p

Early diagnosis and timely treatment of early onset neonatal sepsis (EOS) are essential to prevent life threatening complications. Subtle, nonspecific clinical presentation and low predictive values of biomarkers complicate early diagnosis. This uncertainty commonly results in unnecessary and prolonged empiric antibiotic treatment. Annually, approximately 395,000 neonates (7.9% of live term births) are treated for suspected EOS in the European Union, while the incidence of proven EOS varies between 0.01 and 0.53 per 1000 live births. Adherence to guidelines for the management of suspicion of EOS is poor. Pragmatic approaches to minimise overtreatment in neonates with suspected EOS, using combined stratified risk algorithms, based on maternal and perinatal risk factors, clinical characteristics of the neonate and sequential biomarkers are promising.