ArticleBMC pediatrics2009
Clinical parameters predicting failure of empirical antibacterial therapy in early onset neonatal sepsis, identified by classification and regression tree analysis.
Article in BMC pediatrics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 31 citations in OpenAlex.
- Predictors of gentamicin therapy failure in neonates with sepsis.Pharmacology research & perspectives · 2024Article
- Confirming the Suitability of a Gentamicin Dosing Strategy in Neonates Using the Population Pharmacokinetic Approach with Truncated Sampling Duration.Children (Basel, Switzerland) · 2024Article
- Machine learning applications on neonatal sepsis treatment: a scoping review.BMC infectious diseases · 2023Article
- Predicting risk of sepsis, comparison between machine learning methods: a case study of a Virginia hospital.European journal of medical research · 2022Article
- State of the Art of Machine Learning-Enabled Clinical Decision Support in Intensive Care Units: Literature Review.JMIR medical informatics · 2022Review
- Factors associated with the risk of positive blood culture in neonatal foals presented to a referral center (2000-2014).Journal of veterinary internal medicine · 2020Article
- A Prospective Cohort Study of Factors Associated with Empiric Antibiotic De-escalation in Neonates Suspected with Early Onset Sepsis (EOS).Paediatric drugs · 2020Article
- Empirical use of antibiotic therapy in the prevention of early onset sepsis in neonates: a pilot study.Archives of medical science : AMS · 2016Article
- Article
- High DMBT1 concentrations in breast milk correlate with increased risk of infection in preterm and term neonates.BMC pediatrics · 2012Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAbout 10-20% of neonates with suspected or proven early onset sepsis (EOS) fail on the empiric antibiotic regimen of ampicillin or penicillin and gentamicin. We aimed to identify clinical and laboratory markers associated with empiric antibiotic treatment failure in neonates with suspected EOS.
methodsMaternal and early neonatal characteristics predicting failure of empiric antibiotic treatment were identified by univariate logistic regression analysis from a prospective database of 283 neonates admitted to neonatal intensive care unit within 72 hours of life and requiring antibiotic therapy with penicillin or ampicillin and gentamicin. Variables, identified as significant by univariate analysis, were entered into stepwise multiple logistic regression (MLR) analysis and classification and regression tree (CRT) analysis to develop a decision algorithm for clinical application. In order to ensure the earliest possible timing separate analysis for 24 and 72 hours of age was performed.
resultsAt 24 hours of age neonates with hypoglycaemia < or = 2.55 mmol/L together with CRP values > 1.35 mg/L or those with BW < or = 678 g had more than 30% likelihood of treatment failure. In normoglycaemic neonates with higher BW the best predictors of treatment failure at 24 hours were GA < or = 27 weeks and among those, with higher GA, WBC < or = 8.25 x 10(9) L(-1) together with platelet count < or = 143 x 10(9) L(-1). The algorithm allowed capture of 75% of treatment failure cases with a specificity of 89%. By 72 hours of age minimum platelet count < or = 94.5 x 10(9) L(-1) with need for vasoactive treatment or leukopaenia < or = 3.5 x 10(9) L(-1) or leukocytosis > 39.8 x 10(9) L(-1) or blood glucose < or = 1.65 mmol/L allowed capture of 81% of treatment failure cases with the specificity of 88%. The performance of MLR and CRT models was similar, except for higher specificity of the CRT at 72 h, compared to MLR analysis.
conclusionThere is an identifiable group of neonates with high risk of EOS, likely to fail on conventional antibiotic therapy.
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