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Objective: Hyperoxia is associated with adverse outcome in severe traumatic brain injury (TBI). This study explored differences in patient classification of oxygen exposure by PaO2 cutoff and cumulative areaunder-the-curve (AUC) analysis. Methods: Retrospective, explorative study including children (<18 years) with accidental severe TBI (2002–2015). Oxygen exposure analysis used three PaO2 cutoff values and four PaO2 AUC categories during the first 24 hours of Pediatric Intensive Care Unit (PICU) admission. Results: Seventy-one patients were included (median age 8.9 years [IQR 4.6–12.9]), mortality 18.3% (n = 13). Patient hyperoxia classification differed depending on PaO2 cutoff vs AUC analysis: 52% vs. 26%, respectively, were classified in the highest hyperoxia category. Eleven patients (17%) classified as ‘intermediate oxygen exposure’ based on cumulative PaO2 analysis whereby they did not exceed the 200 mmHg PaO2 cutoff threshold. Patient classification variability was reflected by Pearson correlation coefficient of 0.40 (p-value 0.001). Conclusions: Hyperoxia classification in pediatric severe TBI during the first 24 hours of PICU admission differed depending on PaO2 cutoff or cumulative AUC analysis. We consider PaO2 cumulative (AUC) better approximates (patho-)physiological circumstances due to its time- and dose-dependent approach. Prospective studies exploring the association between cumulative PaO2, physiological parameters (e.g. ICP, PbtO2) and outcome are warranted as different patient classifications of oxygen exposure influences how its relationship to outcome is interpreted.

Background: Phenobarbital and midazolam are commonly used drugs in (near-)term neonates treated with therapeutic hypothermia for hypoxic-ischaemic encephalopathy, for sedation, and/or as anti-epileptic drug. Phenobarbital is an inducer of cytochrome P450 (CYP) 3A, while midazolam is a CYP3A substrate. Therefore, co-treatment with phenobarbital might impact midazolam clearance. Objectives: To assess pharmacokinetics and clinical anti-epileptic effectiveness of phenobarbital and midazolam in asphyxiated neonates and to develop dosing guidelines. Methods: Data were collected in the prospective multicentre PharmaCool study. In the present study, neonates treated with therapeutic hypothermia and receiving midazolam and/or phenobarbital were included. Plasma concentrations of phenobarbital and midazolam including its metabolites were determined in blood samples drawn on days 2–5 after birth. Pharmacokinetic analyses were performed using non-linear mixed effects modelling; clinical effectiveness was defined as no use of additional anti-epileptic drugs. Results: Data were available from 113 (phenobarbital) and 118 (midazolam) neonates; 68 were treated with both medications. Only clearance of 1-hydroxy midazolam was influenced by hypothermia. Phenobarbital co-administration increased midazolam clearance by a factor 2.3 (95% CI 1.9–2.9, p < 0.05). Anticonvulsant effectiveness was 65.5% for phenobarbital and 37.1% for addon midazolam. Conclusions: Therapeutic hypothermia does not influence clearance of phenobarbital or midazolam in (near-)term neonates with hypoxic-ischaemic encephalopathy. A phenobarbital dose of 30 mg/kg is advised to reach therapeutic concentrations. Phenobarbital co-administration significantly increased midazolam clearance. Should phenobarbital be substituted by non-CYP3A inducers as first-line anticonvulsant, a 50% lower midazolam maintenance dose might be appropriate to avoid excessive exposure during the first days after birth.

Objective Morphine is a commonly used drug in encephalopathic neonates treated with therapeutic hypothermia after perinatal asphyxia. Pharmacokinetics and optimal dosing of morphine in this

Evidence on the clinical effectiveness of probiotics in the prevention of necrotising enterocolitis (NEC) in preterm infants is conflicting and cohort studies lacked adjustment for time trend and feeding type. This study investigated the association between the introduction of routine probiotics (Lactobacillus acidophilus and Bifidobacterium bifidum; Infloran ®) on the primary outcome 'NEC or death'. Preterm infants (gestational age <32 weeks or birth weight <1500 gram) admitted before (Jan 2008-Sep 2012; n = 1288) and after (Oct 2012-Dec 2014; n = 673) introduction of probiotics were compared. Interrupted time series logistic regression models were adjusted for confounders, effect modification by feeding type, seasonality and underlying temporal trends. Unadjusted and adjusted analyses showed no difference in 'NEC or death' between the two periods. The overall incidence of NEC declined from 7.8% to 5.1% (OR 0.63, 95% CI 0.42-0.93, p = 0.02), which was not statistically significant in the adjusted models. Introduction of probiotics was associated with a reduced adjusted odds for 'NEC or sepsis or death' in exclusively breastmilk-fed infants (OR 0.43, 95% CI 0.21-0.93, p = 0.03) only. We conclude that introduction of probiotics was not associated with a reduction in 'NEC or death' and that type of feeding seems to modify the effects of probiotics.

Objective: This study aimed external validation of a formerly developed prediction model identifying children at risk for hearing loss after bacterial meningitis (BM). Independent risk factors included in the model are: duration of symptoms prior to admission, petechiae, cerebral spinal fluid (CSF) glucose level, Streptococcus pneumoniae and ataxia. Validation helps to evaluate whether the model has potential in clinical practice. Study design: 116 Dutch school-age BM survivors were included in the validation cohort and screened for sensorineural hearing loss (>25 dB). Risk factors were obtained from medical records. The model was applied to the validation cohort and its performance was compared with the development cohort. Validation was performed by application of the model on the validation cohort and by assessment of discrimination and goodness of fit. Calibration was evaluated by testing deviations in intercept and slope. Multiple imputation techniques were used to deal with missing values. Results: Risk factors were distributed equally between both cohorts. Discriminative ability (Area Under the Curve, AUC) of the model was 0.84 in the development and 0.78 in the validation cohort. Hosmer-Lemeshow test for goodness of fit was not significant in the validation cohort, implying good fit concerning the similarity of expected and observed cases. There were no significant differences in calibration slope and intercept. Sensitivity and negative predicted value were high, while specificity and positive predicted value were low which is comparable with findings in the development cohort. Conclusions: Performance of the model remained good in the validation cohort. This prediction model might be used as a screening tool and can help to identify those children that need special attention and a long follow-up period or more frequent auditory testing. © 2013 de Jonge et al.

Background: Bacterial meningitis (BM) is a severe infection responsible for high mortality and disabling sequelae. Early identification of patients at high risk of these outcomes is necessary to prevent their occurrence by adequate treatment as much as possible. For this reason, several prognostic models have been developed. The objective of this study is to summarize the evidence regarding prognostic factors predicting death or sequelae due to BM in children 0-18 years of age.Methods: A search in MEDLINE and EMBASE was conducted to identify prognostic studies on risk factors for mortality and sequelae after BM in children. Selection of abstracts, full-text articles and assessment of methodological quality using the QUIPS checklist was performed by two reviewers independently. Data on prognostic factors per outcome were summarized.Results: Of the 31 studies identified, 15 were of moderate to high quality. Due to substantial heterogeneity in study characteristics and evaluated prognostic factors, no quantitative analysis was performed. Prognostic factors found to be statistically significant in more than one study of moderate or high quality are: complaints >48 hours before admission, coma/impaired consciousness, (prolonged duration of) seizures, (prolonged) fever, shock, peripheral circulatory failure, respiratory distress, absence of petechiae, causative pathogen Streptococcus pneumoniae, young age, male gender, several cerebrospinal fluid (CSF) parameters and white blood cell (WBC) count.Conclusions: Although several important prognostic factors for the prediction of mortality or sequelae after BM were identified, the inability to perform a pooled analysis makes the exact (independent) predictive value of these factors uncertain. This emphasizes the need for additional well-conducted prognostic studies. © 2010 de Jonge et al; licensee BioMed Central Ltd.