Pediatric research
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Moderate hypothermia is consistently neuroprotective after hypoxic-ischemic insults and is the subject of ongoing clinical trials. In pilot studies, we observed rebound seizure activity in one infant during rewarming from a 72-h period of hypothermia. We therefore quantified the development of EEG-defined seizures during rewarming in an experimental paradigm of delayed cooling for cerebral ischemia. ⋯ Individual seizures were typically short (28.8 +/- 5.8 s versus 29.0 +/- 6.8 s in sham cooled; NS), and of modest amplitude (35.9 +/- 2.8 versus 38.8 +/- 3.4 microV; NS). Neuronal loss in the parasagittal cortex was significantly reduced in the cooled group (51 +/- 9% versus 91 +/- 5%; p <0.002) and was not correlated with rebound epileptiform activity. In conclusion, rapid rewarming after a prolonged interval of therapeutic hypothermia can be associated with a transient increase in epileptiform events but does not seem to have significant adverse implications for neural outcome.
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Normal children have a smaller upper airway than adults, but, nevertheless, snore less and have less apnea. We have previously shown that normal children have an upper airway that is resistant to collapse during sleep. We hypothesized that this resistance to collapse is due to preservation of upper airway neuromotor responses during sleep. ⋯ We conclude that upper airway dynamic responses are decreased in children with OSAS but recover after treatment. We speculate that the pharyngeal airway neuromotor responses present in normal children are a compensatory response for a relatively narrow upper airway. Further, we speculate that this compensatory response is lacking in children with OSAS, most likely due to either habituation to chronic respiratory abnormalities during sleep or to mechanical damage to the upper airway.
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This prospective study aimed to evaluate the diagnostic utilities of neutrophil CD64 expression for the identification of early-onset clinical infection and pneumonia in term infants and to define the optimal cutoff value so that it may act as a reference with which future studies can be compared. Term newborns in whom infection was suspected when they were <72 h of age were recruited into the study. C-reactive protein (CRP) and expression of CD64 on neutrophils were measured at 0 h (at the time of sepsis evaluation) and 24 h. ⋯ The addition of CRP only marginally enhanced the sensitivity and NPV (97 and 98%, respectively). In conclusion, neutrophil CD64 is a very sensitive diagnostic marker for the identification of early-onset clinical infection and pneumonia in term newborns. The results strongly suggest that measurement of neutrophil CD64 may allow neonatal clinicians to discontinue antibiotic treatment at 24 h in infants who are clinically stable and whose CD64 expressions are below the optimal cutoff level.
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Data are scant regarding the development of cerebrovascular autoregulation in intrauterine growth-restricted (IUGR) newborns. We tested the hypothesis that IUGR improves the ability of neonates to withstand critical periods of gradual hemorrhagic hypotension by optimizing cerebrovascular autoregulation. Studies were conducted on 1-d-old anesthetized piglets divided into groups of normal weight (NW, n = 14, body weight = 1518 +/- 122 g) and IUGR (n = 14, body weight = 829 +/- 50 g) animals. ⋯ Furthermore, under these conditions, cerebral cortex blood flow was maintained in newborn IUGR animals. In contrast, NW piglets exhibited a significant reduction in CBF (p < 0.05) during moderate HH. Thus, IUGR resulted in an improved ability to withstand critical periods of gradual oxygen deficit as shown by improved cerebrovascular autoregulation during hemorrhagic hypotension.
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Comparative Study
Predicting extubation outcome in preterm newborns: a comparison of neural networks with clinical expertise and statistical modeling.
Even though ventilator technology and monitoring of premature infants has improved immensely over the past decades, there are still no standards for weaning and determining optimal extubation time for those infants. Approximately 30% of intubated preterm infants will fail attempted extubation, requiring reintubation and resuming of mechanical ventilation. A machine-learning approach using artificial neural networks (ANNs) to aid in extubation decision making is hereby proposed. ⋯ It also compared well with the clinician's expertise, which raises the possibility of being useful as an automated alert tool. Because an ANN learns directly from previous data obtained in the institution where it is to be used, this makes it particularly amenable for application to evidence-based medicine. Given the variety of practices and equipment being used in different hospitals, this may be particularly relevant in the context of caring for preterm newborns who are on mechanical ventilation.