European journal of pediatrics
-
Randomized Controlled Trial
Melatonin does not influence sleep deprivation electroencephalogram recordings in children.
The electroencephalogram (EEG) is an essential diagnostic tool in children with epilepsy. The recording of a sleep EEG can increase the yield of EEG recordings in certain epileptic syndromes. The primary aim of this study was to assess the influence of melatonin on EEG recording (quality, EEG characteristics) and to assess its efficacy to induce sleep. Children with epilepsy or non-epileptic neurological patients requiring sleep deprivation EEG studies were enrolled into this prospective study at a tertiary University Hospital study. Sequential recording of sleep deprivation EEGs both with and without prior administration of melatonin was performed. A total of 50 patients (27 with epilepsy, 23 non-epileptic neurological patients) were included in this study (median age 9.5 years; range 1-18 years; male 28). The quality and EEG characteristics (abnormal findings, depth of sleep) were not affected by the use of melatonin. In total, 92 of 100 EEGs were successfully performed without significant differences between the two groups (six failures with melatonin, two failures without melatonin; p = 0.289). ⋯ We conclude that melatonin does not alter the quality of sleep EEG studies in children with epilepsy or suspected epilepsy. Melatonin does not increase the rate of successfully performed EEG studies in sleep-deprived children.
-
Given their high apparent variability, bedside continuous respiratory mechanics (RM) parameters [excepting tidal volume (V (T))] remain infrequently used for adjustment of neonatal ventilatory settings. RM parameters provided by ventilator (VRC) from ten recordings of newborns [10 min in synchronised intermittent mandatory ventilation and 10 min in assist/control (A/C)] were compared to those computed from visually selected assisted leak-free optimal respiratory cycles (SRC). Mean values, variability and ability to distinguish patients were compared between VRC and SRC. Dynamic resistances were more correlated (r(2) = 0.95) than compliances (r (2) = 0.42). V (T)s were correlated only in A/C (r(2) = 0.78). C20/C was significantly higher in VRC (1.81 ± 0.67) than in SRC (1.23 ± 0.36) and frequently out of neonatal reference range. In A/C ventilation, V(T) was higher in VRC (5.6 ± 1.8 ml/kg) than in SRC (4.8 ± 1.0 ml/kg) (p < 0.05). Displayed V (T)s do not reflect those found in optimal assisted breaths and therefore have incomplete value in assessing adequacy of ventilator settings. The variability of RM parameters provided by the ventilator is large, and coefficients of variation were significantly lower with optimal respiratory cycles (for resistance, compliance, V (T) and C20/C; 27%, 26%, 18%, 24% in SRC and 36%, 35%, 40% and 33% in VRC). Selecting optimal cycles yields RM with two to three times higher discriminating power between patients. ⋯ Current ventilator's RM parameters have limited clinical use. Using optimal breaths to calculate RM parameters improves precision and discriminating power. For integration to ventilatory care, automation of this selection must be implemented first.