Background: Quantitative EEG is a rapidly emerging tool in the diagnosis and follow up of various neurological disorders and can act as predictive marker for subsequent epilepsy in children with complex febrile seizure. The present study aimed to estimate the prevalence of abnormal electroencephalogram (EEG) and to find the association between Quantitative EEG (qEEG) and various clinical features of atypical febrile seizures(AFS).Methods: EEG was recorded along with clinical features including the age at onset, duration of episode, number of episodes in a day, type of seizure and the recurrences from the children aged between 6-60 months with atypical febrile seizures. EEG recordings were classified into Normal and abnormal EEG with epileptiform changes by the expert interpretation and the distribution of above said clinical features in the both groups were analyzed. It is also attempted to find the association between qEEG and few of the clinical features.Results: Prevalence of abnormal EEG in atypical febrile seizures was 33.9%. There were no significant differences in the distribution of abnormal EEG and their association with various clinical features of AFS. Significantly increased absolute power of θ and α waves were recorded from the frontal montages in the children with epileptiform changes in the EEG.Conclusions: qEEG changes can be also considered as marker of severity of febrile seizure episodes. Many prospective studies with long-term follow up are required to establish the predictability of future epilepsy by qEEG.

Background: This study was conducted to study the clinical profile of hypoglycemia in newborn and to determine the prevalence of hypoglycemia among neonates admitted in NICU.Methods: All newborns admitted in NICU were examined and those with hypoglycemia (GMR<45 mg/dl) were included in the study and observed. In neonates with risk factors blood sugar was screened at 2, 6, 12, 24, 48 and 72 hours of life or whenever symptoms suggestive of hypoglycemia developed in any neonates and for critically sick neonates blood sugar was screened in every 6 hour in active phase of illness. Any neonates with blood glucose level less than 45 mg/dl were analysed for maternal risk factors, neonatal risk factors and course in the NICU.Results: The prevalence of neonatal hypoglycemia was 14.9% among NICU admissions. The maternal risk factors were GDM, PIH, and PROM. The neonatal risk factors were prematurity, SGA, LGA and comorbid conditions which include perinatal asphyxia, sepsis, polycythemia, shock. The common symptoms were poor feeding, lethargy, jitteriness, convulsions, irritability, hypotonia and cyanosis. Majority of the neonates required only oral feeds for correction of hypoglycemia.Conclusions: Blood glucose screening in neonates with this risk factor is mandatory as many of the neonates were asymptomatic. The importance of early initiation of breast feeding to prevent hypoglycemia should be emphasized.

Background: Gestational age (GA) estimation plays a vital role in obstetric, perinatal and neonatal care. Foot length (FL) measurement can serve as a simple, easy and cost effective parameter for estimating GA. The aim of this study was to determine correlation between foot length of new born and GA by new Ballard score and forming a percentile chart if a positive correlation was found.Methods: GA assessment of newborns born in our hospital was done by new Ballard score within 24 hours of life. FL was measured using vernier caliper. Neonates were classified as pre term, term and post term and also grouped as small for GA (SGA), appropriate for GA (AGA) and large for GA (LGA).Results: FL measurement was strongly correlating with GA assessment by new Ballard score, with overall correlation coefficient r=0.897 (p<0.001). FL increased as GA increased. Strong positive correlation was seen in pre term and term newborns. The cut-off foot lengths for identifying preterm and early preterm neonates were 73.14 mm (diagnostic accuracy 88.4%) and 68.49 mm (diagnostic accuracy 95.3%), respectively.Conclusions: Strong positive correlation of foot length with GA by new Ballard score was obtained and a percentile chart of foot length for each GA was formed, with mean and standard deviation. This can serve as a simple and quick tool, requiring less expertise for GA assessment.