PubMed · 13258638
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J L O'LEARY. 1955. Electro-encephalography.. https://pubmed.ncbi.nlm.nih.gov/13258638/
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OBJECTIVE: To describe developmental characteristics, morphological aspects and incidence of temporal sharp transients (TST) in normal preterm and term newborns at matched conceptional ages (CA). METHOD: Neonatal EEGs from two groups of normal newborns were evaluated in order to identify and characterize TST. Group I (n=40) consisted of newborns from 34 to 40 weeks of gestational age (GA) that were submitted to a single EEG between 24 and 48 hours of life. Group II consisted of 10 preterm newborns with GA between 30-32 weeks, followed with a weekly EEG until they reached term. Morphology of TST was divided in 3 groups (temporal sawtooth, isolated transients or repetitive transients). TST index, density and total number were calculated in each polysomnography and related to sleep stages and CA. Laterality (right/left) was also evaluated. The groups were compared at 34, 36, 38 and 40 weeks of CA. RESULTS: TST index and density decreased with the increase of CA in both groups (p<0.0001). The temporal sawtooth feature was registered in both groups only at 34 weeks. Although rare, repetitive and isolated TST were the most prevalent morphology between 36 - 40 weeks CA. Significant intragroup difference was observed in the comparison of TST density in REM and transitional sleep in GI. Moreover, isolated TST morphology was significant higher in GI at 34 weeks when compared to the others CA. No intragroup differences were observed on GII. No significant differences between the groups were observed considering TST number, index, density, morphology or laterality, at the matched CA. CONCLUSION: TST are normal features of neonatal EEG, as they are registered in normal newborns. Its incidence varies accordingly to morphology and they tend to disappear following the increase of CA. Temporal sawtooth appears more often in preterm newborns. Our results suggest that TST index, density and morphology variability may be a function of CA.
The authors reviewed the reports of all emergent EEG (EmEEG) performed in our hospital within 1 hour of the test being ordered over a period of 52 months. Two hundred sixty-one EmEEG (12.8% of all EEG) were performed. The most common reason to order the test was a change in mental status or coma (17.6%). Although EmEEG was ordered to rule out status epilepticus (SE) in 60.2% of cases, this diagnosis was made in only 10.7% of patients. The only independent predictor for SE was a history of cardiac or respiratory arrest (odds [95% CI], 6.8 [2.7 to 16.9]).
In this study an information-theoretic test for general Granger causality is used to identify couplings and information transport between different brain areas during epileptic activities. This method can distinguish information that is actually exchanged between two systems from that due to the response to a common signal or past history. This is achieved by an appropriate conditioning of probabilities. Statistical assessment of causality is made from a nonparametric bootstrap test, whereas nonlinearity is assessed by a comparison with a linearized version of the causality index. The framework proposed here provides a useful and model free test to characterize interactions in intracranial electroencephalography (EEG) signals.