Analysis of the EEG Dynamics of Epileptic Activity in Gelastic Seizures Using Decomposition in Independent Components

Objective: Gelastic seizures are a frequent and well established manifestation of the epilepsy associated with hypothalamic hamartomas. The scalp EEG recordings very seldom demonstrate clear spike activity and the information about the ictal epilepsy dynamics is limited. In this work, we try to isolate epileptic rhythms in gelastic seizures and study their generators. Methods: We extracted rhythmic activity from EEG scalp recordings of gelastic seizures using decomposition in independent components (ICA) in three patients, two with hypothalamic hamartomas and one with no hypothalamic lesion. Time analysis of these rhythms and inverse source analysis was done to recover their foci of origin and temporal dynamics. Results: In the two patients with hypothalamic hamartomas consistent ictal delta (2–3 Hz) rhythms were present, with subcortical generators in both and a superficial one in a single patient. The latter pattern was observed in the patient with no hypothalamic hamartoma visible in MRI. The deep generators activated earlier than the superficial ones, suggesting a consistent sub-cortical origin of the rhythmical activity. Conclusions: Our data is compatible with early and brief epileptic generators in deep sub-cortical regions and more superficial ones activating later. Significance: Gelastic seizures express rhythms on scalp EEG compatible with epileptic activity originating in sub-cortical generators and secondarily involving cortical ones.

Optimal Cut-Off Value for Homeostasis Model Assessment (HOMA) Index of Insulin-Resistance in a Population of Patients Admitted Electively in a Portuguese Cardiology Ward

INTRODUCTION: Insulin resistance is the pathophysiological key to explain metabolic syndrome. Although clearly useful, the Homeostasis Model Assessment index (an insulin resistance measurement) hasn't been systematically applied in clinical practice. One of the main reasons is the discrepancy in cut-off values reported in different populations. We sought to evaluate in a Portuguese population the ideal cut-off for Homeostasis Model Assessment index and assess its relationship with metabolic syndrome. MATERIAL AND METHODS: We selected a cohort of individuals admitted electively in a Cardiology ward with a BMI < 25 Kg/m2 and no abnormalities in glucose metabolism (fasting plasma glucose < 100 mg/dL and no diabetes). The 90th percentile of the Homeostasis Model Assessment index distribution was used to obtain the ideal cut-off for insulin resistance. We also selected a validation cohort of 300 individuals (no exclusion criteria applied). RESULTS: From 7 000 individuals, and after the exclusion criteria, there were left 1 784 individuals. The 90th percentile for Homeostasis Model Assessment index was 2.33. In the validation cohort, applying that cut-off, we have 49.3% of individuals with insulin resistance. However, only 69.9% of the metabolic syndrome patients had insulin resistance according to that cut-off. By ROC curve analysis, the ideal cut-off for metabolic syndrome is 2.41. Homeostasis Model Assessment index correlated with BMI (r = 0.371, p < 0.001) and is an independent predictor of the presence of metabolic syndrome (OR 19.4, 95% CI 6.6 - 57.2, p < 0.001). DISCUSSION: Our study showed that in a Portuguese population of patients admitted electively in a Cardiology ward, 2.33 is the Homeostasis Model Assessment index cut-off for insulin resistance and 2.41 for metabolic syndrome. CONCLUSION: Homeostasis Model Assessment index is directly correlated with BMI and is an independent predictor of metabolic syndrome.

Predição de Pré-Eclâmpsia no Primeiro Trimestre em Gravidezes de Baixo Risco: Determinação do Cut-Off numa Amostra da População Portuguesa

Objective:We aimed to identify the cut-off for risk of pre-eclampsia (PE) in Portuguese population by applying the first trimester prediction model from Fetal Medicine Foundation (FMF) in a prospective enrolled cohort of low risk pregnant women. Population and methods: A prospective cohort of low risk singleton pregnancies underwent routine first-trimester scree - ning from 2011 through 2013. Maternal characteristics, blood pressure, uterine artery Doppler, levels of pregnancy-associated plasma protein-A (PAPP-A) and free b-human chorionic gonadotropin were evaluated. The prediction of PE in first trimester was calculated through software Astraia, the outcome obtained from medical records and the cutoff value was subse quently calculated. Results:Of the 273 enrolled patients, 7 (2.6%) developed PE. In first trimester women who developed PE presented higher uterine arteries resistance, represented by higher values of lowest and mean uterine pulsatility index, p <0.005. There was no statistical significance among the remaining maternal characteristics, body mass index, blood pressure and PAPP-A. Using the FMF first trimester PE algorithm, an ideal cut-off of 0.045 (1/22) would correctly detect 71% women who developed PE for a 12% false positive rate and a likelihood ratio of 12.98 (area under the curve: 0.69; confidence interval 95%: 0.39-0.99). By applying the reported cutoff to our cohort, we would obtain 71.4% true positives, 88.3% true negatives, 11.4% false positives and 28.6% false negatives. Conclusion: By applying a first trimester PE prediction model to low risk pregnancies derived from a Portuguese population, a significant proportion of patients would have been predicted as high risk. New larger studies are required to confirm the present findings.