PREDICTIVE MODELS TO ESTIMATE THE RISK OF DEVELOPING EPILEPSY IN CHILDREN

Actuality: Epilepsy is a chronic neurological disorder linked to a predisposition to recurrent seizures, with various clinical features and causes. WHO reports a rate of 10.5 million children under 15 years with epilepsy. Aim: to establish the risk of developing the disease by associating a number of factors – predictors. Material and methods: 108 children (1-36 months) diagnosed with epilepy were examined in the Department of Neurology PMSI BMI (2009-2012). Another 108 children were considered healthy controls. Risk factors studied were: perinatal encephalopathy, febrile seizures, heredity, ma- ternal hypertension, craniocerebral trauma, CNS infections. By multiple logistic regression, step by step, it was analyzed the interrelation of a number of factors : hereditary, evolution of perinatal period (including childbirth), the presence of CNS infections and brain injury in the postnatal period. Results: The results demonstrate the presence of strong combination of both factors (perinatal and postnatal) for developing of seizures. Thus, the presence of the combination of intrapartum factors (EHIP II emergency caesarean section, vacuum extraction) and some postnatal factors (CNS infections) reports a logistic regression coefficients (3.861, 1.909, 2.377, 4.311, 3.505), which indicates a strong link between these factors. Conclusions: The predictive models can be applied in clinical use for decreasing the risk of epilepsy by careful evaluation of these children, particularly in the presence of predictive factors and developing effective measures of primary and secondary prophylaxis.

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