Abstract

Abstract Objective: The prevalence of essential hypertension among children has risen over the last several decades in accordance with the rise in childhood obesity. Early identification and management of elevated blood pressure in the pediatric population are important to decrease the risks of end-organ damage and mortality in the pediatric and adult population. Using a discriminant analysis study of children, we sought to construct a predictive model of individuals who are at a higher risk factor of the occurrence of arterial hypertension in childhood. Design and method: The complex of genetic, environmental and biological risk factors were analyzed on a test sample of 75 subjects (49 patients with essential hypertension and 26 normotensive children). Linear discriminant analysis was used to generate a predictive model. The accuracy of our prognostic model was defined in another group of patients (n = 10). Results: Seventeen variables were found to be predictive of early onset of arterial hypertension in children. Stepwise discriminant analysis revealed that the overweight and obesity (Wilks Lambda = 0.552; F = 53.895; P < 0.001), the familial tendency to high blood pressure (Wilks Lambda = 0.352; F = 14.445; P < 0.001), the individual accumulation of risk factors (Wilks Lambda = 0.333; F = 10.654; P = 0.001), low weight at birth (Wilks Lambda = 0.351; F = 14.319; P < 0.001) and living in poor socioeconomic conditions (Wilks Lambda = 0.350; F = 14.045; P < 0.001) were the strongest discriminators in the model. The ‘low-risk’ persons could be distinguished from the ‘high-risk’ individuals with an almost 97% correctness. The model of prognosis was tested on the control group. The accuracy of prognosis was 90%, with a sensitivity of 100% and specificity of 80%. Conclusions: A personalized prognostic model makes it possible to predict the early onset of arterial hypertension in children. This reliable method for identification of the subset of the pediatric population predisposed to arterial hypertension would aid a targeted implementation of intervention strategies.

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