
Predicting the risk of left ventricular hypertrophy in children and adolescents with arterial hypertension on the basis of 24-hour blood pressure monitoring and metabolism indicators
Author(s) -
Tamara Haiduk,
Olha Haiduk,
I. A. Gubar
Publication year - 2020
Publication title -
journal of internal medicine. science and art
Language(s) - English
Resource type - Journals
ISSN - 2693-7476
DOI - 10.36013/jimsa.v1i1.16
Subject(s) - medicine , blood pressure , left ventricular hypertrophy , cardiology , ambulatory blood pressure , prehypertension , body mass index , logistic regression , insulin resistance , insulin
Objective: To investigate the significance of 24-hr ambulatory blood pressure monitoring (ABPM) data and metabolism indicators, as well their correlation in predicting the risk of left ventricular hypertrophy (LVH) in children and adolescents with arterial hypertension (AH).
Methods: We studied 118 children and adolescents, M±m 15.51±0.25 yrs, Boys/Girls – 104/14, with AH: 60 stable, 40 labile, 18 prehypertension (high-normal blood pressure), and a control group of 13 normotensive children, M±m 15,19±0,41 yrs, Boys/Girls – 10/3. All patients underwent a comprehensive anamnestic, clinical, laboratory, and instrumental examination, including 24-hr ABPM; indicators were standardized by gender and age. On Doppler echocardiography (echoCG), the left ventricular myocardial mass index (LVMI) was calculated. Lipid spectrum parameters were determined by biochemical method, venous blood glycemia by GOD-PAP, blood serum basal immunoreactive insulin by ELISA methods, insulin resistance (IR) by HOMA parameters calculation. Statistical processing was performed using the package of statistical analysis software STATISTICA.
Results: Of a range of metabolism indicators, BMI, TG level, LDL/HDL ratio, HOMA index, 24-hr DBP index, and the stable character of AH identified as the most significant factors in predicting the risk of LVH in hypertensive children. All multivariate models of logistic regressions, which include BMI, can predict the probability of LVH with an accuracy of 79.7-84.7%, sensitivity - 57.5-77.5%, specificity - 86.4-91.0%.
Conclusions: Obtained satisfactory concordance of the actual data with predictive models' results indicate the possibility of their use to predict the risk of LVH in children and adolescents with AH.