SummaryIntroductionIntra-uterine growth restriction (IUGR) is present in about 3–10% of live-born newborns and it is as high as 20–30% in developing countries. Since the 1990s, it has been known that abnormalities during foetal growth may result in cardiovascular disease, including hypertension in adulthood.MethodsThis study evaluated blood pressure parameters (using ambulatory blood pressure monitoring) in children aged six to 10 years old, born as small for gestational age (SGA), and compared them to their healthy peers born as appropriate for gestational age (AGA).ResultsIn the SGA group, an abnormal blood pressure level (prehypertension or hypertension) was present significantly more often than in the AGA group (50 vs 16%, p < 0.01). This relationship also occurred in association with the type of IUGR (asymmetric p < 0.01, symmetric p < 0.05).ConclusionIn SGA children, abnormal blood pressure values occurred more frequently than in AGA children.

SummaryIntroductionThe prevalence of intrauterine growth restriction (IUGR) is about 3–10% of live-born newborns and can be as high as 20% in developing countries. It may result in the occurrence of cardiovascular diseases later in life.MethodsThe aim of this study was echocardiographic evaluation, with the use of conventional and tissue Doppler parameters, of cardiac function in children born with IUGR, and comparison with healthy peers born as normally grown foetuses.ResultsIn the IUGR group, E wave and E/A ratio were significantly lower compared to the control group. A wave, isovolumetric relaxation time, deceleration time, myocardial performance index as well as E/E′ septal and E/E′ lateral indices were significantly higher compared to healthy peers.ConclusionChildren with IUGR presented with subclinical myocardial dysfunction.

Abstract-This paper concerns automated identification of intrauterine growth restriction (IUGR) types by use of machine learning methods. The research presents a comparison of supervised and unsupervised learning covering single and hybrid classification, as well as clustering. Supervised learning techniques included bagging with Naïve Bayes, k-nearest neighbours (kNN), C4.5 and SMO as base classifiers, random forest as a variant of bagging with a decision tree as a base classifier, boosting with Naïve Bayes, SMO, kNN and C4.5 as base classifiers, and voting by all single classifiers using majority as a combination rule, as well as five single classification strategies: kNN, C4.5, Naïve Bayes, random tree and sequential minimal optimization algorithm for training support vector machines. Unsupervised learning encompassed k-means and expectation-maximization algorithms. The major conclusion drawn from the study was that hybrid classifiers have demonstrated their potential ability to identify more accurately symmetrical and asymmetrical types of IUGR, whereas the unsupervised learning techniques produced the worst results.

According to metabolic programming theory, small-for-gestational age patients are at high risk of cardiovascular diseases also because of the possible malfunction of the autonomic nervous system. Autonomic disorders can be assessed by heart rate variability. The aims of this study were to compare time domain parameters of heart rate variability in children born as small-for-gestational age and appropriate-for-gestational age and to assess the correlation of the postnatal and current somatic parameters with the time domain parameters. The small-for-gestational age group consisted of 68 children aged 5-10 years who were born with birth weight below the 10th percentile. The appropriate-for-gestational age group consisted of 30 healthy peers, matched in terms of gender and age. On the basis of Holter monitoring, slightly higher average heart rate was observed in the small-for-gestational age group than in the appropriate-for-gestational age group. It was found that all the time domain parameters (SDNN, SDNNi, SDANNi, rMSSD, pNN50) were lower in the small-for-gestational age group than in the appropriate-for-gestational age group. In the small-for-gestational age group, girls had lower heart rate and some of the heart rate variability parameters (SDNN, SDNNi, SDANNi) in comparison with boys. Children born as small-for-gestational age have impaired function of the autonomic nervous system. Moreover, in the small-for-gestational age group, autonomic balance moved towards the sympathetic component, which was evidenced by higher heart rate. Children with faster heart rate and lower heart rate variability parameters may be at risk of cardiovascular disease.

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