alexa The assessment of fetal brain function in fetuses with ventrikulomegaly: the role of the KANET test.
Bioinformatics & Systems Biology

Bioinformatics & Systems Biology

Journal of Health & Medical Informatics

Author(s): Talic A, Kurjak A, Stanojevic M, Honemeyer U, Badreldeen A,

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Abstract OBJECTIVE: To assess differences in fetal behavior in both normal fetuses and fetuses with cerebral ventriculomegaly (VM). METHODS: In a period of eighteen months, in a longitudinal prospective cohort study, Kurjak Antenatal NeuorogicalTest (KANET) was applied to assess fetal behavior in both normal pregnancies and pregnancies with cerebral VM using four-dimensional ultrasound (4D US). According to the degree of enlargement of the ventricles, VM was divided into three groups: mild, moderate and severe. Moreover fetuses with isolated VM were separated from those with additional abnormalities. According to the KANET, fetuses with scores ≥ 14 were considered normal, those with scores 6-13 borderline and abnormal if the score was ≤ 5. Differences between two groups were examined by Fisher's exact test. Differences within the subgroups were examined by Kruskal-Wallis test and contingency table test. RESULTS: KANET scores in normal pregnancies and pregnancies with VM showed statistically significant differences. Most of the abnormal KANET scores as well as most of the borderline-scores were found among the fetuses with severe VM associated with additional abnormalities. There were no statistically significant differences between the control group and the groups with isolated and mild and /or moderate VM. CONCLUSION: Evaluation of the fetal behavior in fetuses with cerebral VM using KANET test has the potential to detect fetuses with abnormal behavior, and to add the dimension of CNS function to the morphological criteria of VM. Long-term postnatal neurodevelopmental follow-up should confirm the data from prenatal investigation of fetal behavior. This article was published in J Matern Fetal Neonatal Med and referenced in Journal of Health & Medical Informatics

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