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https://open.uns.ac.rs/handle/123456789/4578
Title: | Assessment of general movements and heart rate variability in prediction of neurodevelopmental outcome in preterm infants | Authors: | Lidija Dimitrijević Bojko Bjelaković Hristina Čolović Aleksandra Mikov Vesna Živković Mirjana Kocić Stevo Lukić |
Keywords: | General movements;Heart rate variability;Neurodevelopmental outcome;Preterm infant | Issue Date: | 1-Aug-2016 | Journal: | Early Human Development | Abstract: | © 2016 Elsevier Ireland Ltd Background Adverse neurologic outcome in preterm infants could be associated with abnormal heart rate (HR) characteristics as well as with abnormal general movements (GMs) in the 1st month of life. Aims To demonstrate to what extent GMs assessment can predict neurological outcome in preterm infants in our clinical setting; and to assess the clinical usefulness of time-domain indices of heart rate variability (HRV) in improving predictive value of poor repertoire (PR) GMs in writhing period. Study design Qualitative assessment of GMs at 1 and 3 months corrected age; 24 h electrocardiography (ECG) recordings and analyzing HRV at 1 month corrected age. Subjects Seventy nine premature infants at risk of neurodevelopmental impairments were included prospectively. Outcome measures Neurodevelopmental outcome was assessed at the age of 2 years corrected. Children were classified as having normal neurodevelopmental status, minor neurologic dysfunction (MND), or cerebral palsy (CP). Results We found that GMs in writhing period (1 month corrected age) predicted CP at 2 years with sensitivity of 100%, and specificity of 72.1%. Our results demonstrated the excellent predictive value of cramped synchronized (CS) GMs, but not of PR pattern. Analyzing separately a group of infants with PR GMs we found significantly lower values of HRV parameters in infants who later developed CP or MND vs. infants with PR GMs who had normal outcome. Conclusions The quality of GMs was predictive for neurodevelopmental outcome at 2 years. Prediction of PR GMs was significantly enhanced with analyzing HRV parameters. | URI: | https://open.uns.ac.rs/handle/123456789/4578 | ISSN: | 3783782 | DOI: | 10.1016/j.earlhumdev.2016.05.014 |
Appears in Collections: | MDF Publikacije/Publications |
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