Assessment of general movements and heart rate variability in prediction of neurodevelopmental outcome in preterm infants

• Poor repertoire GMs are the most frequently observed abnormal GMs
• Their predictive values for the neurological outcome is low
• HRV reflect functional integrity of the CNS and could be helpful clinically tool in infants with developmental disorders
• HRV may improve the prediction of neurodevelopmental outcome in infants with poor repertoire GMs

BackgroundAdverse 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.AimsTo 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 designQualitative assessment of GMs at 1 and 3 months corrected age; 24 h electrocardiography (ECG) recordings and analyzing HRV at 1 month corrected age.SubjectsSeventy nine premature infants at risk of neurodevelopmental impairments were included prospectively.Outcome measuresNeurodevelopmental 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).ResultsWe 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.ConclusionsThe quality of GMs was predictive for neurodevelopmental outcome at 2 years. Prediction of PR GMs was significantly enhanced with analyzing HRV parameters.