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Project

Perinatal prediction models for developmental outcome in preterm infants

Approximately 8% of the babies in Flanders are born preterm. These newborns are taken care of in neonatal intensive care units in which they experience an unnatural environment which can cause negative early-life experiences or stress. Stress exposure is found to negatively affect the overall development of preterm newborns. However, an automated method to quantify the impact of stress specifically and early-life experiences in general on developmental outcome of preterms does not yet exist. Such a method would enable medical doctors to identify those babies most at risk and allow them to decide on optimal preventive treatments and interventions. This project will first optimise the most relevant EEG and HRV fingerprints associated with early-life experiences. Secondly, the impact of early-life experiences and its associated fingerprints on developmental outcome of preterm newborns will be quantified to make perinatal computer models for predicting this developmental outcome. Several scales like Bayley scales, executive functions and emotional availability scale will be used to define the developmental outcome. Also the trajectories of development and stress-related variables will be considered. Thirdly, these prediction models will be made clinically interpretable such that they can be used in clinical practice which will be tested during an intervention study. Finally, the perinatal prediction models will be implemented into ready-to-use software.

Date:25 Sep 2020 →  28 Feb 2022
Keywords:Perinatal prediction models, Impact of early-life experiences on overall development, Improvement of perinatal developmental outcome
Disciplines:Biomedical signal processing, Neonatology
Project type:PhD project