PhD defence J.A. (Jarinda) Poppe

Brief summary:

Respiratory instability and the need to stabilize oxygenation are significant daily clinical problems in neonatal intensive care. The condition of preterm infants is monitored extensively. However, the large amount of available physiological data is used suboptimally, without access to detailed, longitudinal, or integrated information parameters. The main aims of this thesis are to enhance assessment of the oxygenation status, improve therapy effect evaluation, and predict neonatal outcomes using routinely monitored physiological data. We investigated the quantification of hypoxemia and hyperoxemia and their clinical relevance. Physiological data were used to measure the clinical effect of pharmacotherapy, and a randomized controlled trial on doxapram therapy versus placebo was designed. Also, we used saturation profiles to indicate treatment need and to identify patients at risk for developing retinopathy of prematurity (ROP) using machine learning techniques. Finally, a web-based oxygenation dashboard was developed to visualize and integrate trends and summary statistics from bedside measurements.