A Method for a Real-Time Novel Premature Infant Pain Profile Using High Rate, High Volume Physiological Data Streams

摘要

Management of pain in the neonatal population is one of the most challenging problems in the Neonatal Intensive Care Unit (NICU). There are many gaps in our knowledge of the optimal utilization of the techniques available to assess pain in a valid and reliable manner. Pain that is not treated may cause significant clinical complications in the newborn infant. An initial start was made in a previous study to design a novel Premature Infant Pain Profile with a substantial focus on physiological factors. In this study, the novel Artemis Premature Infant Pain Profile (APIPP) was retrospectively compared with the Premature Infant Pain Profile (PIPP) that is used in the NICU at The Hospital for Sick Children, Toronto, to evaluate the effectiveness and validity of the novel scale being proposed. The main objective of this research was to use a preliminary case study approach by using retrospective data that were assigned PIPP scores to compare the performance of the novel APIPP with the current standard for measuring pain. The experiment was performed with two surgical subjects' data retrospectively with the APIPP algorithm. We demonstrated this study using an environment known as Artemis, a clinical decision support system.