Safe, effective, and patient-specific glycaemic control in neonatal intensive care.

Abstract

Very premature infants often experience high blood sugar levels as a result of incomplete metabolic development, illness, and stress. High blood sugar levels have been associated with a range of worsened outcomes and increased mortality, but debate exists as to whether high blood sugar levels are a cause of, or marker for, these worsened outcomes. Insulin can be used to lower blood sugar levels, but there is no standard protocol for its use in neonates, and the few clinical studies of insulin use in neonatal intensive care are relatively small and/or have resulted in high incidence of dangerously low blood sugar levels. Hence, there is a need for a safe and effective protocol for controlling blood sugar levels to a normal range in order that potential clinical benefits can be successfully studied in this clinical cohort. This thesis adapted a glucose-insulin model successfully used in adult intensive care for the unique physiology and situation of the very premature infant. The model aims to reflect known physiology. As such, sources and disposal of glucose and insulin within the body are examined using both published data and unique data sets from a study here in New Zealand. In addition, the absorption of glucose from milk feeds is examined. This glucose-insulin physiological model is then used alongside statistical forecasting to develop a protocol for selecting an appropriate insulin dose based on targeting of likely outcomes to a specified target normal range. The protocol is tested in silico using virtual trials, and then clinically implemented, with results showing improved performance over current clinical practice and other published studies. In particular, ~77% of blood glucose is observed within the specified target range across the cohort, and there has been no incidence of dangerously low blood glucose levels. This protocol is thus safe and effective, accounting for inter- and intra- patient variability, and thus enabling patient-specific care.