On the problem of patient specific endogenous glucose production in neonates on stochastic targeted (STAR) glycaemic control

Abstract

Background: Stress and prematurity can both induce hyperglycaemia in the neonatal intensive care unit (NICU), which in turn is associated with worsened outcomes. Endogenous glucose production (EGP) is the formation of glucose by the body from substrates, and contributes to blood glucose (BG) levels. Due to the inherent fragility of the extremely low birth weight (ELBW) true fasting EGP cannot be explicitly determined, introducing uncertainty into glycaemic models that rely on quantifying glucose sources. STAR (Stochastic TARgeted) is one such glycaemic control framework. Methods: A literature review was carried out to gather metabolic and EGP values on preterm infants with a gestational age (GA) < 32 weeks and a birth weight (BW) < 2kg. The data was analysed for EGP trends with BW, GA, BG, plasma insulin and glucose infusion rates. Trends were modelled and compared to a literature-derived range of population constant EGP models using clinically validated virtual trials on retrospective clinical data. Results: No clear relationship was found for EGP and BW, GA, or plasma insulin. Some evidence of suppression of EGP with increasing glucose infusion or BG was seen. Virtual trial results showed that population constant EGP models fit clinical data best and gave tighter control performance to a target band in virtual trials. Conclusions: Variation in EGP cannot easily be quantified, and EGP is sufficiently modelled as a population constant in the NICING (Neonatal Intensive Care Insulin-Nutrition-Glucose) model. Analysis of the clinical data and fitting error suggests that ELBW hyperglycaemic preterm neonates have unsuppressed EGP in the higher range than that seen in literature.