This study compared computer-based control of BG using insulin infusions against clinical control before the introduction of the system. The retrospective clinical control group had a generally higher target than the computer-controlled group. It is completely feasible that even though model-based control targeted a lower BG range it may have had no difference on BG concentrations compared to the previous methods of BG control. The results presented indicate that the model-based system achieved lower BG levels and greater time of BG spent in the desired target range, without excessive hypoglycemia.
Hyperglycemia has been linked to worsening outcomes for premature infants [1
], but there is currently no best-practice approach to its management. Great inter-patient heterogeneity is a hallmark of neonatal glucose metabolism making safe, adequate control difficult [2
]. Even within this relatively small study population a 10-fold spread of insulin sensitivity was computed during long-term trials. Additionally, the inter-patient variation in sensitivity to insulin observed in the short-term trials, presented in Figure
, highlight this wide range of response between individuals. Thus, fixed insulin protocols based on weight or other patient parameters are not likely to accurately account for this level of inter-patient variability, and an adaptive protocol, as presented here, may provide better, safer control.
Model-based control provides real-time identification of insulin sensitivity, and its evolution with time. However, identification of insulin sensitivity relies on the availability of blood glucose concentration measurements. One to four hourly measurements were used in this study, based on simulation results [26
], as a compromise between accurate metabolic identification and nursing/patient burden, magnified in premature neonates with limited blood volumes. Frequent glucose sampling has been shown to be an important precursor for tight glycemic control [26
]. Some insulin infusion studies in premature neonates used longer measurement and intervention intervals of up to 6
], which may have contributed to the difficulty of achieving glycemic control [37
]. Continuous glucose monitoring systems may help in this regard to prevent hypoglycemia and limit excursions into hyperglycemia by providing greater information to quantify insulin sensitivity and respond faster to changes in patient condition.
Clinically, babies were observed to occasionally have periods of rapid change in sensitivity to insulin. Both increases and decreases in the level of insulin sensitivity were seen and often could not be linked to significant changes in any other routinely measured clinical variable during this time. Thus, it is possible that there were changes in some aspect of glucose metabolism that is not typically measured during neonatal intensive care. This example demonstrates robustness of the control system to account for clinically un-measurable and un-modeled effects.
The targets for glucose control vary widely between clinical units [8
]. A blood glucose concentration less than 2.7
mmol/L may increase the risk of long term neurological deficiencies, and is often cited as a limit for hypoglycemia [38
]. However, the precise upper limit for clinically desirable blood glucose concentration is still under debate [2
]. In particular, the 8.0
mmol/L median for retrospective control may have satisfied the attending clinicians at the time and prevented attempts to lower the blood glucose further. The target range of 4–7
mmol/L selected for this study was a relatively conservative choice, reflecting the nature of these pilot trials as the first model-based study performed in premature neonates. The blood glucose target for model-based control can be readily adjusted and could thus provide a method to target specific ranges of blood glucose concentrations, without increasing the risk of hypoglycemia. This methodology could be utilized in a future randomized controlled trial to assess the efficacy of insulin infusions for glucose control whilst avoiding the complication of increased rates of hypoglycemia in the tightly controlled group.
The risk of hypoglycemia is often cited as a barrier to large-scale adoption of glycemic control by insulin infusions, especially as most neonatal hypoglycemia appears to be asymptomatic [40
]. Some studies [10
] found the incidence of hypoglycemia was significantly higher in infants receiving insulin therapy than in controls. In contrast, the results presented in this study and the adult SPRINT system developed from model-based control show a frequency of hypoglycemia similar to that seen with retrospective hospital control protocols [28
]. Thus, the potential for model-based control to reduce BG levels without increasing hypoglycemia by accounting for patient variability may add another element to the discussion of ideal BG targets.
This study compared pilot trial results to retrospective data. Changes in clinical management of these infants over time may have influenced the degree of metabolic variability observed during the trials versus historical data and thus influence relative improvement in glucose control with this system. However, the low incidence of hypoglycemia is an absolute metric independent of any comparison cohort. This result suggests there is a possibility to use insulin for glycemic control without creating significant risk of hypoglycemia, provided dosing is adapted to individual, time-varying patient condition.
The stochastic model employed in this study is built from a whole-cohort perspective using data from the 21 patient retrospective group [24
]. Thus, the forecasts achieve the desired prediction spread over the whole-cohort. However, the degree of variability in insulin sensitivity is patient-specific and may be linked to other clinical and diagnostic variables. Further clinical data and studies may identify patients at different stages of development or with different clinical issues. Individualized stochastic models may provide tighter forecast bands by identifying the levels of glycemic stability for individual patient.
The long-term study included two infants with gestational age of 23
weeks at birth. These infants were significantly younger than the remainder of the study populations and displayed significant resistance to insulin and persistent hyperglycemia despite insulin infusions, resulting in a clinical decision to reduce the dextrose concentration of their parenteral nutrition infusions. This result suggests that in some infants the use of insulin alone may not be enough to fully bring glycemia into control without significantly increasing the hypoglycemiarisk, and that adjusting other infusions affecting the glucose-insulin system may be necessary in these cases.
The goal of this study was to assess the efficacy of model-based insulin dosing for the control of glycemia, as opposed to eliciting the direct anabolic effects of insulin. The model-based approach can naturally modulate dextrose and insulin intake in tandem to meet nutrition goals, while controlling glycemia to allow more prospective neonatal metabolic management. This approach has already been demonstrated in adult critical care studies [27
]. Finally, a significant range of dextrose infusions were used in these infants, and thus accounting for the total glucose load is vital to accurately choose appropriate insulin infusion rates across multiple patients.