What Makes Tight Glycemic Control Tight? The Impact of Variability and Nutrition in Two Clinical Studies

Abstract

Protocols that dose insulin blind to carbohydrate administration can suffer greater outcome glycemic variability, even if average cohort glycemic targets are met. While the cohorts varied significantly in model-assessed insulin resistance, their variability was similar. Such significant intra- and interpatient variability is a further significant cause and marker of glycemic variability in TGC. The results strongly recommended that TGC protocols be explicitly designed to account for significant intra- and interpatient variability in insulin resistance, as well as specifying or having knowledge of carbohydrate administration to minimize variability in glycemic outcomes across diverse cohorts and/or centers.

First pilot trial of the STAR-Liege protocol for tight glycemic control in critically ill patients

“…However, forecasts within stochastically defined prediction ranges (5%-95% and 25%-75%) are lower than expected (71.6% and 26.1%, instead of 90% and 50%, respectively). This result shows that this group of patients had significantly increased variability in insulin sensitivity compared to the stochastic model used to guide control [7], which was also similar to a prior analysis over 200 CHU patients over all days of stay [5].…”

“…This New Zealand patient-based stochastic model was assumed to be broadly applicable to Belgian patients as hour-to-hour insulin sensitivity variability in retrospective comparison is similar [5].…”

“…Hyperglycemia worsens outcomes and increases mortality [1][2][3][4]. Effective glycemic control should reduce blood glucose (BG) levels, reduce variability and account for inter-and intrapatient variability and evolving physiological patient condition [5][6][7]. Some studies have shown that tight glycemic control (TGC) can reduce mortality up to 45% and significantly reduce negative outcomes linked to hyperglycemia [8][9][10].…”

Tight glycemic control in critical care – The leading role of insulin sensitivity and patient variability: A review and model-based analysis

“…However, interestingly, the hourly variations for each cohort shown in Figure 7 indicate that the evolution or intra-patient variability of these cohorts is very similar [107]. These last results seem to reinforce the need to account for both kinds of variability in providing TGC, as it is clear that some adult cohorts will have different inter-patient variability, but potentially quite similar intra-patient variability.…”

“…Certainly, the differences in glycemic variability seen in Figures 1 and 2, are due, at least in part, to the 5x wider range of carbohydrate administration used in Glucontrol at that centre [107], which was based on local standards and clinician specification [46]. Thus, a lack of knowledge of carbohydrate administration, coming from a range of possible sources in the ICU, can multiply the impact of patient-specific variability on the glycemic outcomes of a TGC protocol.…”