Creating smooth SI. B-spline basis function representations of insulin sensitivity

Abstract

Abstract In the intensive care unit (ICU), stress-induced insulin resistance leading to hyperglycemia is commonplace. If safe and effective glycemic control (GC) can be provided, a significant reduction in the negative effects of dysglycemia can be achieved. The Intensive Control Insulin-Nutrition-Glucose (ICING) model has worked particularly well in guiding patient-specific GC. The current method to identify patient- and time- specific insulin sensitivity (SI) with this model employs a discrete stepwise hourly function, which is effective, but not physiologically representative at hourly transitions. 2nd Order B-spline basis functions (BF) are investigated as a more continuous and physiologically relevant alternative for two different cohorts of patient data (Benchmark, 20 patients; Stochastic TARgeted (STAR) sub-cohort, 72 patients). Various knot-widths (KW) of 2nd Order B-spline BFs were investigated and compared to the currently used step function BF in terms of physiological relevance, identifiability, robustness to false measurements, and susceptibility to noise to ensure the most physiologically realistic representation of SI. The 180 min KW 2nd Order B-spline BFs provided the most physiologically realistic fit to the blood glucose (BG) measurements in both cohorts (Standard Deviation of relative fitting error: Benchmark 8.7% vs. 9.35% BG meter, STAR sub-cohort 6.0% vs. 6.0% BG meter), while also having significantly less susceptibility to false BG measurements compared to the current BF. The 180 min 2nd Order B-spline BF provides a smooth second order continuous, more physiologically representative, and identifiable model of the dynamics of SI, and a more realistic resulting BG solution. The outcome provides a promising new addition to the ICING model and STAR GC protocol, while also opening up several new potential continuous time analyses of SI dynamics, not previously possible.