INTRODUCTION Stress-induced hyperglycaemia is common in critical care 1

1. Time to band average of 6 hours and control maintained throughout patient stay 0.35 Clinical ICU data - SPRINT Simulation - van den Berghe 0.3 Simulation - Krinsley Simulation - Insulin sliding scale Simulation - SPRINT 0.25 Simulation predictions match clinical results. 0.2 Density 0.15 0.1 0.05 5 10 15 20 25 Blood glucose [mmol/L] 14 12 100 100 SPRINT - ICU Mortality SPRINT - Hospital Mortality Retrospective - ICU Mortality 10 90 Retrospective - Hospital Mortality 90 80 8 80 Average BG [mmol/L] 70 6 70 60 Percent Percent Significance in mortality reductions improves with increasing stay 4 60 50 2 50 40 40 0 30 0 5 10 15 20 25 30 35 40 45 Time since initiation of SPRINT [hours] 0 5 10 15 20 25 30 0 5 10 15 20 25 30 Time (days) Time (days) Tight Glycaemic Control in Critical Care Using Insulin and Nutrition: The SPRINT Protocol JG Chase, G. Shaw, A. Le Compte, D. Lee, T. Lonergan, M. Willacy, J. Wong, J. Lin, T. Lotz, C. Hann • INTRODUCTION • Stress-induced hyperglycaemia is common in critical care1 • Hyperglycaemia worsens patient outcomes, increasing risk of infection2, myocardial infarction1, polyneuropathy and multi-organ failure3 • Published protocols require significant added clinical effort4 • Very high effective insulin resistance challenges insulin-only protocols4,5 • Model-based protocols that modulate both insulin and nutrition have shown promising results, however computational resources are not typically available in critical care • SPRINT is an easy-to-use alternative that provides control equivalent to model-based methods RESULTS & CONCLUSIONS METHOD: SPRINT (Specialised Relative Insulin-Nutrition Tables) • Over 23,000 hours of control for 165 severely ill patients • Tight control to the 4-6 mmol/L and 4-7.75 mmol/L bands • No clinically significant hypoglycaemia • Developed from model-based methods using virtual cohorts6 • Nurse-driven protocol requires no external clinical intervention • Hourly blood glucose measurements to gain control. Two-hourly measurements once stable to reduce clinical effort • Insulin administered in bolus form for patient safety • “Goal feed” computed based on age, size and gender, effectively customising the protocol for each patient5 • Nutrition optimised to improve critical care outcome7 • Easy-to-implement protocol gained high level of support from clinical and nursing staff and minimum non-compliance (<0.1%) • Statistically significant reductions in mortality compared to similar hyperglycaemic retrospective cohort (APACHE II =21, Risk of Death = 33%) REFERENCES [1] S. E. Capes, et al., "Stress hyperglycaemia and increased risk of death after myocardial infarction in patients with and without diabetes: a systematic overview," Lancet, vol. 355, pp. 773-778, 2000. [2] B. R. Bistrian, "Hyperglycemia and Infection: Which is the Chicken and Which is the Egg?," JPEN J Parenter Enteral Nutr, vol. 25, pp. 180-181, 2001. [3] G. Van den Berghe, et al., "Intensive insulin therapy in the critically ill patients," N Engl J Med, vol. 345, pp. 1359-1367, 2001. [4] S. Meijering, et al., "Towards a feasible algorithm for tight glycaemic control in critically ill patients: a systematic review of the literature," Crit Care, vol. 10, pp. R19, 2006. [5] G. M. Shaw, et al., "Rethinking glycaemic control in critical illness - from concept to clinical practice change," Crit Care Resusc, vol. 8, pp. 90-9, 2006. [6] T. Lonergan, et al., "A Simple Insulin-Nutrition Protocol for Tight Glycemic Control in Critical Illness: Development and Protocol Comparison," Diabetes Technol Ther, vol. 8, pp. 191-206, 2006. [7] J. A. Krishnan, et al., "Caloric intake in medical ICU patients: consistency of care with guidelines and relationship to clinical outcomes," Chest, vol. 124, pp. 297-305, 2003. • Improved ICU and hospital survival.