Development and Pilot Trial Results of Stochastic Targeted (STAR) Glycemic Control in a Medical ICU

摘要

Accurate glycemic control (AGC) is difficult due to excessive hypoglycemia risk. Stochastic TARgeted (STAR) glycemic control forecasts changes in insulin sensitivity to calculate a range of glycemic outcomes for an insulin intervention, creating a risk framework to improve safety and performance. An improved, simplified STAR framework was developed to reduce light hypoglycemia and clinical effort, while improving nutrition rates and performance. Blood glucose (BG) levels are targeted to 80 - 145mg/dL, using insulin and nutrition control for 1-3 hour interventions. Insulin changes are limited to +3U/hour and nutrition to ±30% of goal rate (minimum 30%). All targets and rate change limits are clinically specified and generalizable. Clinically validated virtual trials were run using clinical data from 371 patients (39,841hours) from the SPRINT cohort. Cohort and per-patient results are compared to clinical SPRINT data. Performance was measured as time within glycemic bands, and safety by patients with severe (BG<40mg/dL) and mild (%BG<72mg/dL) hypoglycemia. Pilot trial results from the first 10 patients (1,458 hours) are included to support the in-silico findings. In both virtual and clinical trials, mild hypoglycemia was below 2% versus 4% for SPRINT. Severe hypoglycemia was reduced from 14 (SPRINT) to 6 (STAR), and 0 in the pilot trial. BG results tighter than SPRINT clinical data, with 91.6% BG within the specified target (80-145mg/dL) in virtual trials and 89.4% in pilot trials. Clinical effort (measurements) was reduced from 16.1/day to 11.8/day (13.5/day in pilot trials). This STAR framework provides safe, accurate glycemic control with significant reductions in hypoglycemia and clinical effort due to stochastic forecasting of patient variation - a unique risk-based approach. Initial pilot trials validate the in silico design methods and resulting protocol, all of which can be generalized to suit any given clinical environment.