Accurate Glycemic Control with STAR

dc.contributor.authorFisk, L.M.
dc.contributor.authorChase, Geoff
dc.contributor.authorLe Compte, A.J.
dc.contributor.authorShaw, Geoff
dc.date.accessioned2012-03-20T03:15:33Z
dc.date.available2012-03-20T03:15:33Z
dc.date.issued2011en
dc.description.abstractBackground: Accurate glycemic control (AGC) has proven difficult without 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 increase safety and performance. Objective: Create a new protocol with improved safety from hypoglycemia and reduced clinical burden using virtual trials, prior to clinical pilot trials. Method: Clinically validated virtual trials were run on 371 virtual patients (39,841 hours) from the SPRINT AGC cohort. Model forecasts target control to a clinically specified glycemic range (80mg/dL to 145mg/dL). Robustness to measurement error limit insulin increases to +2U/hour (max 6U/hour bolus and 3U/hr infusion) and nutrition changes to ±30% (between 30-100% of ACCP goal) per intervention. Measurement intervals of 2-3 hours were used when predicted 5th and/or 95th percentile BG were within target range. Performance was compared to clinical SPRINT and measured as time within glycemic bands, and safety assessed by patients with severe (BG < 40mg/dL) and moderate (BG < 72mg/dL) hypoglycemia. Results: Severe hypoglycemia was reduced from 14 patients (clinical SPRINT data) to 5 with a simultaneous 23% workload reduction from 26,646 BG measurements to 20,591. Moderate hypoglycemia was reduced from 2.89% to 1.33%. Whole-cohort %BG in 80-145mg/dL was 90.6% (86.0% for SPRINT) and enteral nutrition was increased overall by 21% in median amount. Limiting measurement intervals to 2-hourly (as in SPRINT) reduced severe hypoglycemia to 2 patients, reduced moderate hypoglycemia to 0.99% and increased %BG in 80-145mg/dL to 91.5%. Conclusions: Safe, accurate glycemic control that also reduces clinical effort is achieved using stochastic forecasting of potential patient variation. Initial pilot clinical trials are successful and ongoing.en
dc.identifier.citationFisk, L.M., Chase, J.G., Le Compte, A.J., Shaw, G.M. (2011) Accurate Glycemic Control with STAR. San Francisco, CA, USA: 11th Annual Diabetes Technology Meeting (DTM2011), 2011.en
dc.identifier.urihttp://hdl.handle.net/10092/6440
dc.language.isoen
dc.publisherUniversity of Canterbury. Mechanical Engineeringen
dc.rights.urihttps://hdl.handle.net/10092/17651en
dc.subject.anzsrcFields of Research::32 - Biomedical and clinical sciences::3202 - Clinical sciences::320208 - Endocrinologyen
dc.titleAccurate Glycemic Control with STARen
dc.typeConference Contributions - Other
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