Chase, J.G.

Goldberg, P.A.

Honiden, S.

Inzucchi, S.E.

LeCompte, A.J.

Ramachandran, M.

UC Research Repository

INTRODUCTIONDue to the risk of hypoglycemia, safe, effective and reproducibletight glycemic control (TGC) has proven challenging in theintensive care unit (ICU). Hence, based on recent clinical trials,there is a trend toward less rigid blood glucose (BG) targets1.Based on new guidelines for inpatient glycemic management,the Yale ICU insulin infusion protocol was revised to achieve ahigher BG target of 120-160mg/dL (Yale 2009). The safety andefficacy of the Yale 2009 protocol was evaluated in silico andcompared with the earlier Yale 2005 protocol2 that targeted 90-120mg/dL.A. Le Compte1, M. Ramachandran2, P.A. Goldberg3, S. Honiden3, S.E. Inzucchi3, J.G. Chase11: University of Canterbury, Dept of Mechanical Eng, Christchurch, NZ; 2:Medtronic Diabetes, Northridge, CA, USA ; 3: Yale University School of Medicine, New Haven, CT, USAIn silico Analysis and Optimization of the Yale Insulin Infusion ProtocolMETHODSInsulin-glucose modeling was used to create ‘virtualpatients’ and simulate expected glycemic responsesto different insulin protocols. To validate thesimulation system for the Yale Protocol, simulationresults were compared to reported clinical resultsfor the Yale 2005 protocol (Figure 1):• Clinical data from 54 US cardiac surgery patientstreated with the Yale 2005 protocol2• Virtual patients generated from 40 New Zealandcardiac surgery patients treated with the SPRINTinsulin-dextrose infusion protocol3Next, the Yale 2009 protocol was simulated on thevirtual cohort and compared to the Yale 2005. Thesystem model (Figure 2) has been previouslyvalidated in silico, versus the euglycemic clamp andin several real-time clinical TGC trials in adults andneonates4. To aid direct comparison to the 54-patient clinical results, the 40 patient virtual cohortwas re-sampled to create 1,000 54-patient cohortsusing the bootstrapping method with replacement.RESULTSYale 2005 (90 – 120 mg/dL)Yale 2009(120 – 160 mg/dL)Clinical Simulated SimulatedNumber of patients 54 54 54Mean initial BG level (mg/dL) 189 188 185SD Initial BG level (mg/dL) 44 35 30Median time on protocol (hours) 15 15 18Median time to target (<120 mg/dL) 6 hours 4 hours -Median time to target (<160 mg/dL) - - 2 hoursMedian time to < 140 mg/dL (hours) 5 hours 3 hours 3 hoursFollowing highlighted results are after respective target achieved:% BGs within 80 - 139 mg/dL 86 78 66% BGs within 80 - 199 mg/dL 95 90 99.8% BGs within 90 - 119 mg/dL 60 50 27% BGs within 100 - 139 mg/dL 66 51 56Mean BG (per-patient) (mg/dL) 109 109 130Mean BG (cohort) (mg/dL) 112 110 130Hypoglycemia (BG < 60 mg/dL)% of BG measurements 0.3 0.6 0.0# of patients 3 4 0# of ICU patient days 3.7 4.0 0.0Number of measurements after target 679 708 866Measurements per hour  0.961 0.938Median BG (overall) (mg/dL) 117 135Mean BG (overall) (mg/dL) 124 137% BGs within target rangeAfter target achieved 51 56Overall 37 48Clinical vs. simulated resultsBG outcomes for the Yale 2005 clinicalresults and simulations on the virtual patientcohort were very similar (Table 1):• Mean BG levels within 1-2 mg/dL.• Hypoglycemia rates closely matched tothe observed clinical incidence.The New Zealand SPRINT clinical patientsand, as a result, the in silico cohorts,exhibited some differences to US Yale clinicalpatients:• Higher sensitivity to insulin• Reduced time to BG target• Lower BMIOverall, the well-matched resultsdemonstrate the ability of the in silico modelto capture Yale 2005’s fundamental glycemicdynamics and outcomes.Yale 2009 simulationsThe Yale 2009 simulation results predictexpected shifts in glucose control (Table 1):• Median BG of 135mg/dL (128mg/dLafter reaching target)• Essentially no hypoglycemia.• Possible reduction in BG fingersticksper hourAdditionally, distributions of simulated BGmeasurements indicates that the Yale 2009protocol will effectively shift glycemic levels tothe new higher target range (Figure 3).Table 1: Clinical results for Yale 2005 compared to simulated glycemic outcomes for Yale 2005 and 2009protocols. Highlighted results indicate metrics are computed once patient has reached target BG band forconsistency with reported clinical results2. ‘Overall’ indicates data used for entire simulated protocol usageBrainOthercellsInsulin losses (liver, kidneys)GlucoseInsulinLiverBloodGlucoseLiverInsulin sensitivityIli i iiEffective insulinPlasmaInsulinPancreasFigure 2: Overall insulin-glucose model employed in this study.Model-fitted insulin sensitivity parameter (SI) indicates influence of insulin on glucoseconcentration (G) via uptake by insulin-dependent mechanisms. Simulated insulin kineticsare governed by the model equations for (I) and (Q), plasma and interstitial insulin.REFERENCES[1] E. S. Moghissi, et al., "American Association of Clinical Endocrinologists and American Diabetes Association consensus statement on inpatient glycemic control," Diabetes Care, vol. 32, pp. 1119-31, Jun 2009.[2] P. A. Goldberg, et al., “Clinical results of an updated insulin infusion protocol in critically ill patients," Diabetes Spectrum, vol. 18, pp. 188-191, 2005[3] J. G. Chase, et al., "Implementation and evaluation of the SPRINT protocol for tight glycaemic control in critically ill patients: a clinical practice change," Critical Care, vol. 12, p. R49, 2008.[4] 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.  bodyfracGbodyENDGIGmtVCNSmPtPQQGSGpG*)(*)(1...,kIkQQ   BtukbodyfracIexIIemVtuInII exI))((, *)(1For further information, please contact:Prof. J. Geoffrey ChaseDepartment of Mechanical EngineeringUniversity of Canterburygeoff.chase@canterbury.ac.nzCONCLUSIONS•The in silico analysis indicates that the Yale 2009 protocol will reduce hypoglycemiawithout increasing BG measurement burden, and will maintain glycemia within anew higher target range.•In silico simulation and analysis is a highly effective tool to design, evaluate andoptimize protocols prior to clinical implementation.Figure 1: Simulation method for in-silico protocol comparison.Comparison of Results for the Yale 2005 and  Yale 2009 Protocols Compare median bootstrap in silico results to clinical dataBootstrap to generate results for 54 patient cohortsYale 2005 protocol Yale 2009 protocol40 virtual patients40 cardiac surgery patientsData from patients treated with SPRINT protocolClinicalresults(54 patients)0 50 100 150 200 25000.0050.010.0150.020.025Yale 2005 - BG after target achievedBG [mg/dL]Density  0 50 100 150 200 25000.0050.010.0150.020.025BG [mg/dL]DensityYale 2009 - BG after target achieved  Yale 2009 targetYale 2009Yale 2005 targetYale 2005Figure 3: Distribution of simulated BG measurements for Yale2005 (top panel, blue) and Yale 2009 (bottom panel, red).

In silico Analysis and Optimization of the Yale Insulin Infusion Protocol

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In silico Analysis and Optimization of the Yale Insulin Infusion Protocol

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