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The SPRINT Protocol for Tight Glycaemic Control Geoffrey M Shaw, J. Geoffrey Chase, Xing-Wei Wong, Thomas Lotz, Jessica Lin, Aaron LeCompte, Timothy Lonergan,

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Presentation on theme: "The SPRINT Protocol for Tight Glycaemic Control Geoffrey M Shaw, J. Geoffrey Chase, Xing-Wei Wong, Thomas Lotz, Jessica Lin, Aaron LeCompte, Timothy Lonergan,"— Presentation transcript:

1 The SPRINT Protocol for Tight Glycaemic Control Geoffrey M Shaw, J. Geoffrey Chase, Xing-Wei Wong, Thomas Lotz, Jessica Lin, Aaron LeCompte, Timothy Lonergan, Michael Willacy and Christopher E. Hann Dept of Intensive Care Christchurch Hospital and Dept of Medicine CSM&HS University of Otago, NZ Dept of Mechanical Engineering, Centre for Bio-Engineering, Universiity of Canterbury, NZ

2 Tight glucose control Hyperglycaemia is prevalent in critical care Impaired endogenous insulin production Increased effective insulin resistance Average blood glucose values > 10mmol/L not uncommon in some critical care units (over length of stay) Stress of condition induces hyperglycaemia Tight control  better outcomes: Reduced mortality Reduced length of stay and length of mechanical ventilation

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5 8.46 to 7.26 mmol /L 11.1 mmol/L

6 et al

7 All patients LOS >3days

8 Oxidative stress Vanhorebeek I. De Vos R, Mesotten D, Wouters P, De Wolf-Peeters C, Van den Berghe G, Protection of hepatocyte mitochondrial ultrastructure and function by strict blood glucose control with insulin in critically ill patients. Lancet 2005;365:53-59 Post-mortem liver biopsies from 20 patients Intensive insulin (11) vs Conventional treatment (9)  Hypertrophic mitochondria with an increased number of abnormal and irregular cristae and reduced matrix electron density were observed in 7 of 9 conventionally treated patients. Only 1 of 11 patients given intensive insulin treatment had these morphological abnormalities (p=0·005).

9 Liver: poor glycaemic control Liver: tight glycaemic control Skeletal Muscle

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11 AIC1  AIC4: Prior Art u(t) G measured G modelled + - Update parameters p G and S I pGpG SISI t 4 years prior trials and research Models mature Adaptive Control Short specific trials Overall AIC control system concept is well established

12 The only ways to reduce glucose levels are:  increase insulin (Q) which saturates  decrease feed (P) Glucose = G Insulin = Q Feed = P

13 Insulin-only (AIC3) control of a patient Dextrose feed and Insulin input Time (minutes) Tight control target = 4-6 mmol/l Insulin boluses Feed rate Glucose level mmol/l

14 Insulin-feed (AIC4) control of a patient Time (minutes) Dextrose feed and Insulin input Tight control target = 4-6 mmol/l Glucose level mmol/l Feed rate Insulin boluses

15 Patient 5 = textbook case Wong, XW, Chase, JG, Shaw, GM, Hann, CE, Lotz, T, Lin, J, Singh-Levett, I, Hollingsworth, L, Wong, OS and Andreassen, S (2006). “Model Predictive Glycaemic Regulation in Critical Illness using Insulin and Nutrition Input: a Pilot Study,” Medical Engineering and Physics, In Press

16 SPRINT Specialised Relative Insulin and Nutrition Table Optimises both insulin and nutrition rates to control glycaemic levels Developed through extensive computer simulation Ensures safe protocol before clinical implementation Simple interface for ease of use by nursing staff Combines the very tight control of computerised simulations with minimal implementation cost (no bedside computer required…)

17 SPRINT Step 1 = Feed Rate Table Requires current glucose measurement and last hour change in glucose

18 SPRINT Step 2 = Insulin Table If feed rate = 0 use only insulin wheel Requires current glucose measurement, last hour change and last hours insulin bolus

19 Patient 5008 Time = 163 hours Mean = 5.4 mmol/L 4-6.1 = 85% 4-7.75 = 97% Avg Feed = 85% Avg Insulin = 3.4 U/hr Lonergan, T, LeCompte, A, Willacy, M, Chase, JG, Shaw, GM, Wong, XW, Lotz, T, Lin, J, and Hann, CE (2006). “A Simple Insulin-Nutrition Protocol for Tight Glycemic Control in Critical Illness: Development and Protocol Comparison,” Diabetes Technology & Therapeutics (DT&T), In Press

20 Nursing survey: SPRINT Results

21 16,063 hours of control on SPRINT; 11,249 measurements 118 admissions Average APAPCHE II score = 21 (41% risk of death) Too low (hypoglycaemia) Too high (hyperglycaemia) 2003 Retrospective Data (Doran, 2004) Mean Glucose = 8.1 Lognormal = outliers to high side 2003 Retrospective Data (Doran, 2004) Mean Glucose = 8.1 Lognormal = outliers to high side SPRINT 0 1000 2000 3000 <33 to 4 4 to 5 5 to 6 6 to 7 7 to 8 8 to 9 9 to 10 10 to 11 11 to 12 12 to 13 13 to 15 15 to 17 18 to 20 plus Number of measurements Reduction in incidence of high blood glucose Results Mean Normal distribution -- 90% in desired band

22 Tight control:

23 Areas under all fitted curves are equal Tight control within target bands Tight control:

24 Poor control: BG less than 2.5mmol/L = harmful!! 3.5% of simulated van den Berghe measurements less than 2.5mmol/L

25 Poor control: 10% of SPRINT ICU measurements > 7.75 mmol/L 70% of simulated Krinsley measurements > 7.75 mmol/L 38% of simulated sliding scale measurements > 7.75 mmol/L

26 Cumulative distribution function for all blood glucose measurements Glucose mmol/ L Cumulative probability Percentiles for ICU data- SPRINT 2.5mmol/L = 4.1x 10 -5 3.0mmol/L = 0.001 4.0mmol/L = 0.041 6.1mmol/L = 0.59 7.0mmol/L = 0.81 7.75mmol/L =0.91 SPRINT ICU raw data- 26-04-06 ICU data- SPRINT (lognormal) 26-04-06 Model simulation- SPRINT (lognormal) Model simulation- van den Berghe (lognormal) Model simulation- Krinsley

27 Tight control 2003 retrospective data2005-06 SPRINT Blood Glucose Average (mmol/l) 5.0 10.0 15.0 20.0 2.50 5.00 7.50 10.00 12.50 15.00 Avg BG Max Retroavg Retromax R Sq Linear = 0.459 R Sq Linear = 0.652 Peak Blood Glucose (mmol/l) Blood Glucose Average (mmol/l) Flatter is better Tighter is better Flatter is better Tighter is better P < 0.05 SPRINT is flatter and tighter in both cases (P < 0.05)

28 0% 5% 10% 15% 20% 25% 30% 2004-05SPRINT Mortality %. SPRINT has decreased mortality by 32% 44 deaths in 169 patients 23 deaths in 118 patients All performance indicators agree with simulation and tight control! Protocol is safe – no clinically significant hypoglycaemia Effective use of insulin and nutrition Tightness of glucose control: the first 118 admissions Improved patient outcome: LOS >3 days Outcomes: Average BG 5.9 mmol/L Average time in 4-6.1 60% Average time in 4-7 82% Average time in 4-7.75 90% Percentageof all measurements less than 4 2.7% Percentage of all measurements less than 2.5 0.1% Average insulin bolus 2.7 U Average percentage of goal feed 66% Average feed rate 51 ml/hr (assuming 1.06 cal/ml for feed) 1293 cal/day P=0.04

29 Tightness of glucose control* Outcomes: SPRINT Mortality grouped by APACHE II2004-05 APACHE IINumberMortalityNumberMortality 0-14205%1041.9% 15-244420%20015.5% 25-342326%4845.8% 35+667%771.4% SPRINT Sepsis data2004-05 (% change) Total sepsis patients2149% Total sepsis LOS<3313% Total sepsis LOS≥31825% Mortality sepsis all419%35.0%-46% Mortality sepsis LOS<3133%37.0%-10% Mortality sepsis LOS ≥ 3317%34.0%-51% * * * Incomplete data Average APACHE II = 21Average APACHE II =18.3

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31 http:/www.geocities.com/active_insulin_control

32 This is just the beginning… Aim: Tight Glycaemic control for everyone with minimal clinical effort…….. ………from babies to adults…..

33 Acknowledgements Intensive Care Nursing Staff, Christchurch Hospital

34 Maths and Stats Gurus Dr Dom Lee Dr Bob Broughton Dr Chris Hann Prof Graeme Wake Thomas Lotz Jessica Lin & AIC3 AIC2 Jason Wong & AIC4 AIC1 The Danes Prof Steen Andreassen Dunedin Dr Kirsten McAuley Prof Jim Mann Assoc. Prof. Geoff Chase AIC5: Mike, Aaron and Tim Acknowledgements


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