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INTRODUCTION • Stress-induced hyperglycaemia is common in critical care 1 • Hyperglycaemia worsens patient outcomes, increasing risk of infection 2 , myocardial infarction 1 , polyneuropathy and multi-organ failure 3 • Published protocols require significant added clinical effort 4 • Very high effective insulin resistance challenges insulin-only protocols 4,5 • 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 • Developed from model-based methods using virtual cohorts 6 • 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 patient 5 • Nutrition optimised to improve critical care outcome 7 • Easy-to-implement protocol gained high level of support from clinical and nursing staff and minimum non-compliance (<0.1%) JG Chase, G. Shaw, A. Le Compte, D. Lee, T. Lonergan, M. Willacy, J. Wong, J. Lin, T. Lotz, C. Hann Tight Glycaemic Control in Critical Care Using Insulin and Nutrition: The SPRINT Protocol METHOD: SPRINT (Specialised Relative Insulin-Nutrition Tables) RESULTS & CONCLUSIONS 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. • 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 • Statistically significant reductions in mortality compared to similar hyperglycaemic retrospective cohort (APACHE II =21, Risk of Death = 33%) Time (days) 30 25 20 15 10 5 0 100 90 80 70 60 50 40 SPRINT - ICU Mortality Retrospective - ICU Mortality Percent Time (days) 30 25 20 15 10 5 0 100 90 80 70 60 50 40 30 SPRINT - Hospital Mortality Retrospective - Hospital Mortality Percent • Improved ICU and hospital survival. 0 5 10 15 20 25 30 35 40 45 0 2 4 6 8 10 12 14 Time since initiation of SPRINT [hours] Average BG [mmol/L] Time to band average of 6 hours and control maintained throughout patient stay 0% 5% 10% 15% 20% 25% 30% 3 days 4 days 5 days Length ofIC U stay P ercentage m ortality R etrospective SPRINT 33% reduction in m ortality (p=0.04) 41% reduction in m ortality (p=0.03) 46% reduction in m ortality (p=0.03) Significance in mortality reductions improves with increasing stay Overall data (n=15,874 measurements) Numberofpatients 165 H ours ofcontrol 23,324 hours APAC H E IIscore 20 ± 7.8 APAC H E IIrisk ofdeath 36% ± 25% Total BG m easurem ents 15,874 BG m ean 5.9 [4.1 – 8.3]* mmol/L BG standard deviation 1.3 mmol/L Percentage betw een 4-6.1 m mol/L 61% Percentage betw een 4-7.0 m mol/L 82% Percentage betw een 4-7.75 m mol/L 89% Percentage < 4 m mol/L 3.3% Percentage < 2.5 m mol/L 0.1% Total < 2.2 m mol/L 6 Per-patient data (n=165 patients) H ours ofcontrol 95 [12 – 447]* hours Num berofm easurem ents 68 [10 – 271]* BG m ean 5.9 [5.0 – 7.4]* mmol/L BG standard deviation 1.1 [0.7 – 2.3]* mmol/L Average hourly insulin 2.5 [1.3 – 4.1]* U Average nutrition rate (R ESO UR CE D iabetic) 37.5 [0 – 80.3]* m l/hr (caloric density 1.06 cal/m L) 954 [0 – 2043]* kCal/day * 5 th – 95 th percentile range 5 10 15 20 25 0.05 0.1 0.15 0.2 0.25 0.3 0.35 Blood glucose [mmol/L] Density Clinical ICU data - SPRINT Simulation - van den Berghe Simulation - Krinsley Simulation - Insulin sliding scale Simulation - SPRINT Simulation predictions match clinical results. l e e h W n i l u s n I t h g i r y p o C T N I R P S h c r a e s e R C I A 6 0 0 2 6 0 0 2 / 1 / 2 1 S E Y n i l u s n i y n a e v i g t o n o D r u o h s i h t . 1 t s e t a l e h t s I e s o c u l g d o o l b L / l o m m 7 r e d n u r o d n a t i s a h d e p p o r d s u o i v e r p e h t m o r f t n e m e r u s a e m ? 5 . 1 n a h t e r o m y b w o l e b s p e t s e h t w o l l o F : O N . 2 t n e i t a p o t l e e h w e t a t o R l e v e l e s o c u l g t n e r r u c n i d e k r a m . y e r g . 3 e h t r e h t e h w e n i m r e t e D l e v e l e s o c u l g r o d e s a e r c n i s a h d n a d e s a e r c e d e h t t c e l e s l e e h w e h t f o e d i s t c e r r o c . 4 e h t g n i s U f o e d i s d e t c e l e s l e e h w e h t 3 m o r f e h t h c t a m , s u l o b n i l u s n i s u o i v e r p e h t o t s u l o b n i l u s n i w e n . 6 e v a h u o y f i l e e h W d e e F e s U . y d a e r l a o s e n o d t o n . 5 r e t s i n i m d A s u l o b n i l u s n i w e n . k c e h c e l b u o d e u g a e l l o c e v a h d n a : T R A T S l e e h W d e e F % 0 8 % 0 9 % 0 9 % 0 0 1 % 0 8 % 0 9 % 0 9 % 0 0 1 % 0 7 % 0 8 % 0 8 % 0 9 % 0 7 % 0 8 % 0 8 % 0 9 % 0 6 % 0 7 % 0 8 % 0 8 % 0 6 % 0 7 % 0 8 % 0 8 % 0 5 % 0 6 % 0 7 % 0 7 % 0 5 % 0 6 % 0 7 % 0 7 % 0 4 % 0 5 % 0 6 % 0 6 % 0 4 % 0 5 % 0 6 % 0 6 % 0 3 % 0 4 % 0 5 % 0 5 % 0 3 % 0 4 % 0 5 % 0 5 % 0 3 % 0 3 % 0 4 % 0 4 % 0 3 % 0 3 % 0 4 % 0 4 % 0 9 % 0 0 1 % 0 0 1 % 0 0 1 % 0 9 % 0 0 1 % 0 0 1 % 0 0 1 % 0 8 % 0 9 % 0 9 % 0 0 1 % 0 8 % 0 9 % 0 9 % 0 0 1 % 0 7 % 0 8 % 0 8 % 0 9 % 0 7 % 0 8 % 0 8 % 0 9 % 0 6 % 0 7 % 0 8 % 0 8 % 0 6 % 0 7 % 0 8 % 0 8 % 0 5 % 0 6 % 0 7 % 0 7 % 0 5 % 0 6 % 0 7 % 0 7 % 0 4 % 0 5 % 0 6 % 0 6 % 0 4 % 0 5 % 0 6 % 0 6 % 0 3 % 0 4 % 0 5 % 0 5 % 0 3 % 0 4 % 0 5 % 0 5 % 0 3 % 0 3 % 0 4 % 0 4 % 0 3 % 0 3 % 0 4 % 0 4 % 0 9 % 0 0 1 % 0 0 1 % 0 0 1 % 0 9 % 0 0 1 % 0 0 1 % 0 0 1 d e e f h c a t t A n o i s r e v n o c e r e h r e k c i t s d e e f h c a t t A n o i s r e v n o c e r e h r e k c i t s t h g i r y p o C T N I R P S h c r a e s e R C I A 6 0 0 2 / 1 / 2 1 : T R A T S . 2 t n e i t a p o t l e e h w e t a t o R d e e f e g a t n e c r e p t n e r r u c l e v e l n i d e k r a m y e r g . 4 e h t g n i s U e d i s d e t c e l e s l e e h w e h t f o 3 m o r f h c t a m , e h t l e v e l e s o c u l g t n e r r u c e h t o t l e v e l d e e f w e n . 5 n o i s r e v n o c d e e f e h t e s U e t u l o s b a e h t d n i f o t r e k c i t s . ] r h / l m [ n i d e e f . 1 n o i s r e v n o c d e e f e h t e s U t n e r r u c e h t d n i f o t r e k c i t s . l e v e l d e e f e g a t n e c r e p . 3 t s e t a l e h t s I d o o l b L / l o m m 7 e s o c u l g r e d n u r o d n a t i s a h d e p p o r d e h t m o r f t n e m e r u s a e m s u o i v e r p y b ? 5 . 1 n a h t e r o m : O N e d i s e s U f o l e e h w . 6 u o y f i l e e h W n i l u s n I e s U . y d a e r l a o s e n o d t o n e v a h : S E Y e d i s e s U f o l e e h w G o al fe ed : 90 m l/hr 30 % 26 m l/hr 40 % 36 m l/hr 50 % 45 m l/hr 60 % 53 m l/hr 70 % 62 m l/hr 80 % 72 m l/hr 90 % 81 m l/hr 100 % 90 m l/hr

INTRODUCTION Stress-induced hyperglycaemia is common in critical care 1 Hyperglycaemia worsens patient outcomes, increasing risk of infection 2, myocardial

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Page 1: INTRODUCTION Stress-induced hyperglycaemia is common in critical care 1 Hyperglycaemia worsens patient outcomes, increasing risk of infection 2, myocardial

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

• 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%)

JG Chase, G. Shaw, A. Le Compte, D. Lee, T. Lonergan, M. Willacy, J. Wong, J. Lin, T. Lotz, C. Hann

Tight Glycaemic Control in Critical Care Using Insulin and Nutrition: The SPRINT

Protocol

METHOD: SPRINT(Specialised Relative Insulin-Nutrition Tables)

RESULTS & CONCLUSIONS

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.

• 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

• Statistically significant reductions in mortality compared to similar hyperglycaemic retrospective cohort (APACHE II =21, Risk of Death = 33%)

Time (days)302520151050

100

90

80

70

60

50

40

SPRINT - ICU MortalityRetrospective - ICU Mortality

Per

cen

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Time (days)

302520151050

100

90

80

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60

50

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30

SPRINT - Hospital Mortality

Retrospective - Hospital Mortality

Perc

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• Improved ICU and hospital survival.

0 5 10 15 20 25 30 35 40 450

2

4

6

8

10

12

14

Time since initiation of SPRINT [hours]

Ave

rage

BG

[mm

ol/L

]

Time to band average of 6 hours and control maintained throughout patient stay

0%

5%

10%

15%

20%

25%

30%

3 days 4 days 5 days

Length of ICU stay

Perc

en

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e m

ort

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Retrospective

SPRINT

33% reduction in mortality (p=0.04)

41% reduction in mortality (p=0.03)

46% reduction in mortality (p=0.03)

Significance in mortality reductions improves with increasing stay

Overall data (n=15,874 measurements) Number of patients 165 Hours of control 23,324 hours APACHE II score 20 ± 7.8 APACHE II risk of death 36% ± 25% Total BG measurements 15,874 BG mean 5.9 [4.1 – 8.3]* mmol/L BG standard deviation 1.3 mmol/L Percentage between 4-6.1 mmol/L 61% Percentage between 4-7.0 mmol/L 82% Percentage between 4-7.75 mmol/L 89% Percentage < 4 mmol/L 3.3% Percentage < 2.5 mmol/L 0.1% Total < 2.2 mmol/L 6 Per-patient data (n=165 patients) Hours of control 95 [12 – 447]* hours Number of measurements 68 [10 – 271]* BG mean 5.9 [5.0 – 7.4]* mmol/L BG standard deviation 1.1 [0.7 – 2.3]* mmol/L Average hourly insulin 2.5 [1.3 – 4.1]* U Average nutrition rate (RESOURCE Diabetic) 37.5 [0 – 80.3]* ml/hr (caloric density 1.06 cal/mL) 954 [0 – 2043]* kCal/day

* 5th – 95th percentile range

5 10 15 20 25

0.05

0.1

0.15

0.2

0.25

0.3

0.35

Blood glucose [mmol/L]D

ensi

ty

Clinical ICU data - SPRINTSimulation - van den BergheSimulation - KrinsleySimulation - Insulin sliding scaleSimulation - SPRINT

Simulation predictions match clinical results.

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26m l/hr

40%

36m l/hr

50%

45m l/hr

60%

53m l/hr

70%

62m l/hr

80%

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90m l/hr