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
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
8.46 to 7.26 mmol /L
11.1mmol/L
et al
All patients
LOS >3days
Oxidative stress
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).
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
Liver: poor glycaemic control
Skeletal Muscle
Liver: tight glycaemic control
Skeletal Muscle
AIC1  AIC4: Prior Art
pG
SI
Gmeasured
t
+
• 4 years prior trials
and research
• Models mature
• Adaptive Control
• Short specific trials
Update parameters
u(t)
pG and SI
G   pG G  S I G  Ge 
Gmodelled
Q
1  GQ
 P(t )
u (t )
I  nI  I b  
V
Overall AIC control system concept is well established
The only ways to reduce glucose
levels are:
 increase insulin (Q) which saturates
 decrease feed (P)
G   pG G  S I G  Ge 
Glucose = G
Insulin = Q
Feed = P
Q
1  GQ
 P(t )
Insulin-only (AIC3) control of a patient
Glucose level mmol/l
Tight control target = 4-6 mmol/l
Dextrose feed and Insulin input
Insulin boluses
Feed rate
Time (minutes)
Insulin-feed (AIC4) control of a patient
Glucose level mmol/l
Tight control target = 4-6 mmol/l
Dextrose feed and Insulin input
Feed rate
Insulin boluses
Time (minutes)
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
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…)
SPRINT Step 1 = Feed Rate Table
Requires current glucose
measurement and last
hour change in glucose
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
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
Results
Number of respondents
Nursing survey: SPRINT
15
Very Good
10
Good
Satisfactory
5
Poor
0
Ease of Use
Quality
Suitability
Results
16,063 hours of control on SPRINT; 11,249 measurements
118 admissions
Average APAPCHE II score = 21 (41% risk of death)
Too high
(hypoglycaemia)
(hyperglycaemia)
Number of
measurements
Too low
1500
2003 Retrospective Data (Doran, 2004)
Mean Glucose = 8.1
Lognormal = outliers to high side
Mean
1000
500
0
<4
4 to 6
6 to 8
8 to 10
10 to 12
2003
Numberofof
Number
measurements
measurements
3000
12 to 15
15 to 20
20 plus
Blood glucose [mmol/L]
SPRINT
Mean
2000
2000
Reduction in incidence
of high blood glucose
1000
1000
0
0
<3
<4
3 to
4
4 to 6
4 to 5 to
5
6
6 to
7
6 to 8
7 to
8
8 to 10
8 to
9 to
2005
9
10
10 to 12
10 to 11 to
11
12
Normal distribution -- 90% in desired band
12 to 15
15 to 20
20 plus
12 to 13 to 15 to 18 to
20
[mmol/L]
13
15
17 Blood
20 glucose plus
Tight control:
Tight control:
Tight control within
target bands
Areas under all fitted curves are equal
Poor control:
BG less than
2.5mmol/L =
harmful!!
3.5% of simulated van den Berghe measurements less than 2.5mmol/L
Poor control:
70% of simulated Krinsley
measurements > 7.75 mmol/L
10% of SPRINT ICU measurements
> 7.75 mmol/L
38% of simulated sliding scale
measurements > 7.75 mmol/L
Cumulative distribution function for all blood glucose measurements
Percentiles for ICU data- SPRINT
2.5mmol/L = 4.1x 10-5
3.0mmol/L = 0.001
4.0mmol/L = 0.041
Cumulative probability
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
Glucose mmol/ L
Tight control
15.00
2003 retrospective data
Avg BG
Range
Retroavg
Retrorange
Flatter is better
Tighter is better
15.00
12.50
12.50
Blood 10.00
Glucose
Average
(mmol/l) 7.50
Blood 10.00
Glucose
Average
(mmol/l)
5.00
5.00
2005-06 SPRINT
Avg BG
Max
Retroavg
Retromax
Flatter is better
Tighter is better
7.50
R Sq Linear = 0.652
R Sq Linear = 0.283
R Sq Linear = 0.36
P < 0.05
P < 0.05
2.50
2.50
0.0
5.0
10.0
15.0
20.0
Blood Glucose Range (mmol/l)
5.0
10.0
15.0
20.0
Peak Blood Glucose (mmol/l)
SPRINT is flatter and tighter in both cases (P < 0.05)
R Sq Linear = 0.459
Outcomes:
Tightness of glucose control: the first 118 admissions
Average BG
Average time in 4 -6.1
Average time in 4 -7
Average time in 4 -7.75
Percentage of all measurements less than 4
Percentage of all measurements less than 2.5
Average insulin bolus
Average percentage of goal feed
Average feed rate
(assuming 1.06 cal/ml for feed)
5.9
60%
82%
90%
2.7%
0.1%
2.7
66%
51
1293
mmol/L
All performance indicators agree with
simulation and tight control!
Protocol is safe – no clinically significant
hypoglycaemia
U
Effective use of insulin and nutrition
ml/hr
cal/day
Improved patient outcome: LOS >3 days
.
30%
Mortality %
25%
SPRINT has decreased
mortality by 32%
20%
15%
10%
5%
44 deaths in
169 patients
23 deaths in
118 patients
0%
2004-05
SPRINT
P=0.04
Outcomes:
Tightness of glucose control*
SPRINT Mortality grouped by APACHE II
APACHE II
Number Mortality
0-14
20
5%
15-24
44
20%
25-34
23
26%
35+
6
67%
SPRINT Sepsis data
Total sepsis patients
Total sepsis LOS<3
Total sepsis LOS≥3
Mortality sepsis all
Mortality sepsis LOS<3
Mortality sepsis LOS≥ 3
*
Average APACHE II = 21
* Incomplete data
*
2004-05
Number
104
200
48
7
2004-05
21
3
18
4
1
3
49%
13%
25%
19%
33%
17%
35.0%
37.0%
34.0%
Mortality
1.9%
15.5%
45.8%
71.4%
(% change)
-46%
-10%
-51%
Average APACHE II =18.3
http:/www.geocities.com/active_insulin_control
This is just the beginning…
Aim:
Tight Glycaemic control for everyone with
minimal clinical effort……..
………from babies to adults…..
Acknowledgements
Intensive Care Nursing Staff, Christchurch Hospital
Acknowledgements
AIC1
AIC2
Jessica Lin & AIC3
AIC5: Mike, Aaron and Tim
Dunedin
Assoc. Prof. Geoff
Chase
The Danes
Thomas Lotz
Jason Wong & AIC4
Prof Steen
Andreassen
Dr Kirsten
McAuley
Prof Jim Mann
Maths and Stats Gurus
Dr Dom Lee
Dr Bob
Broughton
Prof
Graeme Wake
Dr Chris Hann