Post on 26-Jul-2015
Profiling Intra-patient Type 1 Diabetes Behaviours
Iván Contreras
OUTLINE
• Introduction
•Methodology: Hidden Patterns
• In Silico Validation
• In Vivo Experiments
•Current and Future Work
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Type 1 Diabetes
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• Incurable disease
– Autoimmune attack on β-cells
– Hyperglycemia
– 5%-10%
• Intensive insulin treatments
– Multiple Daily injections
– Continuous Subcutaneous Insulin Infusion
– Hypoglucemia
Cardiovascular complications
Diabetic coma
Epileptic fit
Diabetic coma
Type 1 Diabetes
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• Artificial Pancreas
– Limited capacity to extract information
– High Variability
• Seasons, age, habits, menstural period, etc.
• Devoted to provide an innovative tool
– Cope to overload information
– Better Management
• Profile daily patterns
– Improved treatments
– Better control
– Close loop algorithms symbiosis
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Introduction: General Objective
• Introduction
•Methodology :Hidden Patterns •Diabetes: Normalized Compression Distance
• In Silico Validation
• In Vivo Experiments
•Current and Future Work
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OUTLINE
Recommendation ranges for the standardization of glucose
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GREEN: GGGHGBBBGBHHGBBBGBAA
BLUE: GBEDBGEEBEGBHEBBCCAB
RED: GBEDBGEEBEGBGEECEBBB
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Modified Normalized Compression Distance
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OUTLINE
• Introduction
•Methodology :Hidden Patterns
• In Silico Validation
• In Vivo Experiments
•Current and Future Work
In Silico Experiments: A Proof of Concept
•Mathematical models of diabetic patients
•Not guarantee in vivo performance
•Limitations and efficiency
•Girona APSim and LabVIEW software
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In Silico Experiments: Scenarios
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A
B
C
•10 Dalla Man patients
• Insulin Pump
• Individualized variations
• Value per minute
• Mixed meals libraries
• Scenario A features
• Exercise each two days (45 min.)
• Varying intensities
• Scenario B features
• Snack before exercise
In Silico Experiments: Scenarios Example
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In Silico Experiments: Good & Bad Control patients
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Number of hypoglycemia
Basic Exercise Exercise + Snack
P1 2 9 3
P2 1 8 1
P3 0 13 4
P4 0 14 12
P5 1 13 3
P6 2 13 15
P7 2 12 17
P8 1 6 1
P9 3 10 3
P10 0 8 1
Poorly controlled
Well controlled
Patient 7 Results
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In Silico Experiments:
Patient 4 Results
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In Silico Experiments:
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In Silico Experiments: Patient 1 Results
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In Silico Experiments: Patient 9 Results
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OUTLINE
• Introduction
•Methodology :Hidden Patterns
• In Silico Validation
• In Vivo Experiments
•Current and Future Work
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• Complex task : Collection, noise, consistent
database, etc.
• 10 patient of the hospital Clínic i Universitari of
Barcelona.
• Continuous subcutaneous insulin infusion therapy
• Tagged with temporal information : weekends and
bank days with differentiated profiles.
In Vivo Experiments: Patients
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In Vivo Experiments: Patient 3 Results
Clusters
A B C D E
Days 5 19 23 13 13
AvgBG 130 155 142 135 137
AvgVBG 0,3 0,3 0,2 0,2 0,3
StdVBG 0,06 0,07 0,05 0,02 0,08
AUC(180) 2,8 11,7 3,2 1,0 6,1
AUC(70) 0,46 0,05 0,07 0,05 0,25
Carbs 13,3 13,8 13,9 13,4 15,0
In/Carbs 1,82 1,95 1,69 1,67 1,78
T.Ins. 63,7 65,8 64,0 63,1 64,2
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In Vivo Experiments: Patient 5 Results
Clusters
A B C D E
Days 9 9 19 9 14
AvgBG 126 154 136 119 122
AvgVBG 0,3 0,3 0,4 0,4 0,3
StdVBG 0,04 0,05 0,07 0,08 0,06
AUC(180) 2,7 10,9 11,4 6,7 4,0
AUC(70) 0,83 0,24 2,12 2,88 1,43
Carbs 30,3 30,3 29,3 28,7 31,9
In/Carbs 1,30 1,24 1,44 1,30 1,32
T.Ins. 46,0 46,1 48,9 43,6 47,6
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In Vivo Experiments: Patient 1 Results
Clusters
A B C D
Days 29 9 17 34
AvgBG 180 151 167 178
AvgVBG 0,3 0,2 0,3 0,4
StdVBG 0,07 0,04 0,05 0,07
AUC(180) 24,7 5,8 14,9 26,5
AUC(70) 0,35 0,03 0,18 0,60
Carbs 17,8 15,6 15,5 14,8
In/Carbs 0,83 0,69 0,80 1,89
T.Ins. 37,9 34,6 35,2 35,5
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OUTLINE
• Introduction
•Methodology :Hidden Patterns
• In Silico Validation
• In Vivo Experiments
•Current and Future Work
Current and Future Work
• Profiling time series
• Real tagged information: premenstrual, pregnancy, etc.
• Automatic classification
• Glucose prediction
• Complex models : Real behaviors
• Multi-objective algorithms
• Intra-patient models prediction
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THE END