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Real-Time hypoglycemia prediction suite using continuous glucose monitoring: a safety net for the artificial pancreas.

Dassau E, Cameron F, Lee H, Bequette BW, Zisser H, Jovanovic L, Chase HP, Wilson DM, Buckingham BA, Doyle FJ - Diabetes Care (2010)

Bottom Line: We confirmed the function of the HPA using a separate dataset from 22 admissions of type 1 diabetic subjects.When four of five algorithms were required to be positive, then 82% of the events were predicted.The HPA will enable automated insulin-pump suspension in response to a pending event that has been detected prior to severe immediate complications.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemical Engineering, University of California Santa Barbara, Santa Barbara, California, USA. dassau@engineering.ucsb.edu

ABSTRACT

Objective: The purpose of this study was to develop an advanced algorithm that detects pending hypoglycemia and then suspends basal insulin delivery. This approach can provide a solution to the problem of nocturnal hypoglycemia, a major concern of patients with diabetes.

Research design and methods: This real-time hypoglycemia prediction algorithm (HPA) combines five individual algorithms, all based on continuous glucose monitoring 1-min data. A predictive alarm is issued by a voting algorithm when a hypoglycemic event is predicted to occur in the next 35 min. The HPA system was developed using data derived from 21 Navigator studies that assessed Navigator function over 24 h in children with type 1 diabetes. We confirmed the function of the HPA using a separate dataset from 22 admissions of type 1 diabetic subjects. During these admissions, hypoglycemia was induced by gradual increases in the basal insulin infusion rate up to 180% from the subject's own baseline infusion rate. RESULTS Using a prediction horizon of 35 min, a glucose threshold of 80 mg/dl, and a voting threshold of three of five algorithms to predict hypoglycemia (defined as a FreeStyle plasma glucose readings <60 mg/dl), the HPA predicted 91% of the hypoglycemic events. When four of five algorithms were required to be positive, then 82% of the events were predicted.

Conclusions: The HPA will enable automated insulin-pump suspension in response to a pending event that has been detected prior to severe immediate complications.

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Related in: MedlinePlus

Hypoglycemia alarm flowchart. The overall alarming algorithm combines multiple independent alarms into one single alarm using a voting system, where APS is the artificial Pancreas Software (24) feeding the data to the algorithms, LP is the linear prediction algorithm, SP is statistical prediction algorithm, KF is the Kalman filter algorithm, HIIR is the hybrid impulse response filter, and NLA is the numerical logical algorithm.
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Figure 1: Hypoglycemia alarm flowchart. The overall alarming algorithm combines multiple independent alarms into one single alarm using a voting system, where APS is the artificial Pancreas Software (24) feeding the data to the algorithms, LP is the linear prediction algorithm, SP is statistical prediction algorithm, KF is the Kalman filter algorithm, HIIR is the hybrid impulse response filter, and NLA is the numerical logical algorithm.

Mentions: The core of the HPA is a set of individual alarms that are combined through a voting system into one combined alarm. With each new CGM datum, each individual alarm will run independently and will indicate hypoglycemia or euglycemia. Then, if the number of individual alarms that have gone off in the last 10 min is above a preset voting threshold (V), the voting alarm will trigger. A low voting threshold will generate more alarms, giving more warning but less accuracy. Finally, the combined alarm will trigger if either the voting alarm or the threshold alarm goes off. Figure 1 shows the flow of the combined hypoglycemic detection algorithm (14). Glucose predictions and analysis from CGM data can be performed in more than one way by applying different mathematical methods such as optimal estimation techniques (15,16), time series (17), and other methods. The HPA system consists of five prediction algorithms:


Real-Time hypoglycemia prediction suite using continuous glucose monitoring: a safety net for the artificial pancreas.

Dassau E, Cameron F, Lee H, Bequette BW, Zisser H, Jovanovic L, Chase HP, Wilson DM, Buckingham BA, Doyle FJ - Diabetes Care (2010)

Hypoglycemia alarm flowchart. The overall alarming algorithm combines multiple independent alarms into one single alarm using a voting system, where APS is the artificial Pancreas Software (24) feeding the data to the algorithms, LP is the linear prediction algorithm, SP is statistical prediction algorithm, KF is the Kalman filter algorithm, HIIR is the hybrid impulse response filter, and NLA is the numerical logical algorithm.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2875433&req=5

Figure 1: Hypoglycemia alarm flowchart. The overall alarming algorithm combines multiple independent alarms into one single alarm using a voting system, where APS is the artificial Pancreas Software (24) feeding the data to the algorithms, LP is the linear prediction algorithm, SP is statistical prediction algorithm, KF is the Kalman filter algorithm, HIIR is the hybrid impulse response filter, and NLA is the numerical logical algorithm.
Mentions: The core of the HPA is a set of individual alarms that are combined through a voting system into one combined alarm. With each new CGM datum, each individual alarm will run independently and will indicate hypoglycemia or euglycemia. Then, if the number of individual alarms that have gone off in the last 10 min is above a preset voting threshold (V), the voting alarm will trigger. A low voting threshold will generate more alarms, giving more warning but less accuracy. Finally, the combined alarm will trigger if either the voting alarm or the threshold alarm goes off. Figure 1 shows the flow of the combined hypoglycemic detection algorithm (14). Glucose predictions and analysis from CGM data can be performed in more than one way by applying different mathematical methods such as optimal estimation techniques (15,16), time series (17), and other methods. The HPA system consists of five prediction algorithms:

Bottom Line: We confirmed the function of the HPA using a separate dataset from 22 admissions of type 1 diabetic subjects.When four of five algorithms were required to be positive, then 82% of the events were predicted.The HPA will enable automated insulin-pump suspension in response to a pending event that has been detected prior to severe immediate complications.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemical Engineering, University of California Santa Barbara, Santa Barbara, California, USA. dassau@engineering.ucsb.edu

ABSTRACT

Objective: The purpose of this study was to develop an advanced algorithm that detects pending hypoglycemia and then suspends basal insulin delivery. This approach can provide a solution to the problem of nocturnal hypoglycemia, a major concern of patients with diabetes.

Research design and methods: This real-time hypoglycemia prediction algorithm (HPA) combines five individual algorithms, all based on continuous glucose monitoring 1-min data. A predictive alarm is issued by a voting algorithm when a hypoglycemic event is predicted to occur in the next 35 min. The HPA system was developed using data derived from 21 Navigator studies that assessed Navigator function over 24 h in children with type 1 diabetes. We confirmed the function of the HPA using a separate dataset from 22 admissions of type 1 diabetic subjects. During these admissions, hypoglycemia was induced by gradual increases in the basal insulin infusion rate up to 180% from the subject's own baseline infusion rate. RESULTS Using a prediction horizon of 35 min, a glucose threshold of 80 mg/dl, and a voting threshold of three of five algorithms to predict hypoglycemia (defined as a FreeStyle plasma glucose readings <60 mg/dl), the HPA predicted 91% of the hypoglycemic events. When four of five algorithms were required to be positive, then 82% of the events were predicted.

Conclusions: The HPA will enable automated insulin-pump suspension in response to a pending event that has been detected prior to severe immediate complications.

Show MeSH
Related in: MedlinePlus