SYSTEM AND METHOD FOR ACTIVELY MANAGING TYPE 1 DIABETES MELLITUS ON A PERSONALIZED BASIS

• US 20100137786A1
• Filed: 02/12/2008
• Published: 06/03/2010
• Est. Priority Date: 02/12/2008
• Status: Abandoned Application

• Current Assignee: Clifton A. Alferness, Gust H. Bardy
• Original Assignee: Clifton A. Alferness, Gust H. Bardy
• Inventors: Bardy, Gust H., Alferness, Clifton A.
• Application Number:
  US12/030,087
• Publication Number:
  US 20100137786A1
• Time in Patent Office: Days
• US Class Current: 604/66
• CPC Class Codes: G16H 15/00 ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: G16H 20/17 delivered via infusion or injection
• CPC Class Codes: G16H 20/60 relating to nutrition control, e.g. diets
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders

Abstract

A system and method for actively managing Type 1 diabetes mellitus on a personalized basis is provided. Models of glycemic effect for a Type 1 diabetic patient are established for both insulin time course and digestive response. A rise in postprandial blood glucose is estimated through food ingestion of a planned meal in proportion to the digestive response model. An amount of insulin necessary and timing of delivery to mediate transport of blood glucose into cells in proportion to the postprandial blood glucose rise is determined through the insulin time course model.

Claims

1. A system for actively managing Type 1 diabetes mellitus on a personalized basis, comprising:

a database comprising models of glycemic effect for a Type 1 diabetic patient for both insulin time course and digestive response; and

a forecaster module, comprising;

a blood glucose estimator module configured to estimate a rise in postprandial blood glucose through food ingestion of a planned meal in proportion to the digestive response model; and

an insulin estimator module configured to determine an amount of insulin necessary and timing of delivery to mediate transport of blood glucose into cells in proportion to the postprandial blood glucose rise through the insulin time course model.

2. A system according to claim 1, further comprising:

a library of digestive responses for foods, which include rises in blood glucose particular to the patient, wherein the digestive responses for the foods in the planned meal are aggregated over overlapping time courses as the digestive response model.

3. A system according to claim 2, wherein the library is maintained as glycemic indices, and the glycemic indices for the foods in the planned meal are apportioned as glycemic loads based on portion size.

4. A system according to claim 2, further comprising:

a determination module configured to determine the digestive response model as a summation of the digestive responses for the foods in the planned meal.

5. A system according to claim 4, wherein the summation is adjusted by one or more synergistic effects observed for a combination of a plurality of the foods in the planned meal.

6. A system according to claim 1, further comprising:

a refinement module configured to refine the digestive response model through at least one of preprandial and postprandial blood glucose testing.

7. A system according to claim 1, further comprising:

a model of glycemic effect for a medication other than insulin, wherein a physiological effect on the postprandial blood glucose due to dosing of the medication is determined over a time course of the insulin.

8. A system according to claim 1, wherein the models are expressed as coefficients respectively applied to a population-based insulin time course and empirically-derived digestive response.

9. A system according to claim 1, further comprising:

a display module configured to interact directly with the patient, comprising one or more of;

a suggestion module configured to suggest times for self-testing blood glucose;

an alert module configured to generate alerts regarding blood glucose;

a reminder module configured to provide reminders regarding insulin; and

an intervention module configured to intervene through communication with a caregiver on behalf of the patient.

10. A method for actively managing Type 1 diabetes mellitus on a personalized basis, comprising:

establishing models of glycemic effect for a Type 1 diabetic patient for both insulin time course and digestive response;

estimating a rise in postprandial blood glucose through food ingestion of a planned meal in proportion to the digestive response model; and

determining an amount of insulin necessary and timing of delivery to mediate transport of blood glucose into cells in proportion to the postprandial blood glucose rise through the insulin time course model.

11. A method according to claim 10, further comprising:

referencing a library of digestive responses for foods, which include rises in blood glucose particular to the patient; and

aggregating the digestive responses for the foods in the planned meal over overlapping time courses as the digestive response model.

12. A method according to claim 11, further comprising:

maintaining the library as glycemic indices; and

apportioning the glycemic indices for the foods in the planned meal as glycemic loads based on portion size.

13. A method according to claim 11, further comprising:

determining the digestive response model as a summation of the digestive responses for the foods in the planned meal.

14. A method according to claim 13, further comprising:

adjusting the summation by one or more synergistic effects observed for a combination of a plurality of the foods in the planned meal.

15. A method according to claim 10, further comprising:

refining the digestive response model through at least one of preprandial and postprandial blood glucose testing.

16. A method according to claim 10, further comprising:

establishing a model of glycemic effect for a medication other than insulin; and

determining a physiological effect on the postprandial blood glucose due to dosing of the medication over a time course of the insulin.

17. A method according to claim 10, further comprising:

expressing the models as coefficients respectively applied to a population-based insulin time course and empirically-derived digestive response.

18. A method according to claim 10, further comprising:

interacting directly with the patient, comprising one or more of;

suggesting times for self-testing blood glucose;

generating alerts regarding blood glucose;

providing reminders regarding insulin; and

intervening through communication with a caregiver on behalf of the patient.