Method, system, and computer program product for the evaluation of glycemic control in diabetes from self-monitoring data

• US 7,874,985 B2
• Filed: 12/19/2005
• Issued: 01/25/2011
• Est. Priority Date: 03/29/2000
• Status: Active Grant

• Current Assignee: University of Virginia Patent Foundation (University of Virginia)
• Original Assignee: University of Virginia Patent Foundation (University of Virginia)
• Inventors: Cox, Daniel J., Kovatchev, Boris P.
• Primary Examiner(s): Mallari; Patricia C
• Application Number:
  US11/305,946
• Publication Number:
  US 20060094947A1
• Time in Patent Office: 1,863 Days
• Field of Search: 600/347, 600/365
• US Class Current: 600/365
• CPC Class Codes: A61B 5/0002 Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network A61B5/07 takes precedence; transmission systems for measured values G08C; transmission H04B; transmission of digital information H04L; wireless communication networks H04W
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: G16H 10/40 for data related to laboratory analysis, e.g. patient specimen analysis
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders

Abstract

A method, system, and computer program product related to the diagnosis of diabetes, and is directed to predicting the long-term risk of hyperglycemia, and the long-term and short-term risks of severe hypoglycemia in diabetics, based on blood glucose readings collected by a self-monitoring blood glucose device. The method, system, and computer program product pertain directly to the enhancement of existing home blood glucose monitoring devices, by introducing an intelligent data interpretation component capable of predicting both HbA_1c and periods of increased risk of hypoglycemia, and to the enhancement of emerging continuous monitoring devices by the same features. With these predictions the diabetic can take steps to prevent the adverse consequences associated with hyperglycemia and hypoglycemia.

Claims

1. A computerized method for evaluating hemoglobin A_1c (HbA_1c) of a patient based on blood glucose (BG) data collected over a predetermined duration, said method comprising:

computing on a computer weighted deviation of the BG of said patient toward high blood glucose (WR) from a predefined normal level;

computing on a computer mean blood glucose (Dr); and

estimating on a computer HbA_1c using a predetermined mathematical formula based on said computed WR and Dr;

defining predetermined categories for the estimate of HbA_1c, each of said HbA_1c estimate categories representing a range of values for estimated HbA_1c; and

assigning said estimated HbA_1c to at least one of said HbA_1c estimate categories.

2. The method of claim 1, wherein:

said computed WR is mathematically defined from a series of BG readings x₁, x₂, . . . x_n taken at time points t₁, t₂, . . . t_n as;

3. The method of claim 1, wherein said estimating HbA_1c from said BG monitoring data comprises determining Estimated HbA_1c according to:

Estimated HbA_1c=0.9008(WR)−

0.8207(DR)+6.7489.

4. The method of claim 1, wherein said HbA_1c estimate categories are defined as follows:

classified category 1, wherein said estimated HbA_1c is less than about 7.8;

classified category 2, wherein said estimated HbA_1c is between about 7.8 and about 8.5;

classified category 3, wherein said estimated HbA_1c is between about 8.5 and about 9.0;

classified category 4, wherein said estimated HbA_1c is between about 9.0 and about 9.6;

classified category 5, wherein said estimated HbA_1c is between about 9.6 and about 10.3;

classified category 6, wherein said estimated HbA_1c is between about 10.3 and about 11.0; and

classified category 7, wherein said estimated HbA_1c is above about 11.0.

5. The method of claim 4, further comprising:

defining predicted confidence intervals for corresponding said HbA_1c estimate categories, wherein said predicted confidence intervals are defined as follows;

said classified category 1 corresponds with a predicted HbA_1c less than about 8.0;

said classified category 2 corresponds with a predicted HbA_1c between about 8.0 and about 8.5;

said classified category 3 corresponds with a predicted HbA_1c between about 8.5 and about 9.0;

said classified category 4 corresponds with a predicted HbA_1c between about 9.0 and about 9.5;

said classified category 5 corresponds with a predicted HbA_1c between about 9.5 and about 10.1;

said classified category 6 corresponds with a predicted HbA_1c between about 10.1 and about 11.0; and

said classified category 7 corresponds with a predicted HbA_1c above about 11.0.

6. The method of claim 1, further comprising:

defining predicted confidence intervals for corresponding said HbA_1c, each of said predicted confidence intervals representing a range of values for HbA_1c.

7. The method of claim 6, wherein said predicted HbA_1c confidence intervals have about a 95% confidence level.

8. A computerized method for evaluating hemoglobin A_1c (HbA_1c) of a patient based on blood glucose (BG) data collected over a predetermined duration, said method comprising:

computing on a computer weighted deviation of the BG of said patient toward high blood glucose (WR) from a predefined normal level;

computing on a computer mean blood glucose (Dr) based on said collected BG data;

estimating on a computer HbA_1c using a predetermined mathematical formula based on said computed WR and Dr; and

providing on a computer a predetermined confidence interval for classification of said estimated value of HbA_1c.

9. The method of claim 8, wherein:

said confidence interval is between about 85% to about 95%.

10. The method of claim 8, wherein:

said computed WR is mathematically defined from a series of BG readings x₁, x₂, . . . x_n taken at time points t₁, t₂, . . . , t_n as;

11. The method of claim 8, wherein said estimating HbA_1c from said BG monitoring data comprises determining Estimated HbA_1c according to:

Estimated HbA_1c=0.9008(WR)−

0.8207(DR)+6.7489.

12. The method of claim 8, further comprising:

defining predetermined categories for the estimate of HbA_1c, each of said HbA_1c estimate categories representing a range of values for estimated HbA_1c; and

assigning said estimated HbA_1c to at least one of said HbA_1c estimate categories.

13. The method of claim 12, wherein said HbA_1c estimate categories are defined as follows:

classified category 1, wherein said estimated HbA_1c is less than about 7.8;

classified category 2, wherein said estimated HbA_1c is between about 7.8 and about 8.5;

classified category 3, wherein said estimated HbA_1c is between about 8.5 and about 9.0;

classified category 4, wherein said estimated HbA_1c is between about 9.0 and about 9.6;

classified category 5, wherein said estimated HbA_1c is between about 9.6 and about 10.3;

classified category 6, wherein said estimated HbA_1c is between about 10.3 and about 11.0; and

classified category 7, wherein said estimated HbA_1c is above about 11.0.

14. The method of claim 13, further comprising:

defining predicted confidence intervals for corresponding said HbA_1c estimate categories, wherein said predicted confidence intervals are defined as follows;

said classified category 1 corresponds with a predicted HbA_1c less than about 8.0;

said classified category 2 corresponds with a predicted HbA_1c between about 8.0 and about 8.5;

said classified category 3 corresponds with a predicted HbA_1c between about 8.5 and about 9.0;

said classified category 4 corresponds with a predicted HbA_1c between about 9.0 and about 9.5;

said classified category 5 corresponds with a predicted HbA_1c between about 9.5 and about 10.1;

said classified category 6 corresponds with a predicted HbA_1c between about 10.1 and about 11.0; and

said classified category 7 corresponds with a predicted HbA_1c above about 11.0.

15. A system for evaluating hemoglobin A_1c (HbA_1c) of a patient based on blood glucose (BG) data collected over a predetermined duration, said system comprising:

a database component operative to maintain a database identifying said BG data;

a processor programmed to;

compute weighted deviation of the BG of said patient toward high blood glucose (WR) from a predefined normal level;

compute mean blood glucose (Dr) based on said collected BG data; and

estimate HbA_1c using a predetermined mathematical formula based on said computed WR and Dr; and

define predetermined categories for the estimate of HbA_1c, each of said HbA_1c estimate categories representing a range of values for estimated HbA_1c; and

assign said estimated HbA_1c to at least one of said HbA_1c estimate categories.

16. The system of claim 15, wherein:

said computed WR is mathematically defined from a series of BG readings x₁, x₂, . . . x_n taken at time points t₁, t₂, . . . t_n as;

17. The system of claim 15, wherein said estimating HbA_1c from said BG monitoring data comprises determining Estimated HbA_1c according to:

Estimated HbA_1c=0.9008(WR)−

0.8207(DR)+6.7489.

18. The system of claim 15, wherein said HbA_1c estimate categories are defined as follows:

classified category 1, wherein said estimated HbA_1c is less than about 7.8;

classified category 2, wherein said estimated HbA_1c is between about 7.8 and about 8.5;

classified category 3, wherein said estimated HbA_1c is between about 8.5 and about 9.0;

classified category 4, wherein said estimated HbA_1c is between about 9.0 and about 9.6;

classified category 5, wherein said estimated HbA_1c is between about 9.6 and about 10.3;

classified category 6, wherein said estimated HbA_1c is between about 10.3 and about 11.0; and

classified category 7, wherein said estimated HbA_1c is above about 11.0.

19. The system of claim 18, wherein said processor being further programmed to:

define predicted confidence intervals for corresponding said HbA_1c estimate categories, wherein said predicted confidence intervals are defined as follows;

said classified category 1 corresponds with a predicted HbA_1c less than about 8.0;

said classified category 2 corresponds with a predicted HbA_1c between about 8.0 and about 8.5;

said classified category 3 corresponds with a predicted HbA_1c between about 8.5 and about 9.0;

said classified category 4 corresponds with a predicted HbA_1c between about 9.0 and about 9.5;

said classified category 5 corresponds with a predicted HbA_1c between about 9.5 and about 10.1;

said classified category 6 corresponds with a predicted HbA_1c between about 10.1 and about 11.0; and

said classified category 7 corresponds with a predicted HbA_1c above about 11.0.

20. The system of claim 15, wherein said processor being further programmed to:

define predicted confidence intervals for corresponding said HbA_1c, each of said predicted confidence intervals representing a range of values for HbA_1c.

21. The system of claim 20, wherein said predicted HbA_1c confidence intervals have about a 95% confidence level.

22. A glycemic control system for evaluating hemoglobin A_1c (HbA_1c) of a patient, said system comprising:

a blood glucose (BG) acquisition mechanism, said acquisition mechanism configured to acquire BG data from the patient,

a database component operative to maintain a database identifying said BG data;

a processor programmed to;

compute weighted deviation of the BG of said patient toward high blood glucose (WR) from a predefined normal level;

compute mean blood glucose (Dr) based on said collected BG data; and

estimate HbA_1c using a predetermined mathematical formula based on said computed WR and Dr;

define predetermined categories for the estimate of HbA_1c, each of said HbA_1c estimate categories representing a range of values for estimated HbA_1c; and

assign said estimated HbA_1c to at least one of said HbA_1c estimate categories.

23. The system of claim 22, wherein:

said computed WR is mathematically defined from a series of BG readings x₁, x₂, . . . x_n taken at time points t₁, t₂, . . . t_n as;

24. The system of claim 22, wherein estimating HbA_1c from said BG monitoring data comprises determining Estimated HbA_1c according to:

Estimated HbA_1c=0.9008(WR)−

0.8207(DR)+6.7489.

25. The system of claim 22, wherein said HbA_1c estimate categories are defined as follows:

classified category 1, wherein said estimated HbA_1c is less than about 7.8;

classified category 2, wherein said estimated HbA_1c is between about 7.8 and about 8.5;

classified category 3, wherein said estimated HbA_1c is between about 8.5 and about 9.0;

classified category 4, wherein said estimated HbA_1c is between about 9.0 and about 9.6;

classified category 5, wherein said estimated HbA_1c is between about 9.6 and about 10.3;

classified category 6, wherein said estimated HbA_1c is between about 10.3 and about 11.0; and

classified category 7, wherein said estimated HbA_1c is above about 11.0.

26. The system of claim 25, wherein:

said processor programmed to;

define predicted confidence intervals for corresponding said HbA_1c estimate categories, wherein said predicted confidence intervals are defined as follows;

said classified category 1 corresponds with a predicted HbA_1c less than about 8.0;

said classified category 2 corresponds with a predicted HbA_1c between about 8.0 and about 8.5;

said classified category 3 corresponds with a predicted HbA_1c between about 8.5 and about 9.0;

said classified category 4 corresponds with a predicted HbA_1c between about 9.0 and about 9.5;

said classified category 5 corresponds with a predicted HbA_1c between about 9.5 and about 10.1;

said classified category 6 corresponds with a predicted HbA_1c between about 10.1 and about 11.0; and

said classified category 7 corresponds with a predicted HbA_1c above about 11.0.

27. The system of claim 22, wherein:

said processor programmed to;

define predicted confidence intervals for corresponding said HbA_1c, each of said predicted confidence intervals representing a range of values for HbA_1c.

28. The system of claim 27, wherein said predicted HbA_1c confidence intervals have about a 95% confidence level.

29. A computer program product comprising a computer useable medium having computer program logic for enabling at least one processor in a computer system to evaluate hemoglobin A_1c (HbA_1c) of a patient based on blood glucose (BG) data, said computer program logic comprising:

computing weighted deviation of the BG of said patient toward high blood glucose (WR) from a predefined normal level;

computing mean blood glucose (Dr) based on said collected BG data; and

estimating HbA_1c using a predetermined mathematical formula based on said computed WR and Dr; and

providing a predetermined confidence interval for classification of said estimated value of HbA_1c, wherein said confidence interval is a single value or a range of values.

30. A glycemic control system for evaluating hemoglobin A_1c (HbA_1c) of a patient, said system comprising:

a blood glucose (BG) acquisition mechanism, said acquisition mechanism configured to acquire BG data from the patient,

a database component operative to maintain a database identifying said BG data;

a processor programmed to;

compute weighted deviation of the BG of said patient toward high blood glucose (WR) from a predefined normal level and estimated rate of change of blood glucose (Dr) based on said collected BG data; and

estimate HbA_1c using a predetermined mathematical formula based on said computed WR and Dr, wherein;

said computed WR is mathematically defined from a series of BG readings x₁, x₂, . . . x_n taken at time points t₁, t₂, . . . t_n as;

31. A glycemic control system for evaluating hemoglobin A_1c (HbA_1c) of a patient, said system comprising:

a blood glucose (BG) acquisition mechanism, said acquisition mechanism configured to acquire BG data from the patient,

a database component operative to maintain a database identifying said BG data;

a processor programmed to;

compute weighted deviation of the BG of said patient toward high blood glucose (WR) from a predefined normal level and estimated rate of change of blood glucose (Dr) based on said collected BG data; and

estimate HbA_1c using a predetermined mathematical formula based on said computed WR and Dr, wherein

said estimating HbA_1c from said BG monitoring data comprises determining Estimated HbA_1c according to;

Estimated HbA_1c=0.9008(WR)−

0.8207(DR)+6.7489.

32. A glycemic control system for evaluating hemoglobin A_1c (HbA_1c) of a patient, said system comprising:

a blood glucose (BG) acquisition mechanism, said acquisition mechanism configured to acquire BG data from the patient,

a database component operative to maintain a database identifying said BG data;

a processor programmed to;

compute weighted deviation of the BG of said patient toward high blood glucose (WR) from a predefined normal level and estimated rate of change of blood glucose (Dr) based on said collected BG data;

estimate HbA_1c using a predetermined mathematical formula based on said computed WR and Dr;

define predetermined categories for the estimate of HbA_1c, each of said HbA_1c estimate categories representing a range of values for estimated HbA_1c; and

assign said estimated HbA_1c to at least one of said HbA_1c estimate categories.

33. The system of claim 32, wherein said HbA_1c estimate categories are defined as follows:

classified category 1, wherein said estimated HbA_1c is less than about 7.8;

classified category 2, wherein said estimated HbA_1c is between about 7.8 and about 8.5;

classified category 3, wherein said estimated HbA_1c is between about 8.5 and about 9.0;

classified category 4, wherein said estimated HbA_1c is between about 9.0 and about 9.6;

classified category 5, wherein said estimated HbA_1c is between about 9.6 and about 10.3;

classified category 6, wherein said estimated HbA_1c is between about 10.3 and about 11.0; and

classified category 7, wherein said estimated HbA_1c is above about 11.0.

34. The system of claim 33, wherein:

said processor programmed to;

define predicted confidence intervals for corresponding said HbA_1c estimate categories, wherein said predicted confidence intervals are defined as follows;

said classified category 1 corresponds with a predicted HbA_1c less than about 8.0;

said classified category 2 corresponds with a predicted HbA_1c between about 8.0 and about 8.5;

said classified category 3 corresponds with a predicted HbA_1c between about 8.5 and about 9.0;

said classified category 4 corresponds with a predicted HbA_1c between about 9.0 and about 9.5;

said classified category 5 corresponds with a predicted HbA_1c between about 9.5 and about 10.1;

said classified category 6 corresponds with a predicted HbA_1c between about 10.1 and about 11.0; and

said classified category 7 corresponds with a predicted HbA_1c above about 11.0.

35. The system of claim 32, wherein:

said processor programmed to;

define predicted confidence intervals for corresponding said HbA_1c, each of said predicted confidence intervals representing a range of values for HbA_1c.

36. The system of claim 35, wherein said predicted HbA_1c confidence intervals have about a 95% confidence level.