Method, System and Computer Program Product for Evaluation of Blood Glucose Variability In Diabetes From Self-Monitoring Data

• US 20090171589A1
• Filed: 01/05/2007
• Published: 07/02/2009
• Est. Priority Date: 01/05/2006
• Status: Active Grant

• Current Assignee: University of Virginia Patent Foundation (University of Virginia)
• Original Assignee: University of Virginia Patent Foundation (University of Virginia)
• Inventors: Kovatchev, Boris P.
• Granted Patent: US 11,355,238 B2
• Time in Patent Office: Days
• US Class Current: 702/19
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment

Abstract

A system, computer program product, method and algorithm for evaluation of blood glucose variability—one of the most important parameters of diabetes management. An embodiment of the method may use routine self-monitoring blood glucose (SMBG) data collected over a period of 2-6 weeks, for example, based on a theory of risk analysis of blood glucose data. One aspect may include a method, system and computer program product for computing the Average Daily Risk Range (ADRR)—a measure of overall glucose variability. Another aspect may include a method, system, and computer program product for estimating separately the glucose variability in the hypoglycemic range via a Low BG Index (LBGI) and the glucose variability in the high BG range via High BG Index (HBGI) followed by a combination of the two indices into a single variability display.

Claims

1. A method for measuring blood glucose variability, said method comprising:

acquiring a plurality of blood glucose data points;

transforming the plurality of blood glucose data points according to a transforming function;

calculating at least one risk value for at least some of each of the transformed plurality of blood glucose data points;

calculating at least one risk range based on at least two of the calculated risk values within a period of time with a predetermined duration; and

calculating at least one composite risk range based on at least one of the calculated risk ranges.

2. The method of claim 1, wherein the calculation of said at least one composite risk range comprises computing an average risk range.

3. The method of claim 2, wherein the average risk range is computed as:

$A<br><br><br><br>D<br><br><br><br>R<br><br><br><br>R=\frac{1}{M}<br><br>\underset{i=1}{\overset{M}{\sum <br><br>}}<br><br>\left[{\mathrm{LR}}^i+{\mathrm{HR}}^i\right],$

where LRⁱ represents a maximal hypoglycemic risk value for period of time with a predetermined duration i, HRⁱ represents a maximal hyperglycemic risk value for period of time with predetermined duration i, LRⁱ+HRⁱ represents a calculated risk range for a period of time with predetermined duration i, and the plurality of blood glucose data points are collected on periods of time with predetermined duration i=1, 2, . . . , M.

4. The method of claim 1, wherein the calculation of said composite risk range comprises computing a standard deviation risk range.

5. The method of claim 4, wherein the standard deviation risk range is computed as:

$S<br><br><br><br>D<br><br><br><br>R<br><br><br><br>R^2=\frac{1}{M-1}<br><br>\underset{i=1}{\overset{M}{\sum <br><br>}}<br><br>{\left[\left({\mathrm{LR}}^i+{\mathrm{HR}}^i\right)-\mathrm{mean}\left({\mathrm{LR}}^i+{\mathrm{HR}}^i\right)\right]}^2,$

where LRⁱ represents a maximal hypoglycemic risk value for period of time with a predetermined duration i, HRⁱ represents a maximal hyperglycemic risk value for period of time with a predetermined duration i, LRⁱ+HRⁱ represents a calculated risk range for period of time with predetermined duration i, and the plurality of blood glucose data points are collected on periods of time with predetermined duration i=1, 2, . . . , M.

6. The method of claim 1, wherein the plurality of blood glucose data points includes at least three blood glucose data point readings per period of time with predetermined duration.

7. The method of claim 1, wherein the plurality of blood glucose data points includes blood glucose data points from about one to about two weeks of self-monitoring.

8. The method of claim 1, wherein the plurality of blood glucose data points includes blood glucose data points from about two to about six weeks of self-monitoring.

9. The method of claim 8, wherein the plurality of blood glucose data points includes blood glucose data points from about four weeks of self-monitoring.

10. The method of claim 1, wherein the plurality of blood glucose data points includes blood glucose data points from greater than about six weeks of self-monitoring.

11. The method of claim 1, wherein the plurality of blood glucose data points includes about thirty to about seventy-five blood glucose data points.

12. The method of claim 1, wherein the plurality of blood glucose data points includes about seventy-five blood glucose data points.

13. The method of claim 1, wherein the plurality of blood glucose data points includes greater than about seventy-five blood glucose data points.

14. The method of claim 1, further comprising displaying the calculated risk range.

15. The method of claim 14, wherein displaying the calculated risk range comprises providing a gauge having at least one indicator, wherein the at least one indicator displays the calculated composite risk range.

16. The method of claim 15, wherein the gauge is segmented into at least one category including “

Low Risk”

, “

Moderate Risk”

, and “

High Risk.”

17. The method of claim 16, wherein the “

Low Risk”

category corresponds to a composite risk range between about 0 and about 20, the “

Moderate Risk”

category corresponds to a composite risk range between about 20 and about 40, and the “

High Risk”

category corresponds to composite a risk range greater than about 40.

18. The method of claim 15, wherein the gauge is segmented into at least one category including “

Low Risk”

, “

Low-Moderate Risk”

, “

Moderate-High Risk”

, and “

High Risk.”

19. The method of claim 18, wherein the “

Low Risk”

category corresponds to a composite risk range between about 0 and about 20, the “

Low-Moderate Risk”

category corresponds to a composite risk range between about 20 and about 30, the “

Moderate-High Risk”

category corresponds to a composite risk range between about 30 and about 40, and the “

High Risk”

category corresponds to a composite risk range greater than about 40.

20. The method of claim 14, wherein said display of the calculated composite risk range comprises:

providing a high blood glucose indicator; and

providing a low blood glucose indicator.

21. The method of claim 1, further comprising storing and/or displaying the calculated composite risk range into a plurality of category levels.

22. The method of claim 1, further comprising displaying the calculated composite risk range on an analog and/or digital display.

23. The method of claim 1, wherein the period of time with predetermined duration is about daytime or about a nighttime in a daytime/nighttime cycle.

24. The method of claim 1, wherein the period of time with predetermined duration is greater than about a daytime or about a nighttime in a daytime/nighttime cycle but less than a twenty-four hour period.

25. The method of claim 1, wherein the period of time with predetermined duration is less than a twenty-four hour period.

26. The method of claim 1, wherein the period of time with predetermined duration is about a twenty-four hour period.

27. The method of claim 1, wherein the period of time with predetermined duration is greater than a twenty-four hour period but less than about a week.

28. The method of claim 1, wherein the period of time with predetermined duration is about a week.

29. The method of claim 1, wherein the period of time with predetermined duration is greater than a week.

30. A system for determining blood glucose variability, said system comprising:

an acquisition module acquiring a plurality of blood glucose data points; and

a processor programmed to;

transform the plurality of blood glucose data points from a blood glucose range to a transformed range according to a transforming function,

calculate at least one risk value for at least some of each of the transformed plurality of blood glucose data points,

calculate at least one risk range based on at least two of the calculated risk values within a period of time with a predetermined duration, and

calculate at least one composite risk range based on at least one of the calculated risk ranges.

31. The system of claim 30, wherein the calculation of said at least one composite risk range comprises computing an average risk range.

32. The system of claim 31, wherein the average risk range is computed as:

$A<br><br><br><br>D<br><br><br><br>R<br><br><br><br>R=\frac{1}{M}<br><br>\underset{i=1}{\overset{M}{\sum <br><br>}}<br><br>\left[{\mathrm{LR}}^i+{\mathrm{HR}}^i\right],$

where LRⁱ represents a maximal hypoglycemic risk value for period of time with a predetermined duration i, HRⁱ represents a maximal hyperglycemic risk value for period of time with a predetermined duration i, LRⁱ+HRⁱ represents a calculated risk range for period of time with predetermined duration i, and the plurality of blood glucose data points are collected on periods of time with predetermined duration i=1, 2, . . . , M.

33. The system of claim 30, wherein the calculation of said composite risk range comprises computing a standard deviation risk range.

34. The system of claim 33, wherein the standard deviation risk range is computed as:

$S<br><br><br><br>D<br><br><br><br>R<br><br><br><br>R^2=\frac{1}{M-1}<br><br>\underset{i=1}{\overset{M}{\sum <br><br>}}<br><br>{\left[\left({\mathrm{LR}}^i+{\mathrm{HR}}^i\right)-\mathrm{mean}\left({\mathrm{LR}}^i+{\mathrm{HR}}^i\right)\right]}^2,$

where LRⁱ represents a maximal hypoglycemic risk value for period of time with a predetermined duration i, HRⁱ represents a maximal hyperglycemic risk value for period of time with a predetermined duration i, LRⁱ+HRⁱ represents a calculated daily risk range for period of time with predetermined duration i, and the plurality of blood glucose data points are collected on periods of time with predetermined duration i=1, 2, . . . , M.

35. The system of claim 30, wherein the plurality of blood glucose data points includes at least three blood glucose data point readings per period of time with predetermined duration.

36. The system of claim 30, wherein the plurality of blood glucose data points includes blood glucose data points from about one to about two weeks of self-monitoring.

37. The system of claim 30, wherein the plurality of blood glucose data points includes blood glucose data points from about two to about six weeks of self-monitoring.

38. The system of claim 37, wherein the plurality of blood glucose data points includes blood glucose data points from about four weeks of self-monitoring.

39. The system of claim 30, wherein the plurality of blood glucose data points includes blood glucose data points from greater than about six weeks of self-monitoring.

40. The system of claim 30, wherein the plurality of blood glucose data points includes about thirty to about seventy-five blood glucose data points.

41. The system of claim 30, wherein the plurality of blood glucose data points includes about seventy-five blood glucose data points.

42. The system of claim 30, wherein the plurality of blood glucose data points includes greater than about seventy-five blood glucose data points.

43. The system of claim 30, further comprising a display module, said display module displaying the calculated composite risk range.

44. The system of claim 43, wherein the display module comprises a gauge, said gauge having at least one indicator, wherein the at least one indicator displays the calculated composite risk range.

45. The system of claim 44, wherein the gauge is segmented into at least one category including “

Low Risk”

, “

Moderate Risk”

, and “

High Risk.”

46. The system of claim 45, wherein the “

Low Risk”

category corresponds to a composite risk range between about 0 and about 20, the “

Moderate Risk”

category corresponds to a composite risk range between about 20 and about 40, and the “

High Risk”

category corresponds composite to a risk range greater than about 40.

47. The system of claim 44, wherein the gauge is segmented into at least one category including “

Low Risk”

, “

Low-Moderate Risk”

, “

Moderate-High Risk”

, and “

High Risk.”

48. The system of claim 47, wherein the “

Low Risk”

category corresponds to a composite risk range between about 0 and about 20, the “

Low-Moderate Risk”

category corresponds to a composite risk range between about 20 and about 30, the “

Moderate-High Risk”

category corresponds to a composite risk range between about 30 and about 40, and the “

High Risk”

category corresponds to a composite risk range greater than about 40.

49. The system of claim 43, wherein said display module comprises:

a high blood glucose indicator; and

a low blood glucose indicator.

50. The system of claim 30, further comprising a storage module, said storage module storing the calculated composite risk range into a plurality of category levels.

51. The system of claim 30, further comprising a display module, said display module displaying the calculated composite risk range into a plurality of category levels.

52. The system of claim 30, further comprising:

a storage module, said storage module storing the calculated composite risk range into a plurality of category levels; and

a display module, said display module displaying the calculated composite risk range into a plurality of category levels.

53. The system of claim 30, further comprising a display module, said display module displaying the calculated composite risk range on an analog and/or digital display.

54. The system of claim 30, wherein the period of time with predetermined duration is about daytime or about nighttime in a daytime/nighttime cycle.

55. The system of claim 30, wherein the period of time with predetermined duration is greater than about daytime or about a nighttime in a daytime/nighttime cycle but less than a twenty-four hour period.

56. The system of claim 30, wherein the period of time with predetermined duration is less than a twenty-four hour period.

57. The system of claim 30, wherein the period of time with predetermined duration is about a twenty-four hour period.

58. The system of claim 30, wherein the period of time with predetermined duration is greater than a twenty-four hour period but less than about a week.

59. The system of claim 30, wherein the period of time with predetermined duration is about a week.

60. The system of claim 30, wherein the period of time with predetermined duration is greater than a week.

61. A computer program product comprising a computer useable medium having computer program logic for enabling at least one processor in a computer system to measure blood glucose variability, said computer program logic comprising:

acquiring a plurality of blood glucose data points;

transforming the plurality of blood glucose data points from a blood glucose range to a transformed range according to a transforming function;

calculating at least one risk value for at least some of each of the transformed plurality of blood glucose data points;

calculating at least one risk range based on at least two of the calculated risk values within a period of time with a predetermined duration; and

calculating at least composite one risk range based on at least one of the calculated risk ranges.

62. The computer program product of claim 61, wherein the calculation of said at least one composite risk range comprises computing an average risk range.

63. The computer program product of claim 62, wherein the average risk range is computed as:

$A<br><br><br><br>D<br><br><br><br>R<br><br><br><br>R=\frac{1}{M}<br><br>\underset{i=1}{\overset{M}{\sum <br><br>}}<br><br>\left[{\mathrm{LR}}^i+{\mathrm{HR}}^i\right],$

where LRⁱ represents a maximal hypoglycemic risk value for period of time with predetermined duration i, HRⁱ represents a maximal hyperglycemic risk value for period of time with predetermined duration i, LRⁱ+HRⁱ represents a calculated daily risk range for period of time with predetermined duration i, and the plurality of blood glucose data points are collected on periods of time with predetermined duration i=1, 2, . . . , M.

64. The computer program product of claim 61, wherein the calculation of said composite risk range comprises computing a standard deviation risk range.

65. The computer program product of claim 64, wherein the standard deviation risk range is computed as:

$S<br><br><br><br>D<br><br><br><br>R<br><br><br><br>R^2=\frac{1}{M-1}<br><br>\underset{i=1}{\overset{M}{\sum <br><br>}}<br><br>{\left[\left({\mathrm{LR}}^i+{\mathrm{HR}}^i\right)-\mathrm{mean}\left({\mathrm{LR}}^i+{\mathrm{HR}}^i\right)\right]}^2,$

where LRⁱ represents a maximal hypoglycemic risk value for period of time with predetermined duration i, HRⁱ represents a maximal hyperglycemic risk value for period of time with predetermined duration i, LRⁱ+HRⁱ represents a calculated risk range for period of time with predetermined duration i, and the plurality of blood glucose data points are collected on period of time with predetermined duration i=1, 2, . . . , M.

70. The computer program product of claim 61, wherein the plurality of blood glucose data points includes blood glucose data points from greater than about six weeks of self-monitoring.

71. The computer program product of claim 61, wherein the plurality of blood glucose data points includes about thirty to about seventy-five blood glucose data points.

72. The computer program product of claim 61, wherein the plurality of blood glucose data points includes about seventy-five blood glucose data points.

73. The computer program product of claim 61, wherein the plurality of blood glucose data points includes greater than about seventy-five blood glucose data points.

74. The computer program product of claim 61, said computer program logic further comprising displaying the calculated composite risk range.

75. The computer program product of claim 74, wherein displaying the calculated composite risk range comprises providing a gauge having at least one indicator, wherein the at least one indicator displays the calculated composite risk range.

76. The computer program product of claim 75, wherein the gauge is segmented into at least one category including “

Low Risk”

, “

Moderate Risk”

, and “

High Risk.”

77. The computer program product of claim 76, wherein the “

Low Risk”

category corresponds to a composite risk range between 0 and 20, the “

Moderate Risk”

category corresponds to a composite risk range between 20 and 40, and the “

High Risk”

category corresponds to a composite risk range greater than 40.

78. The computer program product of claim 75, wherein the gauge is segmented into at least one category including “

Low Risk”

, “

Low-Moderate Risk”

, “

Moderate-High Risk”

, and “

High Risk.”

79. The computer program product of claim 78, wherein the “

Low Risk”

category corresponds to a composite risk range between about 0 and about 20, the “

Low-Moderate Risk”

category corresponds to a composite risk range between about 20 and about 30, the “

Moderate-High Risk”

category corresponds to a composite risk range between about 30 and about 40, and the “

High Risk”

category corresponds to a composite risk range greater than about 40.

80. The method of claim 74, wherein said display of the calculated composite risk range comprises:

providing a high blood glucose indicator; and

providing a low blood glucose indicator.

81. The computer program product of claim 61, said computer program logic further comprising storing and/or displaying the calculated composite risk range into a plurality of category levels.

82. The computer program product of claim 61, said computer program logic further comprising displaying the calculated composite risk range on an analog and/or digital display.

83. The computer program product of claim 61, wherein the period of time with predetermined duration is about daytime or about nighttime in a daytime/nighttime cycle.

84. The computer program product of claim 61, wherein the period of time with predetermined duration is greater than about daytime or about a nighttime in a daytime/nighttime cycle but less than a twenty-four hour period.

85. The computer program product of claim 61, wherein the period of time with predetermined duration is less than a twenty-four hour period.

86. The computer program product of claim 61, wherein the period of time with predetermined duration is about a twenty-four hour period.

87. The computer program product of claim 61, wherein the period of time with predetermined duration is greater than a twenty-four hour period but less than about a week.

88. The computer program product of claim 61, wherein the period of time with predetermined duration is about a week.

89. The computer program product of claim 61, wherein the period of time with predetermined duration is greater than a week.

66. The computer program product of claim 66, wherein the plurality of blood glucose data points includes at least three blood glucose data point readings per period of time with predetermined duration.

67. The computer program product of claim 66, wherein the plurality of blood glucose data points includes blood glucose data points from about one to about two weeks of self-monitoring.

68. The computer program product of claim 66, wherein the plurality of blood glucose data points includes blood glucose data points from about two to about six weeks of self-monitoring.

69. The computer program product of claim 68, wherein the plurality of blood glucose data points includes blood glucose data points from about four weeks of self-monitoring.

90. A method for measuring blood glucose variability, said method comprising:

acquiring a plurality of self-monitored blood glucose data points, wherein the plurality of self-monitored blood glucose data points span a period of at least one day;

transforming the plurality of self-monitored blood glucose data points according to a transforming function, wherein the transforming function is;

f(BG,α

,β

,γ

)=γ

·

[(ln(BG))^α

−

β

],

where BG is a blood glucose value, (α

, β

, γ

)=(1.026, 1.861, 1.794) if BG is measured in mM, and (α

, β

, γ

)=(1.084, 5.381, 1.509) if BG is measured in mg/dl;

defining a BG risk space, wherein the BG risk space is;

r(BG)=10·

f(BG)²;

defining a left branch of the BG risk space representing a risk of hypoglycemia as;

rl(BG)=r(BG) if f(BG)<

0 and 0 otherwise;

defining a right branch of the BG risk space representing a risk of hyperglycemia as;

rh(BG)=r(BG) if f(BG)>

0 and 0 otherwise;

calculating a maximal hypoglycemic risk value for the plurality of self-monitored blood glucose data points for each day as;

LRⁱ=max(rl(x₁ⁱ),rl(x₂ⁱ), . . . , rl(x_niⁱ)),

where n_i is the number of readings for each day i and x₁ⁱ, x₂ⁱ, . . . , x_niⁱ are the n_i self-monitored blood glucose data points for each day i;

calculating a maximal hyperglycemic risk value for the plurality of self-monitored blood glucose data points for each day as;

HRⁱ=max(rh(x₁ⁱ),rh(x₂ⁱ), . . . , rh(x_niⁱ))

where n_i is the number of readings for each day i and x₁ⁱ, x₂ⁱ, . . . , x_niⁱ are the n_i self-monitored blood glucose data points for each day i;

calculating an average daily risk range as;

$A<br><br><br><br>D<br><br><br><br>R<br><br><br><br>R=\frac{1}{M}<br><br>\underset{i=1}{\overset{M}{\sum <br><br>}}<br><br>\left[{\mathrm{LR}}^i+{\mathrm{HR}}^i\right],$

where the plurality of self-monitored blood glucose data points are collected on days i=1, 2, . . . , M;

classifying the average daily risk range into one of at least four categories, wherein said at least four categories includes “

Low”

, “

Low-Moderate”

, “

Moderate-High”

, and “

High, wherein the “

Low Risk”

category corresponds to a risk range between about 0 and about 20, the “

Low-Moderate Risk”

category corresponds to a risk range between about 20 and about 30, the “

Moderate-High Risk”

category corresponds to a risk range between about 30 and about 40, and the “

High Risk”

category corresponds to a risk range greater than about 40; and

displaying the average daily risk range and the one of the at least four categories into which the average daily risk range is classified.

91. A system for measuring blood glucose variability, said system comprising:

an acquisition module acquiring a plurality of self-monitored blood glucose data points, wherein the plurality of self-monitored blood glucose data points span a period of at least one day;

a processor programmed to;

transform the plurality of self-monitored blood glucose data points from a blood glucose range to a transformed range according to a transforming function, wherein the minimal and maximal values of the transformed range are −

√

10 and ·

10, respectively, wherein the transforming function is;

f(BG,α

,β

,γ

)=γ

·

[(ln(BG))^α

−

β

],

where BG is a blood glucose value, (α

, β

, γ

)=(1.026, 1.861, 1.794) if BG is measured in mM, and (α

, β

, γ

)=(1.084, 5.381, 1.509) if BG is measured in mg/dl;

define a BG risk space, wherein the BG risk space is;

r(BG)=10·

f(BG)²;

define a left branch of the BG risk space representing a risk of hypoglycemia as;

rl(BG)=r(BG) if f(BG)<

0 and 0 otherwise;

define a right branch of the BG risk space representing a risk of hyperglycemia as;

rh(BG)=r(BG) if f(BG)>

0 and 0 otherwise;

calculate a maximal hypoglycemic risk value for the plurality of self-monitored blood glucose data points for each day as;

LRⁱ=max(rl(x₁ⁱ),rl(x₂ⁱ), . . . , rl(x_niⁱ)),

where n_i is the number of readings for each day i and x₁ⁱ, x₂ⁱ, . . . , x_niⁱ are the n_i self-monitored blood glucose data points for each day i;

calculate a maximal hyperglycemic risk value for the plurality of self-monitored blood glucose data points for each day as;

HRⁱ=max(rh(x₁ⁱ),rh(x₂ⁱ), . . . , rh(x_niⁱ))

where n_i is the number of readings for each day i and x₁ⁱ, x₂ⁱ, . . . , x_niⁱ are the n_i self-monitored blood glucose data points for each day i; and

calculate an average daily risk range as;

$A<br><br><br><br>D<br><br><br><br>R<br><br><br><br>R=\frac{1}{M}<br><br>\underset{i=1}{\overset{M}{\sum <br><br>}}<br><br>\left[{\mathrm{LR}}^i+{\mathrm{HR}}^i\right],$

where the plurality of self-monitored blood glucose data points are collected on days i=1, 2, . . . , M;

classifying the average daily risk range into one of at least four categories, wherein said at least four categories includes “

Low”

, “

Low-Moderate”

, “

Moderate-High”

, and “

High, wherein the “

Low Risk”

category corresponds to a risk range between about 0 and about 20, the “

Low-Moderate Risk”

category corresponds to a risk range between about 20 and about 30, the “

Moderate-High Risk”

category corresponds to a risk range between about 30 and about 40, and the “

High Risk”

category corresponds to a risk range greater than about 40; and

a display module displaying the average daily risk range and the one of the at least four categories into which the average daily risk range is classified.

92. A computer program product comprising a computer useable medium having computer program logic for enabling at least one processor in a computer system to measure blood glucose variability, said computer program logic comprising:

acquiring a plurality of self-monitored blood glucose data points, wherein the plurality of self-monitored blood glucose data points span a period of at least one day;

transforming the plurality of self-monitored blood glucose data points from a blood glucose range to a transformed range according to a transforming function, wherein the minimal and maximal values of the transformed range are −

√

10 and √

10, respectively, wherein the transforming function is;

f(BG,α

,β

,γ

)=γ

·

[(ln(BG))^α

−

β

],

where BG is a blood glucose value, (α

, β

, γ

)=(1.026, 1.861, 1.794) if BG is measured in mM, and (α

, β

, γ

)=(1.084, 5.381, 1.509) if BG is measured in mg/dl;

defining a BG risk space, wherein the BG risk space is;

r(BG)=10·

f(BG)²;

defining a left branch of the BG risk space representing a risk of hypoglycemia as;

rl(BG)=r(BG) if f(BG)<

0 and 0 otherwise;

defining a right branch of the BG risk space representing a risk of hyperglycemia as;

rh(BG)=r(BG) if f(BG)>

0 and 0 otherwise;

calculating a maximal hypoglycemic risk value for the plurality of self-monitored blood glucose data points for each day as;

LRⁱ=max(rl(x₁ⁱ),rl(x₂ⁱ), . . . , rl(x_niⁱ))

where n_i is the number of readings for each day i and x₁ⁱ, x₂ⁱ, . . . , x_niⁱ are the n_i self-monitored blood glucose data points for each day i;

calculating a maximal hyperglycemic risk value for the plurality of self-monitored blood glucose data points for each day as;

HRⁱ=max(rh(x₁ⁱ),rh(x₂ⁱ), . . . , rh(x_niⁱ)),

where n_i is the number of readings for each day i and x₁ⁱ, x₂ⁱ, . . . , x_niⁱ are the n_i self-monitored blood glucose data points for each day i;

calculating an average daily risk range as;

$A<br><br><br><br>D<br><br><br><br>R<br><br><br><br>R=\frac{1}{M}<br><br>\underset{i=1}{\overset{M}{\sum <br><br>}}<br><br>\left[{\mathrm{LR}}^i+{\mathrm{HR}}^i\right],$

where the plurality of self-monitored blood glucose data points are collected on days i=1, 2, . . . M;

classifying the average daily risk range into one of at least four categories, wherein said at least four categories includes “

Low”

, “

Low-Moderate”

, “

Moderate-High”

, and “

High, wherein the “

Low Risk”

category corresponds to a risk range between about 0 and about 20, the “

Low-Moderate Risk”

category corresponds to a risk range between about 20 and about 30, the “

Moderate-High Risk”

category corresponds to a risk range between about 30 and about 40, and the “

High Risk”

category corresponds to a risk range greater than about 40; and

displaying the average daily risk range and the one of the at least four categories into which the average daily risk range is classified.

93. A method for measuring blood glucose variability, said method comprising:

acquiring a plurality of blood glucose data points;

calculating at least one risk range based on at least two of the plurality of blood glucose data points within a period of time with a predetermined duration; and

calculating at least one average predetermined duration blood glucose risk range based on at least one of the calculated risk ranges.

94. The method of claim 93, wherein predetermined duration is a day whereby said at least one average predetermined duration blood glucose risk range provides an average daily blood glucose risk range.

95. The method of claim 94, wherein the average daily blood glucose risk range is calculated as:

$B<br><br><br><br>G<br><br><br><br>\mathrm{RANGE}=\frac{1}{M}<br><br>\underset{i=1}{\overset{M}{\sum <br><br>}}<br><br>\left[\underset{j=1,n_i}{\max }<br><br>\left(x_j^i\right)-\underset{j=1,n_i}{\min }<br><br>\left(x_j^i\right)\right]$

where n_i is the number of readings for each day i, x_jⁱ is the jth blood glucose data point for

$\mathrm{day}<br><br><br><br>i,\underset{j=1,n_i}{\max }<br><br>\left(x_j^i\right)-\underset{j=1,n_i}{\min }<br><br>\left(x_j^i\right)$

represents a calculated daily risk range for day i, and the plurality of blood glucose data points are collected on days i=1, 2, . . . , M.

96. A system for measuring blood glucose variability, said system comprising:

an acquisition module acquiring a plurality of blood glucose data points; and

a processor programmed to;

calculate at least one risk range based on at least two of the plurality of blood glucose data points within a period of time with a predetermined duration, and

calculate at least one average predetermined duration blood glucose risk range based on at least one of the calculated risk ranges.

97. The method of claim 96, wherein predetermined duration is a day whereby said at least one average predetermined duration blood glucose risk range provides an average daily blood glucose risk range.

98. The system of claim 97, wherein the average daily blood glucose risk range is calculated as:

$B<br><br><br><br>G<br><br><br><br>\mathrm{RANGE}=\frac{1}{M}<br><br>\underset{i=1}{\overset{M}{\sum <br><br>}}<br><br>\left[\underset{j=1,n_i}{\max }<br><br>\left(x_j^i\right)-\underset{j=1,n_i}{\min }<br><br>\left(x_j^i\right)\right]$

where n_i is the number of readings for each day i, x_jⁱ is the jth blood glucose data point for

$\mathrm{day}<br><br><br><br>i,\underset{j=1,n_i}{\max }<br><br>\left(x_j^i\right)-\underset{j=1,n_i}{\min }<br><br>\left(x_j^i\right)$

represents a calculated daily risk range for day i, and the plurality of blood glucose data points are collected on days i=1, 2, . . . , M.

99. A computer program product comprising a computer useable medium having computer program logic for enabling at least one processor in a computer system to measure blood glucose variability, said computer program logic comprising:

acquiring a plurality of blood glucose data points;

calculating at least one risk range based on at least two of the plurality of blood glucose data points; and

calculating at least one average daily blood glucose risk range based on at least one of the calculated daily risk ranges.

100. The computer program product of claim 99, wherein predetermined duration is a day whereby said at least one average predetermined duration blood glucose risk range provides an average daily blood glucose risk range.

101. The computer program product of claim 100, wherein the average daily blood glucose risk range is calculated as:

$B<br><br><br><br>G<br><br><br><br>\mathrm{RANGE}=\frac{1}{M}<br><br>\underset{i=1}{\overset{M}{\sum <br><br>}}<br><br>\left[\underset{j=1,n_i}{\max }<br><br>\left(x_j^i\right)-\underset{j=1,n_i}{\min }<br><br>\left(x_j^i\right)\right]$

where n_i is the number of readings for each day i, x_jⁱ is the jth blood glucose data point for

$\mathrm{day}<br><br><br><br>i,\underset{j=1,n_i}{\max }<br><br>\left(x_j^i\right)-\underset{j=1,n_i}{\min }<br><br>\left(x_j^i\right)$

represents a calculated daily risk range for day i, and the plurality of blood glucose data points are collected on days i=1, 2, . . . , M.