Abstract
A method, system, and computer program product related to the diagnosis of diabetes, and is directed to predicting the longterm risk of hyperglycemia, and the longterm and shortterm risks of severe hypoglycemia in diabetics, based on blood glucose readings collected by a selfmonitoring 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<SUB>1c </SUB>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

A computerized method for evaluating the HbA_{1c }of a patient based on blood glucose (BG) data collected over a predetermined duration, said method comprising:
computing weighted deviation toward high blood glucose (WR) and estimated rate of change of 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.

The method of claim 1, wherein:
said computed WR is mathematically defined from a series of BG readings x_{1}, x_{2}, . . . x_{n }taken at time points t_{1}, t_{2}, . . . , t_{n }as: WR=1n∑i=1nwr(xi;1)
where:
wr(BG;b)=10f(BG)^{b }if f(BG)>0 and 0 otherwise,
b=1, representing a weighting parameter, and
said computed Dr is mathematically defined as:
Dr=average of s_{k+1}−s_{k},
where:
s_{k}=10S(k+t_{1})^{2 }for k=0, 1, . . . , t_{n}−t_{1},
S(t_{j})=f(x_{j}), for j=1, . . . , n.

The method of claim 1, wherein said estimate of HbA_{1c }from said BG monitoring data is mathematically defined as:
Estimated HbA_{1c}=0.9008(WR)−0.89207(Dr)+6.7489.

The method of claim 1, 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.

The method of claim 4, 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.

The method of claim 5, 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.

The method of claim 4, 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}.
 The method of claim 7, wherein said predicted HbA_{1c }confidence intervals have about a 95% confidence level.

A computerized method for evaluating the HbA_{1c }of a patient based on blood glucose (BG) data collected over a predetermined duration, said method comprising:
computing weighted deviation toward high blood glucose (WR) and estimated rate of change of blood glucose (Dr) based on said collected BG data;
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}.

The method of claim 9, wherein:
said confidence interval is between about 85% to about 95%.

A system for evaluating 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 toward high blood glucose (WR) 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.

The system of claim 11, wherein:
said computed WR is mathematically defined from a series of BG readings x_{1}, x_{2}, . . . x_{n }taken at time points t_{1}, t_{2}, . . . , t_{n }as: WR=1n∑i=1nwr(xi;1)
where:
wr(BG;b)=10f(BG)^{b }if f(BG)>0 and 0 otherwise,
b=1, representing a weighting parameter, and
said computed Dr is mathematically defined as:
Dr=average of s_{k+1}−s_{k},
where:
s_{k}=10S(k+t_{1})^{2 }for k=0, 1, . . . , t_{n}−t_{1},
S(t_{j})=f(x_{j}), for j=1, . . . , n.

The system of claim 11, wherein said the estimate of HbA_{1c }from said BG monitoring data is mathematically defined as:
Estimated HbA_{1c}=0.9008(WR)−0.8207(Dr)+6.7489.

The system of claim 11, wherein said processor is further programmed to:
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.

The system of claim 14, 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.

The system of claim 15, wherein said processor is 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.

The system of claim 14, wherein said processor is 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}.
 The system of claim 17, wherein said predicted HbA_{1c }confidence intervals have about a 95% confidence level.

A glycemic control system for evaluating 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 toward high blood glucose (WR) 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.

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 HbA_{1c }of a patient based on blood glucose (BG) data, said computer program logic comprising:
computing weighted deviation toward high blood glucose (WR) and estimated rate of change of 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.

The computer program product of claim 20, wherein said computer program logic further comprises:
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.
Owners (US)

University Of Virginia Patent Foundation
(Feb 15 2006)
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University Of Virginia
(Jan 31 2006)
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Virginia University Of Patent Foundation
(Sep 18 2002)
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Applicants

Univ Virginia
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Inventors

Kovatchev Boris P
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Cox Daniel J
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CPC Classifications

G06F19/3418
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A61B5/0002
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A61B5/14532
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G16H10/40
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G16H10/60
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G16H50/50
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IPC Classifications
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 Publication: Apr 11, 2006

Application:
Sep 26, 2002
US 24022802 A

Priority:
Sep 26, 2002
US 24022802 A

Priority:
Mar 29, 2001
US 0109884 W

Priority:
Mar 29, 2000
US 19303700 P