초록 ▼

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 glu

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 HbA1c 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.

대표청구항 ▼

We claim: 1. A computerized method for evaluating the HbA1c 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 col

We claim: 1. A computerized method for evaluating the HbA1c 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 HbA1c using a predetermined mathematical formula based on said computed WR and Dr. 2. The method of claim 1, wherein: said computed WR is mathematically defined from a series of BG readings x1, x2, . . . xn taken at time points t1, t2, . . . , tn as: 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 sk+1-sk, where: sk=10S(k+t1)2 for k=0, 1, . . . , tn-t1, S(tj)=f(xj), for j=1, . . . , n. 3. The method of claim 1, wherein said estimate of HbA1c from said BG monitoring data is mathematically defined as: Estimated HbA1c=0.9008(WR)-0.89207(Dr)+6.7489. 4. The method of claim 1, further comprising: defining predetermined categories for the estimate of HbA 1c, each of said HbA1c estimate categories representing a range of values for estimated HbA1c; and assigning said estimated HbA1c to at least one of said HbA1c estimate categories. 5. The method of claim 4, wherein said HbA1c estimate categories are defined as follows: classified category 1, wherein said estimated HbA1c is less than about 7.8; classified category 2, wherein said estimated HbA1c is between about 7.8 and about 8.5; classified category 3, wherein said estimated HbA1c is between about 8.5 and about 9.0; classified category 4, wherein said estimated HbA1c is between about 9.0 and about 9.6; classified category 5, wherein said estimated HbA1c is between about 9.6 and about 10.3; classified category 6, wherein said estimated HbA1c is between about 10.3 and about 11.0; and classified category 7, wherein said estimated HbA1c is above about 11.0. 6. The method of claim 5, further comprising: defining predicted confidence intervals for corresponding said HbA1c estimate categories, wherein said predicted confidence intervals are defined as follows: said classified category 1 corresponds with a predicted HbA1c less than about 8.0; said classified category 2 corresponds with a predicted HbA1c between about 8.0 and about 8.5; said classified category 3 corresponds with a predicted HbA1c between about 8.5 and about 9.0; said classified category 4 corresponds with a predicted HbA1c between about 9.0 and about 9.5; said classified category 5 corresponds with a predicted HbA1c between about 9.5 and about 10.1; said classified category 6 corresponds with a predicted HbA1c between about 10.1 and about 11.0; and said classified category 7 corresponds with a predicted HbA1c above about 11.0. 7. The method of claim 4, further comprising: defining predicted confidence intervals for corresponding said HbA1c, each of said predicted confidence intervals representing a range of values for HbA1c. 8. The method of claim 7, wherein said predicted HbA1c confidence intervals have about a 95% confidence level. 9. A computerized method for evaluating the HbA1c 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 HbA1c 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 HbA1c. 10. The method of claim 9, wherein: said confidence interval is between about 85% to about 95%. 11. A system for evaluating HbA1c 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 HbA1c using a predetermined mathematical formula based on said computed WR and Dr. 12. The system of claim 11, wherein: said computed WR is mathematically defined from a series of BG readings x1, x2, . . . xn taken at time points t1, t2, . . . , tn as: 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 sk+1-sk, where: sk=10S(k+t1)2 for k=0, 1, . . . , tn-t1, S(tj)=f(xj), for j=1, . . . , n. 13. The system of claim 11, wherein said the estimate of HbA1c from said BG monitoring data is mathematically defined as: Estimated HbA1c=0.9008(WR)-0.8207(Dr)+6.7489. 14. The system of claim 11, wherein said processor is further programmed to: define predetermined categories for the estimate of HbA 1c, each of said HbA1c estimate categories representing a range of values for estimated HbA1c; and assign said estimated HbA1c to at least one of said HbA1c estimate categories. 15. The system of claim 14, wherein said HbA1c estimate categories are defined as follows: classified category 1, wherein said estimated HbA1c is less than about 7.8; classified category 2, wherein said estimated HbA1c is between about 7.8 and about 8.5; classified category 3, wherein said estimated HbA1c is between about 8.5 and about 9.0; classified category 4, wherein said estimated HbA1c is between about 9.0 and about 9.6; classified category 5, wherein said estimated HbA1c is between about 9.6 and about 10.3; classified category 6, wherein said estimated HbA1c is between about 10.3 and about 11.0; and classified category 7, wherein said estimated HbA1c is above about 11.0. 16. The system of claim 15, wherein said processor is further programmed to: define predicted confidence intervals for corresponding said HbA1c estimate categories, wherein said predicted confidence intervals are defined as follows: said classified category 1 corresponds with a predicted HbA1c less than about 8.0; said classified category 2 corresponds with a predicted HbA1c between about 8.0 and about 8.5; said classified category 3 corresponds with a predicted HbA1c between about 8.5 and about 9.0; said classified category 4 corresponds with a predicted HbA1c between about 9.0 and about 9.5; said classified category 5 corresponds with a predicted HbA1c between about 9.5 and about 10.1; said classified category 6 corresponds with a predicted HbA1c between about 10.1 and about 11.0; and said classified category 7 corresponds with a predicted HbA1c above about 11.0. 17. The system of claim 14, wherein said processor is further programmed to: define predicted confidence intervals for corresponding said HbA1c, each of said predicted confidence intervals representing a range of values for HbA1c. 18. The system of claim 17, wherein said predicted HbA1c confidence intervals have about a 95% confidence level. 19. A glycemic control system for evaluating HbA1c 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 HbA1c using a predetermined mathematical formula based on said computed WR and Dr. 20. 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 HbA1c 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 HbA1c using a predetermined mathematical formula based on said computed WR and Dr. 21. 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 HbA1c, wherein said confidence interval is a single value or a range of values.