METHOD AND/OR SYSTEM FOR ESTIMATING GLYCATION OF HEMOGLOBIN

• US 20100168539A1
• Filed: 12/31/2008
• Published: 07/01/2010
• Est. Priority Date: 12/31/2008
• Status: Abandoned Application

• Current Assignee: Medtronic Minimed Incorporated (Medtronic Plc)
• Original Assignee: Medtronic Minimed Incorporated (Medtronic Plc)
• Inventors: Shepp, Lawrence, Zhang, Cun-Hui, Palerm, Cesar C.
• Application Number:
  US12/347,778
• Publication Number:
  US 20100168539A1
• Time in Patent Office: Days
• US Class Current: 600/365
• CPC Class Codes: G01N 33/723 Glycosylated haemoglobin
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

Disclosed are systems, methods and techniques to estimate an extent of glycation of hemoglobin in a patient. In one particular implementation, although claimed subject matter is not limited in this respect, an estimate of glycation of hemoglobin in a patient may be measured based, at least in part, on blood-glucose measurements obtained from the patient.

Claims

1. A method comprising:

estimating a probability distribution associated with a probability of a hemoglobin molecule being glycated at a particular age of said hemoglobin molecule in a patient; and

estimating hemoglobin A1c of said patient based, at least in part, on said probability distribution and blood-glucose measurements taken from said patient.

2. The method of claim 1, wherein said estimating said probability distribution further comprises estimating a rate at which hemoglobin is glycated in said patient.

3. The method of claim 2, wherein said estimating said rate at which hemoglobin is glycated in a patient comprises estimating said rate based, at least in part, on hemoglobin A1c measurements taken from blood drawn from said patient.

4. The method of claim 3, wherein said estimating said rate further comprises periodically updating said rate based, at least in part, on a least square error estimate from a plurality of hemoglobin A1c measurements.

5. The method of claim 2, wherein said estimating said rate further comprises associating one or more attributes of said patient with a look up table.

6. The method of claim 1, wherein said estimating said probability distribution comprises estimating said probability based, at least in part, on an exponential probability distribution.

7. The method of claim 1, wherein said blood-glucose measurements are obtained at periodic sample intervals.

8. The method of claim 1, wherein said blood-glucose measurements are obtained from a blood-glucose sensor implanted in said patient.

9. The method of claim 8, and further comprising displaying said estimate of said hemoglobin A1c on a display coupled to said blood-glucose sensor.

10. The method of claim 8, and further comprising:

storing said blood-glucose measurements obtained from said blood-glucose sensor in a memory; and

executing a computing platform to estimate said hemoglobin A1c based, at least in part, on said stored blood-glucose measurements.

11. An apparatus comprising:

means for estimating a probability distribution associated with a probability of a hemoglobin molecule being glycated at a particular age of said hemoglobin molecule in a patient; and

means for estimating hemoglobin A1c of said patient based, at least in part, on said probability distribution and blood-glucose measurements taken from said patient.

12. The apparatus of claim 11, wherein said means for estimating said probability distribution further comprises means for estimating a rate at which hemoglobin is glycated in said patient.

13. The apparatus of claim 12, wherein said means for estimating said rate at which hemoglobin is glycated in a patient comprises means for estimating said rate based, at least in part, on hemoglobin A1c measurements taken from blood drawn from said patient.

14. The apparatus of claim 13, wherein said means for estimating said rate further comprises means for updating said rate based, at least in part, on a least square error estimate from a plurality of hemoglobin A1c measurements.

15. The apparatus of claim 12, wherein said means for estimating said rate further comprises means for associating one or more attributes of said patient with a look up table.

16. The apparatus of claim 11, wherein said means for estimating said probability distribution comprises means for estimating said probability based, at least in part, on an exponential probability distribution.

17. The apparatus of claim 11, wherein said blood-glucose measurements are obtained at periodic sample intervals.

18. The apparatus of claim 11, wherein said blood-glucose measurements are obtained from a blood-glucose sensor implanted in said patient.

19. The apparatus of claim 18, and further comprising means for displaying said estimate of said hemoglobin A1c on a display coupled to said blood-glucose sensor.

20. An article comprising:

a storage medium, said storage medium comprising machine-readable instructions stored thereon which, if executed by a computing platform, are adapted to direct said computing platform to;

estimate a probability distribution associated with a probability of a hemoglobin molecule being glycated at a particular age of said hemoglobin molecule in a patient; and

estimate hemoglobin A1c of said patient based, at least in part, on said probability distribution and blood-glucose measurements taken from said patient.

21. The article of claim 20, wherein said instructions, if executed by said computing platform, are further adapted to direct said computing platform to estimate said probability distribution based, at least in part, on an estimated rate at which hemoglobin is glycated in said patient.

22. The article of claim 21, wherein said instructions, if executed by said computing platform, are further adapted to direct said computing platform to determine said estimated rate at which hemoglobin is glycated in a patient based, at least in part, on hemoglobin A1c measurements taken from blood drawn from said patient.

23. The article of claim 22, wherein said instructions, if executed by said computing platform, are further adapted to direct said computing platform to update said estimated rate based, at least in part, on a least square error estimate from a plurality of hemoglobin A1c measurements.

24. The article of claim 21, wherein said instructions, if executed by said computing platform, are further adapted to direct said computing platform to estimating said rate by associating one or more attributes of said patient with a look up table.

25. The article of claim 21, wherein said estimating said probability distribution comprises estimating said probability based, at least in part, on an exponential probability distribution.

26. The article of claim 20, wherein said blood-glucose measurements are obtained at periodic sample intervals.

27. The article of claim 20, wherein said blood-glucose measurements are obtained from a blood-glucose sensor implanted in said patient.

28. The article of claim 20, wherein said instructions, if executed by said computing platform, are further adapted to direct said computing platform to initiate display of said estimate of said hemoglobin A1c on a display coupled to said blood-glucose sensor.

29. An apparatus comprising:

a computing platform, said computing platform being adapted to;

estimate a probability distribution associated with a probability of a hemoglobin molecule being glycated at a particular age of said hemoglobin molecule in a patient; and

estimate hemoglobin A1c of said patient based, at least in part, on said probability distribution and blood-glucose measurements taken from said patient.

30. The apparatus of claim 29, and further comprising a blood-glucose sensor adapted to be implanted in said patient to obtain said blood-glucose measurements.

31. The apparatus of claim 30, and further comprising a display coupled to said blood-glucose sensor to display said estimated hemoglobin A1c.