Method and device for utilizing analyte levels to assist in the treatment of diabetes, insulin resistance and metabolic syndrome

• US 20040248204A1
• Filed: 04/01/2004
• Published: 12/09/2004
• Est. Priority Date: 04/01/2003
• Status: Abandoned Application

• Current Assignee: Abbott Diabetes Care Incorporated (Abbott Laboratories Incorporated)
• Original Assignee: Abbott Diabetes Care Incorporated (Abbott Laboratories Incorporated)
• Inventors: Moerman, Piet
• Application Number:
  US10/817,211
• Publication Number:
  US 20040248204A1
• Time in Patent Office: Days
• US Class Current: 435/7.1
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: G01N 21/8483 Investigating reagent band test-element handling not specific to a test method G01N33/4875; analytical elements specific to chemical analysis of biological material G01N33/52; autometer with reagent band G01N35/04
• CPC Class Codes: G01N 27/3271 Amperometric enzyme electrodes for analytes in body fluids, e.g. glucose in blood amperometry per se G01N27/49; aspects concerning the enzyme reagent C12Q1/001

Abstract

A health-monitoring device assesses the health of a user based on levels of two analytes in a biological fluid. A first analyte that is utilized to assess a user'"'"'s health is a fat metabolism analyte, such as ketones, free fatty acids and glycerol, which is indicative of fat metabolism. A first analyte that is utilized is a glucose metabolism analyte, such as glucose. The levels of the two analytes may be used to assess insulin sensitivity, to detect both recent hypoglycemia and the cause of high glucose levels, and/or to guide therapeutic intervention. The dual analyte model of the present invention may be used to identify individuals at risk for metabolic syndrome, insulin resistance and non-insulin dependent diabetes, and allows monitoring of the progression of those disease states, as well as progress made by therapeutic interventions.

Claims

1. A method of assessing a user'"'"'s health comprising the computer implemented steps of:

measuring an amount of a first analyte in a biological fluid sample reflecting body fat metabolism and an amount of a second analyte in the biological fluid sample reflecting glucose metabolism, and

assessing the health of the user based on the amount of the first analyte and the amount of the second analyte.

2. The method of claim 1, further comprising the step of formulating advice to the user based on the step of assessing.

3. The method of claim 2, further comprising the step of using the formulated advice to drive a closed loop system for insulin dosage.

4. The method of claim 1, further comprising calculating and providing a dose for a medication based on the step of assessing.

5. The method of claim 1, wherein the step of assessing the health comprises assessing a metabolic syndrome, and further comprising the step of calculating a therapeutic intervention for the metabolic syndrome.

6. The method of claim 1, wherein the step of assessing the health of the user comprises calculating an insulin sensitivity factor based on the amount of the first analyte and the amount of the second analyte in the biological fluid sample.

7. The method of claim 1, wherein the first analyte comprises at least one fat metabolism analyte.

8. The method of claims 1 wherein the sample comprises one of blood, a derivate of blood, interstitial fluid, urine, saliva and mixtures thereof.

9. The method of claim 1 wherein the step of assessing comprises predicting the likelihood of the user developing hypoglycemia or hyperglycemia.

10. The method of claim 1, wherein the step of assessing comprises utilizing a third parameter comprising one or more of:

body mass Index, gender, body composition, meal intake, insulin delivery, medication and weight to assess the health of the user.

11. The method of claim 2, wherein the advice takes the form of a glucose level prediction for a future period.

12. A health-monitoring device for running the computer implemented steps of claim 1.

14. The device of claim 12, further comprising a program for assessing a parameter indicative of the user'"'"'s health based on the amount of the first analyte and the amount of the second analyte in the sample.

19. The device of claim 12, where the test elements comprise one or more of a photometric, reflectometric, electrochemical and fluorescense based system for analyzing the biological fluid sample.

20. The device of claim 12 where a single test element is able measuring both an amount of a first analyte in the biological fluid sample reflecting body fat metabolism and an amount of a second analyte in the biological fluid sample reflecting glucose metabolism.

21. The device of claim 12, wherein the device automatically or continuously measures the second analyte.

22. The device of claim 12, wherein the device automatically or continuously measures the first analyte.

23. The device of claim 12, further comprising a memory element for tracking the evolution of a disease or therapeutic success.

25. The method of claim 22, further comprising the step of predicting the likelihood of a developing hypoglycemia or hyperglycemia.

26. The method of claim 22, wherein the step of calculating and tracking utilizes one or more additional parameters comprising one of:

body mass Index, gender, body composition, meal intake, insulin intake, medication and weight.

27. The method of claim 22, wherein the glucose level is determined by measuring an amount of glucose in a biological fluid sample.

28. The method of claim 22, wherein the glucose level is determined by assuming the glucose level to be a normal level.

13. A health-monitoring device for assessing a user'"'"'s health, comprising:

a sampling device for providing a biological fluid sample from the user; and

one or more test elements for measuring an amount of a first analyte in the biological fluid sample reflecting body fat metabolism and an amount of a second analyte in the biological fluid sample reflecting glucose metabolism.

15. The device of claim 13, wherein the parameter is an insulin sensitivity factor.

16. The device of claim 13, wherein the parameter is hypoglycemia.

17. The device of claim 13, wherein the program formulates a recommendation for therapeutic intervention.

18. The device of claim 16, wherein the therapeutic intervention comprises one of:

a dose of insulin, diabetic medication and dietary advice.

24. A method for monitoring the health of a user, comprising the steps of:

measuring a first analyte in a biological fluid sample reflecting body fat metabolism;

determining a glucose level in a biological fluid sample; and

calculating and tracking the evolution of an insulin resistance factor in the user based on the measured level of the first analyte and the glucose level.

29. A method of monitoring a health parameter in a user, comprising the computer implemented steps of:

measuring an amount of a fat metabolism analyte in a biological fluid sample reflecting body fat metabolism

measuring an amount of a glucose metabolism analyte in the biological fluid sample, and

correlating the amount of the fat metabolism analyte and the amount of the glucose metabolism analyte to the health parameter.