Method of hypoglycemia risk determination

• US 10,872,696 B2
• Filed: 02/08/2017
• Issued: 12/22/2020
• Est. Priority Date: 02/11/2011
• Status: Active Grant

• Current Assignee: Abbott Diabetes Care Incorporated (Abbott Laboratories Incorporated)
• Original Assignee: Abbott Diabetes Care Incorporated (Abbott Laboratories Incorporated)
• Inventors: Bernstein, Daniel M., Doniger, Kenneth J., Dunn, Timothy C., Hayter, Gary A., Wolpert, Howard
• Primary Examiner(s): Vanni, G Steven
• Application Number:
  US15/427,586
• Publication Number:
  US 20170147769A1
• Time in Patent Office: 1,413 Days
• Field of Search: None
• CPC Class Codes: A61B 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/14546 for measuring analytes not otherwise provided for, e.g. ions, cytochromes
• CPC Class Codes: A61B 5/150358 Strips for collecting blood, e.g. absorbent optical reagent test strips G01N21/8483; chemical reagent test strips G01N33/4875, G01N33/52
• CPC Class Codes: A61B 5/151 Devices specially adapted for taking samples of capillary blood, e.g. by lancets , needles or blades
• CPC Class Codes: A61B 5/4839 combined with drug delivery
• CPC Class Codes: A61B 5/486 Bio-feedback A61B5/375 takes precedence
• CPC Class Codes: A61B 5/6898 Portable consumer electronic devices, e.g. music players, telephones, tablet computers
• 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: A61B 5/742 using visual displays A61B5/339 takes precedence
• CPC Class Codes: A61B 5/743 Displaying an image simultaneously with additional graphical information, e.g. symbols, charts, function plots
• CPC Class Codes: A61B 5/7475 User input or interface means, e.g. keyboard, pointing device, joystick
• CPC Class Codes: G16H 10/20 for electronic clinical trials or questionnaires
• CPC Class Codes: G16H 20/17 delivered via infusion or injection
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 40/67 for remote operation
• 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

Presented herein are one or more software applications to help a user manager their diabetes. Embodiments and descriptions of the various applications are provided below in conjunction with an analyte measurement device.

Claims

1. A computer-implemented method for hypoglycemia risk determination and treatment recommendation, the method comprising:

collecting, by one or more computing devices, a plurality of analyte concentration measurements generated by an in vivo analyte monitoring system, the in vivo analyte monitoring system comprising at least a portion of an analyte sensor in contact with a bodily fluid of a user;

executing, by one or more processors of the one or more computing devices, software configured to perform the following steps;

(a) determining a first median value for the plurality of analyte concentration measurements corresponding to a first time of day period;

(b) determining a first variability value for the plurality of analyte concentration measurements corresponding to the first time of day period;

(c) determining, with reference to a data space defined by a range of median analyte concentration values and a range of variability analyte concentration values where the data space comprises a plurality of zones, if a first zone of the plurality of zones includes the first median value and the first variability value, wherein the first zone is associated with a risk of hypoglycemia, and

(d) if it is determined that the first median value and the first variability value are included in the first zone, then outputting either a representation of the first zone or a treatment recommendation based on the first zone, wherein the treatment recommendation is related to a medication adjustment or food intake.

2. The method of claim 1, wherein the first zone is defined by a hypoglycemia risk boundary, wherein the first zone comprises a plurality of median values that are less than the hypoglycemia risk boundary.

3. The method of claim 2, wherein the hypoglycemia risk boundary is either a straight hypoglycemia risk line or a curved hypoglycemia risk line.

4. The method of claim 1, wherein the representation of the identified first zone is output in (d), wherein the representation indicates hypoglycemia risk.

5. The method of claim 1, wherein the treatment recommendation is output in (d).

6. The method of claim 2, wherein the first variability value is a variability of the analyte concentration measurements in a range from the first median value to a tenth percentile value less than the median value, wherein when the plurality of analyte measurement concentrations are sorted from a highest to a lowest value, the tenth percentile value is the value in which about ninety percent of the analyte measurement concentrations are above the tenth percentile value and about ten percent of the analyte measurement concentrations are below the tenth percentile value.

7. The method of claim 2, wherein the first variability value is a variability of the analyte concentration measurements in a range from the first median value to an amount less than the first median value when the analyte concentration measurements are sorted from a highest to a lowest value.

8. The method of claim 2, further comprising adjusting, with the software executed by the one or more processors, the hypoglycemia risk boundary prior to determining if the first zone, from the plurality of zones, includes the first median value and the first variability value.

9. The method of claim 1, wherein the analyte concentration measurements comprise glucose data.

10. The method of claim 1, wherein the software, when executed by the one or more processors of the one or more computing devices, is further configured to perform the following steps:

(e) determining a second median value for a plurality of analyte concentration measurements corresponding to a second time of day period and a second variability value for the plurality of analyte concentration measurements corresponding to the second time of day period;

(f) determining with reference to the data space, if a second zone from the plurality of zones includes the second median value and the second variability value, wherein the second zone is associated with a risk of hypoglycemia, and

(g) if it is determined that the second median value and the second variability value are included in the second zone, outputting a representation of the second zone.

11. The method of claim 10, further comprising:

displaying a first treatment recommendation to the user based on the first zone for the first median value and the first variability value; and

displaying a second treatment recommendation to the user based on the second zone for the second median value and the second variability value.

22. The method of claim 1, wherein the one or more computing devices comprise one or more cloud-based servers.

23. The method of claim 1, wherein the one or more computing devices comprise a smart phone.

24. The method of claim 1, wherein the representation of the first zone is output in (d).

12. A computer-implemented method for hypoglycemia risk determination and treatment recommendation, the method comprising:

collecting, by one or more computing devices, a plurality of analyte concentration measurements generated by an in vivo analyte monitoring system, the in vivo analyte monitoring system comprising at least a portion of an analyte sensor that is in contact with a bodily fluid of a user;

executing, by one or more processors of the one or more computing devices, software configured to perform the following steps;

(a) determining a first central tendency value for the plurality of analyte concentration measurements corresponding to a first time of day period;

(b) determining a first variability value for the plurality of analyte concentration measurements corresponding to the first time of day period;

(c) determining, with reference to a data space defined by a range of central tendency values and a range of variability values where the data space comprises a plurality of zones, if a first zone of the plurality of zones includes the first central tendency value and the first variability value, wherein the first zone is associated with a risk of hypoglycemia, and

(d) if it is determined that the first central tendency value and the first variability value are included in the first zone, outputting either a representation of the first zone or a treatment recommendation based on the first zone, wherein the treatment recommendation is related to a medication adjustment or food intake.

13. The method of claim 12, wherein the first zone is defined by a hypoglycemia risk boundary, wherein the first zone includes a plurality of central tendency values that are less than the hypoglycemia risk boundary.

14. The method of claim 12, wherein the representation indicates hypoglycemia risk.

15. The method of claim 13, further comprising displaying a treatment recommendation to the user based on the identified first zone.

16. The method of claim 13, wherein the first variability value is a variability of the analyte concentration values in a range from the first central tendency value to a tenth percentile value less than the first central tendency value, wherein when the plurality of analyte measurement concentrations are sorted from a highest to lowest central tendency value, the tenth percentile value is the value in which about ninety percent of the central tendency values are above the tenth percentile value and about ten percent of the central tendency values are below the tenth percentile value.

17. The method of claim 13, wherein the first variability value is a variability of the analyte concentration values in a range from the first central tendency value to an amount less than the first central tendency value when the central tendency values are sorted from a highest to a lowest value.

18. The method of claim 13, further comprising adjusting, with the software executed by the one or more processors, the hypoglycemia risk boundary prior to determining if the first one zone, from the plurality of zones, includes the first central tendency value and the first variability value.

19. The method of claim 12, wherein the analyte concentration measurements comprise glucose data.

20. The method of claim 12, wherein the software, when executed by the one or more processors of the one or more computing devices, is further configured to perform the following steps:

(e) determining a second a central tendency value for the plurality of analyte concentration measurements corresponding to a second time of day period and a second variability value for the plurality of analyte concentration measurements corresponding to the second time of day period;

(f) determining, with reference to the data space, if a second zone from the plurality of zones includes the second central tendency value and the second variability value, wherein the second zone is associated with a risk of hypoglycemia; and

(g) outputting a representation of the identified second zone if it is determined that the second central tendency value and the second variability value are included in the second zone.

21. The method of claim 20, further comprising:

displaying a first treatment recommendation to the user based on the first zone for the first central tendency value and the first variability value; and

displaying a second treatment recommendation to the user based on the second zone for the second central tendency value and the first variability value.

25. A system for hypoglycemia risk determination and treatment recommendation, the system comprising:

one or more in vivo analyte monitoring systems, each comprising at least a portion of an analyte sensor in contact with a bodily fluid of a user;

one or more computing devices configured to collect a plurality of analyte concentration measurements generated by the one or more in vivo analyte monitoring systems, wherein the one or more computing devices comprises one or more processors and memory coupled thereto, the memory storing software that, when executed by the one or more processors, cause the one or more processors to perform the following steps;

(a) determine a first median value for the plurality of analyte concentration measurements corresponding to a first time of day period;

(b) determine a first variability value for the plurality of analyte concentration measurements corresponding to the first time of day period;

(c) determine, with reference to a data space defined by a range of median analyte concentration values and a range of variability analyte concentration values where the data space comprises a plurality of zones, if a first zone of the plurality of zones includes the first median value and the first variability value, wherein the first zone is associated with a risk of hypoglycemia, and

(d) if it is determined that the first median value and the first variability value are included in the first zone, then output a treatment recommendation based on the first zone, wherein the treatment recommendation is related to a medication adjustment or food intake.

26. The system of claim 25, wherein the analyte concentration measurements comprise glucose data.

27. The system of claim 25, wherein the first zone is defined by a hypoglycemia risk boundary, wherein the first zone comprises a plurality of median values that are less than the hypoglycemia risk boundary.