SYSTEM AND METHOD FOR ASSESSING RISK ASSOCIATED WITH A GLUCOSE STATE

• US 20140100435A1
• Filed: 10/04/2012
• Published: 04/10/2014
• Est. Priority Date: 10/04/2012
• Status: Active Grant

• Current Assignee: Roche Diabetes Care Inc. (Roche Holding AG)
• Original Assignee: Roche Diagnostics Operations Incorporated (Roche Holding AG)
• Inventors: Duke, David L., Soni, Abhishek S.
• Granted Patent: US 10,463,282 B2
• Time in Patent Office: Days
• US Class Current: 600/365
• 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: 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

A system and method is provided for analyzing a glucose state. A method may include identifying a target glucose state and an initial glucose state. The method may include calculating a target return path for a transition from the initial glucose state to the target glucose state. The target return path may comprise at least one intermediate glucose state associated with the transition from the initial glucose state to the target glucose state. The target return path may be calculated based on a hazard associated with the at least one intermediate glucose state of the target return path.

Claims

1. A method of analyzing a glucose state, the method comprising:

identifying, by at least one computing device, a target glucose state including a target glucose level and a target rate of change of the target glucose level;

identifying, by the at least one computing device, an initial glucose state including an initial glucose level and an initial rate of change of the initial glucose level, the initial glucose state being different from the target glucose state;

calculating, by hazard analysis logic of the at least one computing device, a target return path for a transition from the initial glucose state to the target glucose state, the target return path comprising at least one intermediate glucose state associated with the transition from the initial glucose state to the target glucose state, the target return path being calculated by the hazard analysis logic based on a hazard associated with the at least one intermediate glucose state of the target return path.

2. The method of claim 1, wherein the calculating comprises:

identifying a plurality of potential intermediate glucose states between the initial glucose state and the target glucose state, and

selecting the at least one intermediate glucose state from the plurality of potential intermediate glucose states for the target return path to minimize the hazard associated with the target return path.

3. The method of claim 2, wherein the at least one intermediate glucose state of the target return path comprises a plurality of intermediate glucose states each having an associated penalty value, the plurality of intermediate glucose states are selected from the plurality of potential intermediate glucose states to minimize a sum of the penalty values associated with the target return path, and each penalty value includes a measure of a hazard associated with the corresponding intermediate glucose state.

4. The method of claim 1, wherein the target return path is calculated by the at least one computing device further based on a physiological limit of a glucose perturbation.

5. The method of claim 4, wherein the physiological limit comprises a predetermined maximum acceleration of a glucose level.

6. The method of claim 4, wherein the calculating comprises:

identifying a plurality of potential glucose states based on the target glucose state, the physiological limit of the glucose perturbation, and a predetermined period for a transition from each of the potential glucose states to the target glucose state, and

selecting an intermediate glucose state from the plurality of potential glucose states for the target return path to minimize the hazard associated with the target return path.

7. The method of claim 1, further comprising:

calculating, by the hazard analysis logic, a target return path for each of a plurality of initial glucose states, each target return path comprising a plurality of intermediate glucose states associated with a transition from the initial glucose state to the target glucose state, each target return path being calculated by the at least one computing device based on a minimization of a hazard associated with the plurality of intermediate glucose states of the target return path; and

generating, by the hazard analysis logic, a lookup table that maps each of the plurality of initial glucose states to the corresponding target return path, and

storing the lookup table in memory accessible by the at least one computing device.

8. The method of claim 7, further comprising:

detecting a glucose state of a person with diabetes based on at least one measured glucose value provided with a glucose sensor;

accessing, by the hazard analysis logic, the lookup table to identify an initial glucose state of the plurality of initial glucose states that is substantially the same as the detected glucose state of the person; and

identifying a penalty value in the lookup table associated with the identified initial glucose state, the penalty value representing a hazard associated with the identified initial glucose state based on the corresponding target return path of the identified initial glucose state.

9. The method of claim 8, wherein the detected glucose state includes a glucose level, a rate of change of the glucose level, and an uncertainty of at least one of the glucose level and the rate of change, the method further comprising calculating a risk associated with the detected glucose state based on the penalty value and the uncertainty.

10. The method of claim 8, further comprising providing the penalty value for display on a display.

11. The method of claim 1, wherein the target glucose state is an optimal glucose state having a penalty value of zero, wherein the penalty value represents the hazard associated with the target glucose state.

12. The method of claim 1, wherein the target glucose state includes a target glucose level of about 112.5 milligrams per deciliter and a target rate of change of about zero milligrams per deciliter per second.

13. A method of analyzing a glucose state of a person with diabetes, the method comprising:

detecting, by at least one computing device, a glucose state of the person based on at least one measured glucose value provided with a glucose sensor, the detected glucose state including a glucose level of the person and a rate of change of the glucose level;

determining, by hazard analysis logic of the at least one computing device, a target return path for a transition from the detected glucose state to a target glucose state, the target glucose state including a target glucose level and a target rate of change of the target glucose level, the target return path comprising at least one intermediate glucose state associated with the transition from the detected glucose state to the target glucose state; and

computing, by the hazard analysis logic of the at least one computing device, at least one risk metric associated with the detected glucose state based on the at least one intermediate glucose state of the target return path.

14. The method of claim 13, wherein the target return path includes a plurality of intermediate glucose states each having an associated penalty value, the detected glucose state has an associated penalty value, and each penalty value includes a measure of a hazard associated with the corresponding glucose state.

15. The method of claim 14, wherein the at least one risk metric associated with the detected glucose state includes a cumulative penalty value comprising a sum of the penalty values associated with the plurality of intermediate glucose states and the penalty value associated with the detected glucose state.

16. The method of claim 14, wherein the at least one risk metric associated with the detected glucose state includes a mean penalty rate for the target return path, wherein the mean penalty rate is calculated based on the ratio between a sum of the penalty values associated with the target return path and a total estimated time to complete the transition from the detected glucose state to the target glucose state along the target return path.

17. The method of claim 14, wherein the at least one risk metric associated with the detected glucose state includes a maximum penalty value of the glucose states of the target return path.

18. The method of claim 13, wherein the at least one risk metric associated with the detected glucose state includes a total estimated time for the person to transition from the detected glucose state to the target glucose state along the target return path.

19. The method of claim 18, wherein the total estimated time is computed based on a predetermined maximum acceleration of glucose and the number of intermediate glucose states along the target return path.

20. The method of claim 13, further comprising adjusting, by the at least one computing device, a therapy of the person to transition the person from the detected glucose state towards the target glucose state based on the target return path.

21. The method of claim 20, wherein adjusting the therapy includes adjusting at least one of a basal rate and a bolus of an insulin treatment provided to the person.

22. The method of claim 13, further comprising:

comparing, by the hazard analysis logic, the at least one risk metric associated with the detected glucose state to a risk threshold; and

upon the at least one risk metric exceeding the risk threshold, adjusting a therapy of the person to transition the person from the detected glucose state towards the target glucose state along a second return path having at least one intermediate glucose state that is different from the target return path.

23. The method of claim 13, further comprising:

detecting a plurality of glucose states of the person to identify a trace of glucose states of the person, each glucose state including a glucose level of the person and a rate of change of the glucose level;

determining, for each detected glucose state, a target return path from the detected glucose state to the target glucose state, each target return path comprising at least one intermediate glucose state associated with a transition from the detected glucose state to the target glucose state; and

calculating, for each detected glucose state, at least one risk metric associated with the detected glucose state based on the at least one intermediate glucose state of the target return path.

24. The method of claim 13, wherein the target glucose state includes a target glucose level of about 112.5 milligrams per deciliter and a target rate of change of about zero milligrams per deciliter per second.

25. The method of claim 13, wherein at least one of the detected glucose level and the detected rate of change is estimated by the at least one computing device based on the at least one measured glucose value weighted with a probability of accuracy of the glucose sensor.

26. The method of claim 25, wherein the at least one of the detected glucose level and the detected rate of change is estimated with a recursive filter of the at least one computing device.

27. The method of claim 25, wherein the computing the at least one risk metric associated with the detected glucose state is based on a penalty value associated with the detected glucose state and on the accuracy of the glucose sensor.

28. The method of claim 13, wherein the detecting the glucose state of the person comprises detecting each of the glucose level, the rate of change of the glucose level, and an acceleration of the glucose level based on the at least one measured glucose value provided with the glucose sensor.

29. The method of claim 13, further comprising providing a lookup table that includes a mapping of each of a plurality of glucose states to a corresponding target return path and to a corresponding risk metric, the lookup table being stored in memory accessible by the at least one computing device, wherein the computing the at least one risk metric associated with the detected glucose state comprises:

accessing the lookup table to identify a glucose state of the lookup table that substantially matches the detected glucose state of the person, and

retrieving the risk metric corresponding to the identified glucose state from the lookup table.

30. A non-transitory computer-readable medium comprising:

executable instructions such that when executed by at least one processor cause the at least one processor to;

identify a target glucose state including a target glucose level and a target rate of change of the target glucose level;

identify an initial glucose state including an initial glucose level and an initial rate of change of the initial glucose level, the initial glucose state being different from the target glucose state;

calculate a target return path for a transition from the initial glucose state to the target glucose state, the target return path comprising at least one intermediate glucose state associated with the transition from the initial glucose state to the target glucose state, the target return path being calculated by the at least one processor based on a hazard associated with the at least one intermediate glucose state of the target return path.

31. The non-transitory computer-readable medium of claim 30, wherein the executable instructions further cause the at least one processor to:

identify a plurality of potential intermediate glucose states between the initial glucose state and the target glucose state; and

select the at least one intermediate glucose state from the plurality of potential intermediate glucose states for the target return path to minimize the hazard associated with the target return path.

32. The non-transitory computer-readable medium of claim 31, wherein the at least one intermediate glucose state of the target return path comprises a plurality of intermediate glucose states each having an associated penalty value, the plurality of intermediate glucose states are selected by the at least one processor from the plurality of potential intermediate glucose states to minimize a sum of the penalty values associated with the target return path, and each penalty value includes a measure of a hazard associated with the corresponding intermediate glucose state.

33. The non-transitory computer-readable medium of claim 30, wherein the target return path is calculated by the at least one processor further based on a physiological limit of a glucose perturbation.

34. The non-transitory computer-readable medium of claim 33, wherein the executable instructions further cause the at least one processor to:

identify a plurality of potential glucose states based on the target glucose state, the physiological limit of the glucose perturbation, and a predetermined period for a transition to the target glucose state from each of the potential glucose states; and

select an intermediate glucose state from the plurality of potential glucose states for the target return path to minimize the hazard associated with the target return path.

35. The non-transitory computer-readable medium of claim 30, wherein the executable instructions further cause the at least one processor to:

calculate a target return path for each of a plurality of initial glucose states, each target return path comprising a plurality of intermediate glucose states associated with a transition from the initial glucose state to the target glucose state, each target return path being calculated based on a minimization of a hazard associated with the plurality of intermediate glucose states of the target return path; and

generate a lookup table that maps each of the plurality of initial glucose states to the corresponding target return path, and

store the lookup table in memory accessible by the at least one processor.

36. The non-transitory computer-readable medium of claim 35, wherein the executable instructions further cause the at least one processor to:

detect a glucose state of a person with diabetes based on at least one measured glucose value provided with a glucose sensor;

access the lookup table to identify an initial glucose state of the plurality of initial glucose states that is substantially the same as the detected glucose state of the person; and

identify a penalty value in the lookup table associated with the identified initial glucose state, the penalty value representing a hazard associated with the identified initial glucose state based on the corresponding target return path of the identified initial glucose state.

37. A non-transitory computer-readable medium comprising:

executable instructions such that when executed by at least one processor cause the at least one processor to;

detect a glucose state of the person based on at least one measured glucose value provided with a glucose sensor, the detected glucose state including a glucose level of the person and a rate of change of the glucose level;

determine a target return path for a transition from the detected glucose state to a target glucose state, the target glucose state including a target glucose level and a target rate of change of the target glucose level, the target return path comprising at least one intermediate glucose state associated with the transition from the detected glucose state to the target glucose state; and

compute at least one risk metric associated with the detected glucose state based on the at least one intermediate glucose state of the target return path.

38. The non-transitory computer-readable medium of claim 37, wherein the target return path includes a plurality of intermediate glucose states each having an associated penalty value, the detected glucose state has an associated penalty value, and each penalty value includes a measure of a hazard associated with the corresponding glucose state.

39. The non-transitory computer-readable medium of claim 38, wherein the at least one risk metric associated with the detected glucose state includes at least one of a cumulative penalty value of the target return path, a mean penalty rate of the target return path, and a maximum penalty value for glucose states of the target return path, wherein the cumulative penalty comprises a sum of the penalty values associated with the plurality of intermediate glucose states and the penalty value associated with the detected glucose state, and wherein the mean penalty rate is based on a ratio between the sum of the penalty values and a total estimated time to complete the transition from the detected glucose state to the target glucose state along the target return path.

40. The non-transitory computer-readable medium of claim 37, wherein the at least one risk metric associated with the detected glucose state includes a total estimated time for the person to transition from the detected glucose state to the target glucose state along the target return path.

41. The non-transitory computer-readable medium of claim 37, wherein the executable instructions further cause the at least one processor to adjust a therapy of the person to transition the person from the detected glucose state towards the target glucose state based on the target return path, wherein adjusting the therapy includes adjusting at least one of a basal rate and a bolus of an insulin treatment provided to the person.

42. The non-transitory computer-readable medium of claim 37, wherein the executable instructions further cause the at least one processor to estimate at least one of the glucose level and the rate of change of the glucose level based on the at least one measured glucose value weighted with an accuracy of the glucose sensor.

43. The non-transitory computer-readable medium of claim 42, wherein the executable instructions further cause the at least one processor to calculate a risk associated with the detected glucose state based on a penalty value associated with the detected glucose state and based on the accuracy of the glucose sensor.

44. The non-transitory computer-readable medium of claim 37, wherein, to compute the at least one risk metric associated with the detected glucose state, the executable instructions cause the at least one processor to:

access a lookup table to identify a glucose state of the lookup table that substantially matches the detected glucose state of the person, wherein the lookup table includes a mapping of each of a plurality of glucose states to a corresponding target return path and to a corresponding risk metric; and

retrieve the risk metric corresponding to the identified glucose state from the lookup table.