CGM-based prevention of hypoglycemia via hypoglycemia risk assessment and smooth reduction of insulin delivery

• US 8,562,587 B2
• Filed: 02/25/2010
• Issued: 10/22/2013
• Est. Priority Date: 02/25/2009
• Status: Active Grant

• Current Assignee: University of Virginia
• Original Assignee: University of Virginia Patent Foundation (University of Virginia)
• Inventors: Kovatchev, Boris P., Breton, Marc D., Patek, Stephen D.
• Primary Examiner(s): Lucchesi, Nicholas
• Assistant Examiner(s): Eisenberg, Rebecca E
• Application Number:
  US13/203,469
• Publication Number:
  US 20120059353A1
• Time in Patent Office: 1,335 Days
• Field of Search: 604503-504
• US Class Current: 604/504
• CPC Class Codes: A61B 5/0002 Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network A61B5/07 takes precedence; transmission systems for measured values G08C; transmission H04B; transmission of digital information H04L; wireless communication networks H04W
• CPC Class Codes: A61B 5/0004 characterised by the type of physiological signal transmitted
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/4839 combined with drug delivery
• 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 5/746 Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms alarms per se G08B
• CPC Class Codes: A61M 5/1723 using feedback of body parameters, e.g. blood-sugar, pressure measurement of body parameters A61B5/00
• CPC Class Codes: A61P 3/10 for hyperglycaemia, e.g. antidiabetics
• 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
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders

Abstract

An aspect of an embodiment or partial embodiment of the present invention (or combinations of various embodiments in whole or in part of the present invention) comprises, but not limited thereto, a method and system (and related computer program product) for continually assessing the risk of hypoglycemia for a patient and then determining what action to take based on that risk assessment. A further embodiment results in two outputs: (1) an attenuation factor to be applied to the insulin rate command sent to the pump (either via conventional therapy or via open or closed loop control) and/or (2) a red/yellow/green light hypoglycemia alarm providing to the patient an indication of the risk of hypoglycemia. The two outputs of the CPHS can be used in combination or individually.

Claims

1. A computer-implemented method for preventing or mitigating hypoglycemia in a subject, comprising:

receiving, by a processor, metabolic measurements associated with the subject from a metabolic measurement device;

assessing, by a processor a risk of hypoglycemia based on the received metabolic measurements;

determining, by a processor, an insulin delivery attenuation factor based on the assessed risk of hypoglycemia; and

outputting, by a processor, said insulin delivery attenuation factor to an insulin delivery device that adjusts delivery of insulin to said subject in accordance with said insulin delivery attenuation factor, if the assessed risk of hypoglycemia is above a predetermined threshold.

2. The method of claim 1, wherein said metabolic measurement comprises blood or interstitial glucose data.

3. The method of claim 1, wherein said risk assessment is determined by a risk assessment function R(t), where:

4. The method of claim 3, wherein the threshold glucose concentration is the glucose concentration below which the risk assessment function will be positive.

5. The method of claim 3, wherein the values for parameters α

(θ

), β

(θ

), and γ

(θ

) are as follows;

6. The method of claim 3, wherein the insulin delivery attenuation factor is φ

_brakes(R(t)), where

φ

_brakes(R(t))=1/(1+k·

R(t)),

and wherein k is an aggressiveness factor.

7. The method of claim 6, wherein he aggressiveness factor corresponds to insulin sensitivity.

8. The method of claim 6, wherein the aggressiveness factor k is:

k=exp(−

0.7672−

0.0091·

TDI+0.0449·

CF),

wherein TDI is total daily insulin and CF is a correction factor.

9. The method of claim 3, further comprising:

obtaining a programmed rate of insulin injection; and

multiplying the programmed rate of insulin injection by the insulin delivery attenuation factor to determine an attenuated insulin injection rate.

10. The method of claim 1, further comprising:

receiving external insulin data associated with said subject;

whereby

said risk assessment is determined by using said received external insulin data in addition to said received metabolic measurements.

11. The method of claim 1, further comprising:

outputting a signal to a user corresponding to a determined one of a plurality of predefined levels of hypoglycemia risk as determined based on the received metabolic measurements, wherein one of said levels corresponds to a signal indicating that external intervention is needed to reduce risk of hypoglycemia.

12. A system for preventing or mitigating hypoglycemia in a subject, comprising:

a metabolic measurement device for obtaining metabolic measurements associated with the subject;

an assessment device for receiving said metabolic measurements and assessing a risk of hypoglycemia based on the metabolic measurements;

an evaluation device for determining an insulin delivery attenuation factor based on the assessed the risk of hypoglycemia, and outputting said insulin delivery attenuation factor to an insulin delivery device that adjusts delivery of insulin to said subject in accordance with said insulin delivery attenuation factor, if the assessed risk of hypoglycemia is above a predetermined threshold.

13. The system of claim 12, wherein said metabolic measurement comprises blood or interstitial glucose data.

14. The system of claim 12, wherein the risk assessment is determined by a risk assessment function R(t), where:

15. The system of claim 14, wherein the threshold glucose concentration is the glucose concentration below which the risk function will be positive.

16. The system of claim 14, wherein the values for parameters α

(θ

), β

(θ

), and γ

(θ

) are as follows;

17. The system of claim 12, wherein the insulin delivery attenuation factor is φ

_brakes(R(t)), where

φ

_brakes(R(t))=1/(1+k·

R(t)),

and wherein k is an aggressiveness factor.

18. The system of claim 17, wherein the aggressiveness factor corresponds to insulin sensitivity.

19. The system of claim 17, wherein the aggressiveness factor k is:

k=exp(−

0.7672−

0.0091·

TDI+0.0449·

CF),

wherein TDI is total daily insulin and CF is a correction factor.

20. The system of claim 17, further comprising:

a second obtaining device for obtaining a programmed rate of insulin injection; and

a multiplication device for multiplying the programmed rate of insulin injection by the insulin delivery attenuation factor to determine an attenuated insulin injection rate.

21. The system of claim 12, wherein said assessment device further receives external insulin data associated with said subject;

whereby said risk assessment is determined by using said received external insulin data in addition to said received metabolic measurements.

22. The system of claim 12, wherein the assessment device further is adapted to output a signal to a user corresponding to a determined one of a plurality of predefined levels of hypoglycemia risk as determined based on the received metabolic measurements, wherein one of said levels corresponds to a signal indicating that external intervention is needed to reduce risk of hypoglycemia.

23. A computer program product comprising a non-transitory computer readable storage medium having stored therein computer executable instructions for causing a computer system to prevent or mitigate hypoglycemia in a subject, said computer executable instructions comprising instructions for:

receiving data of metabolic measurements associated with the subject from a metabolic measurement device;

assessing a risk of hypoglycemia based on the received metabolic measurements;

determining an insulin delivery attenuation factor based on the assessed risk of hypoglycemia; and

outputting said insulin delivery attenuation factor to an insulin delivery device that adjusts delivery of insulin to said subject in accordance with said insulin delivery attenuation factor, if the assessed risk of hypoglycemia is above a predetermined threshold.

24. The computer program product of claim 23, wherein said metabolic measurement comprises blood or interstitial glucose data.

25. The computer program product of claim 23, wherein the risk assessment is determined by a risk assessment function R(t), where:

26. The computer program product of claim 25, wherein the values for parameters α

(θ

), β

(θ

), and γ

(θ

) are as follows;

27. The computer program product of claim 25, wherein the insulin delivery attenuation factor is φ

_brakes(R(t)), where

φ

_brakes(R(t))=1/(1+k·

R(t)),

and wherein k is an aggressiveness factor.

28. The computer program product of claim 27, wherein the aggressiveness factor k is

k=exp(−

0.7672−

0.0091·

TDI+0.0449·

CF),

wherein TDI is total daily insulin and CF is a correction factor.

29. The computer program product of claim 23, further comprising computer executable instructions for:

receiving external insulin data associated with said subject; and

wherein said instructions for assessing risk use said received external insulin data in addition to said received metabolic measurements.

30. The computer program product of claim 23, further comprising computer executable instructions for:

outputting a signal to a user corresponding to a determined one of a plurality of predefined levels of hypoglycemia risk as determined based on the received metabolic measurements, wherein one of said levels corresponds to a signal indicating that external intervention is needed to reduce risk of hypoglycemia.