Systems and methods for dynamically and intelligently monitoring a host's glycemic condition after an alert is triggered

• US 10,143,426 B2
• Filed: 04/13/2017
• Issued: 12/04/2018
• Est. Priority Date: 10/30/2012
• Status: Active Grant

• Current Assignee: DexCom Incorporated
• Original Assignee: DexCom Incorporated
• Inventors: Hampapuram, Hari, Davis, Anna Leigh, Bhavaraju, Naresh C., Kamath, Apurv Ullas, Cobelli, Claudio, Sparacino, Giovanni, Facchinetti, Andrea, Zecchin, Chiara
• Primary Examiner(s): McNally, Kerri L
• Application Number:
  US15/486,704
• Publication Number:
  US 20170224291A1
• Time in Patent Office: 600 Days
• Field of Search: 3405731
• CPC Class Codes: A61B 5/0004 characterised by the type of physiological signal transmitted
• CPC Class Codes: A61B 5/002 Monitoring the patient using a local or closed circuit, e.g. in a room or building A61B5/0017 takes precedence
• CPC Class Codes: A61B 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• CPC Class Codes: A61B 5/0031 Implanted circuitry
• CPC Class Codes: A61B 5/14503 invasive, e.g. introduced into the body by a catheter or needle or using implanted sensors A61B5/1459, A61B5/1464, A61B5/1473, A61B5/1482, A61B5/14865 take precedence
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/4848 Monitoring or testing the effects of treatment, e.g. of medication
• CPC Class Codes: A61B 5/4866 Evaluating metabolism A61B5/083 takes precedence
• CPC Class Codes: A61B 5/7221 Determining signal validity, reliability or quality A61B5/7207 and A61B5/7217 take precedence
• 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: G16H 40/67 for remote operation
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment

Abstract

Systems and methods for providing sensitive and specific alarms indicative of glycemic condition are provided herein. In an embodiment, a method of processing sensor data by a continuous analyte sensor includes: evaluating sensor data using a first function to determine whether a real time glucose value meets a first threshold; evaluating sensor data using a second function to determine whether a predicted glucose value meets a second threshold; activating a hypoglycemic indicator if either the first threshold is met or if the second threshold is predicted to be met; and providing an output based on the activated hypoglycemic indicator.

Claims

1. A method of avoiding unnecessary hyperglycemic alerts, the method comprising:

initially activating a first alert state based on one or more first criteria associated with a hyperglycemic condition;

waiting a time period before providing an output associated with the first alert state, wherein the waiting includes determining the time period using at least in part a machine or adaptive learning algorithm to learn a lag setting, unique to the individual, associated with the time period;

actively monitoring, by a processor module, data associated with the host'"'"'s hyperglycemic condition during the waiting time period; and

providing an output associated with the first alert state after the waiting time period if the data associated with the host'"'"'s hyperglycemic condition meets one or more second criteria and not providing an output associated with the first alert state after the waiting time period if the data associated with the host'"'"'s hyperglycemic condition does not meet the one or more second criteria, wherein a numerical value associated with the one or more first criteria and a numerical value associated with the one or more second criteria are different.

2. The method of claim 1, wherein the actively monitoring comprises determining an average glucose over a window of time.

3. The method of claim 1, wherein the actively monitoring comprises determining an amplitude and/or direction of rate of change.

4. The method of claim 1, wherein the actively monitoring comprises determining an amplitude and/or direction of rate of acceleration.

5. The method of claim 1, wherein the actively monitoring comprises evaluating insulin information.

6. The method of claim 1, wherein the actively monitoring comprises evaluating meal information or timing.

7. The method of claim 1, wherein the waiting time period is user selectable.

8. The method of claim 1, further comprising transitioning from the first alert state to an inactive alert state based on the data associated with the host'"'"'s hyperglycemic condition meeting the one or more second criteria.

9. A system for processing data, the system comprising:

a continuous analyte sensor configured to be implanted within a body; and

sensor electronics configured to receive and process sensor data output by the sensor, the sensor electronics including a processor configured to;

initially activate a first alert state based on one or more first criteria associated with a hyperglycemic condition;

wait a time period before providing an output associated with the first alert state, wherein the waiting includes determining the time period using at least in part a machine or adaptive learning algorithm to learn a lag setting, unique to the individual associated with the time period;

actively monitor data associated with the host'"'"'s hyperglycemic condition during the waiting time period; and

provide an output associated with the first alert state after the waiting time period if the data associated with the host'"'"'s hyperglycemic condition meets one or more second criteria and not provide an output associated with the first alert state after the waiting time period if the data associated with the host'"'"'s hyperglycemic condition does not meet the one or more second criteria, wherein a numerical value associated with the one or more first criteria and a numerical value associated with the one or more second criteria are different.

10. The system of claim 9, wherein the actively monitoring comprises determining an average glucose over a window of time.

11. The system of claim 9, wherein the actively monitoring comprises determining an amplitude and/or direction of rate of change.

12. The system of claim 9, wherein the actively monitoring comprises determining an amplitude and/or direction of rate of acceleration.