Assessing Measures Of Glycemic Variability

• US 20130225959A1
• Filed: 03/29/2013
• Published: 08/29/2013
• Est. Priority Date: 10/23/2007
• Status: Active Grant

• Current Assignee: Abbott Diabetes Care Incorporated (Abbott Laboratories Incorporated)
• Original Assignee: Abbott Diabetes Care Incorporated (Abbott Laboratories Incorporated)
• Inventors: Bugler, Jolyon Robert
• Granted Patent: US 9,439,586 B2
• Time in Patent Office: Days
• US Class Current: 600/365
• 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 5/01 Measuring temperature of body parts ; Diagnostic temperature sensing, e.g. for malignant or inflamed tissue clinical contact thermometers G01K13/20
• 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 5/14546 for measuring analytes not otherwise provided for, e.g. ions, cytochromes
• CPC Class Codes: A61B 5/1468 using chemical or electrochemical methods, e.g. by polarographic means A61B5/1486 takes precedence
• CPC Class Codes: A61B 5/1473 invasive, e.g. introduced into the body by a catheter A61B5/1482 takes precedence
• CPC Class Codes: A61B 5/14735 comprising an immobilised reagent
• CPC Class Codes: A61B 5/1486 using enzyme electrodes, e.g. with immobilised oxidase
• CPC Class Codes: A61B 5/14865 invasive, e.g. introduced into the body by a catheter or needle or using implanted sensors
• CPC Class Codes: A61B 5/1495 Calibrating or testing of in-vivo probes
• CPC Class Codes: A61B 5/7278 Artificial waveform generation or derivation, e.g. synthesising signals from measured signals A61B5/327 takes precedence
• CPC Class Codes: A61B 5/7282 Event detection, e.g. detecting unique waveforms indicative of a medical condition A61B5/4094, A61B5/4818, A61B5/349, A61B5/0823 take precedence
• CPC Class Codes: A61B 5/7405 using sound
• CPC Class Codes: A61B 5/742 using visual displays A61B5/339 takes precedence
• CPC Class Codes: A61B 5/7455 characterised by tactile indication, e.g. vibration or electrical stimulation

Abstract

Methods, devices and systems for receiving an instruction to determine a glycemic variation level, retrieving a stored metric for determining the glycemic variation level, retrieving one or more parameters associated with the retrieved metric analysis, determining the glycemic variation level based on the retrieved one or more parameters for the retrieved metric analysis, and outputting the determined glycemic variation level when it is determined that the retrieved one or more parameters associated with the retrieved metric analysis meets a predetermined condition are disclosed.

Claims

1. A method, comprising:

receiving an instruction to determine a glycemic variation level associated with a glycemic variation metric;

retrieving one or more parameters associated with the glycemic variation metric;

retrieving stored glycemic data based on the one or more retrieved parameters;

determining if the retrieved glycemic data meets one or more predetermined conditions based on the one or more parameters associated with the glycemic variation metric;

determining the glycemic variation level associated with the glycemic variation metric based on the retrieved one or more parameters and the retrieved glycemic data, when it is determined that the one or more predetermined conditions are met;

outputting the determined glycemic variation level; and

outputting a notification when it is determined that the one or more predetermined conditions are not met.

2. The method of claim 1 wherein the parameters associated with the glycemic variation metric include a value for a predetermined time period.

3. The method of claim 1 wherein the parameters associated with the glycemic variation metric include a value for a minimum number of glucose data over a predetermined time period.

4. The method of claim 1 wherein the parameters associated with the glycemic variation metric include a value for a minimum number of days with available glucose data within a predetermined time period.

5. The method of claim 1 wherein the determined glycemic variation level is output as one or more of an audible indication, a visual indication, a vibratory indication, or one or more combinations thereof.

6. The method of claim 1 wherein the determined glycemic variation level is output as a graphical representation of glycemic variation over time.

7. The method of claim 1 wherein the notification is output as one or more of an audible indication, a visual indication, a vibratory indication, or one or more combinations thereof.

8. The method of claim 1 including storing the determined glycemic variation level.

9. The method of claim 1 wherein the glycemic variation metric includes one or more of a standard deviation analysis, Mean Amplitude of Glycemic Excursions (MAGE) analysis, Glycemic Risk Assessment Diabetes Excursion (GRADE) analysis, Lability index analysis, a number of glycemic variation episode excursions analysis, a duration of each glycemic variation episode excursion analysis, an average maximum excursion value analysis, or a low/high blood glucose index analysis.

10. An apparatus, comprising:

one or more processing units; and

a memory for storing instructions which, when executed by the one or more processing units, causes the one or more processing units to receive an instruction to determine a glycemic variation level associated with a glycemic variation metric, to retrieve one or more parameters associated with the glycemic variation metric, to retrieve stored glycemic data based on the one or more retrieved parameters, to determine if the retrieved glycemic data meets one or more predetermined conditions based on the one or more parameters associated with the glycemic variation metric, to determine the glycemic variation level associated with the glycemic variation metric based on the retrieved one or more parameters and the retrieved glycemic data, when it is determined that the one or more predetermined conditions are met, to output the determined glycemic variation level, and to output a notification when it is determined that the one or more predetermined conditions are not met.

11. The apparatus of claim 10 wherein the parameters associated with the glycemic variation metric include a value for a predetermined time period.

12. The apparatus of claim 10 wherein the parameters associated with the glycemic variation metric include a value for a minimum number of glucose data over a predetermined time period.

13. The apparatus of claim 10 wherein the parameters associated with the glycemic variation metric include a value for a minimum number of days with available glucose data within a predetermined time period.

14. The apparatus of claim 10 wherein the determined glycemic variation level is output as one or more of an audible indication, a visual indication, a vibratory indication, or one or more combinations thereof.

15. The apparatus of claim 10 wherein the determined glycemic variation level is output as a graphical representation of glycemic variation over time.

16. The apparatus of claim 10 wherein the notification is output as one or more of an audible indication, a visual indication, a vibratory indication, or one or more combinations thereof.

17. The apparatus of claim 10 wherein the memory for storing instructions which, when executed by the one or more processing units, further causes the one or more processing units to store the determined glycemic variation level.

18. The apparatus of claim 10 wherein the glycemic variation metric includes one or more of a standard deviation analysis, Mean Amplitude of Glycemic Excursions (MAGE) analysis, Glycemic Risk Assessment Diabetes Excursion (GRADE) analysis, Lability index analysis, a number of glycemic variation episode excursions analysis, a duration of each glycemic variation episode excursion analysis, an average maximum excursion value analysis, or a low/high blood glucose index analysis.

19. A method, comprising:

receiving an instruction to determine a glycemic variation level associated with a glycemic variation metric;

retrieving one or more parameters associated with the glycemic variation metric;

retrieving stored glycemic data based on the one or more retrieved parameters;

determining if the retrieved glycemic data meets one or more predetermined conditions based on the one or more parameters associated with the glycemic variation metric;

determining the glycemic variation level associated with the glycemic variation metric based on the retrieved one or more parameters and the retrieved glycemic data, when it is determined that the one or more predetermined conditions are met; and

outputting a notification when it is determined that the one or more predetermined conditions are not met.