Systems and methods for pattern recognition in diabetes management

• US 8,758,245 B2
• Filed: 03/20/2007
• Issued: 06/24/2014
• Est. Priority Date: 03/20/2007
• Status: Active Grant

• Current Assignee: Cilag Gmbh International (Johnson & Johnson)
• Original Assignee: Lifescan Incorporated (Duv Holding Corporation)
• Inventors: Ray, Pinaki, Matian, Greg, Srinivasan, Aparna, Rodbard, David, Price, David
• Primary Examiner(s): Kahelin, Michael
• Assistant Examiner(s): TOTH, KAREN E
• Application Number:
  US11/688,639
• Publication Number:
  US 20080234992A1
• Time in Patent Office: 2,653 Days
• Field of Search: 600/345, 600/347, 600/365
• US Class Current: 600/365
• CPC Class Codes: G01N 33/66 involving blood sugars, e.g. galactose
• CPC Class Codes: G06F 17/18 for evaluating statistical data , e.g. average values, frequency distributions, probability functions, regression analysis forecasting specially adapted for a specific administrative, business or logistic context G06Q10/04
• CPC Class Codes: G16H 15/00 ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: G16H 20/10 relating to drugs or medications, e.g. for ensuring correct administration to patients
• 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

Abstract

A diabetes management system or process is provided herein that may be used to analyze and recognize patterns for a large number of blood glucose concentration measurements and other physiological parameters related to the glycemia of a patient. In particular, a method of monitoring glycemia in a patient may include storing a patient'"'"'s data on a suitable device, such as, for example, a blood glucose meter. The patient'"'"'s data may include blood glucose concentration measurements. The diabetes management system or process may be installed on, but is not limited to, a personal computer, an insulin pen, an insulin pump, or a glucose meter. The diabetes management system or process may identify a plurality of pattern types from the data including a testing/dosing pattern, a hypoglycemic pattern, a hyperglycemic pattern, a blood glucose variability pattern, and a comparative pattern. After identifying a particular pattern with the data management system or process, a warning message may be displayed on a screen of a personal computer or a glucose meter. Other messages can also be provided to ensure compliance of any prescribed diabetes regiments or to guide the patient in managing the patient'"'"'s diabetes.

Claims

1. A method of monitoring glycemia in a patient with a glucose meter that includes at least a power source, microprocessor, memory and display, the method comprising:

measuring, with a microprocessor of the meter, a plurality glucose concentrations of a patient with the glucose meter to provide a plurality of glucose measurements;

storing in the memory of the meter, the plurality of glucose measurements of the patient;

using the microprocessor, generating, from the memory, statistically significant patterns from the patient'"'"'s glucose measurements, the patterns indicative of hypoglycemia, hyperglycemia, or excessive glucose variability by time of day, by day in a week, both by time of day and day of week, or at different time intervals which are selected from a group consisting of a time interval between visits to a physician, a time interval between visits to a clinician, a time interval between different prescribed therapies, and combinations thereof, the generating comprising;

determining a hypoglycemic pattern by;

obtaining a number of glucose measurements over a total time period;

dividing the total time period into a plurality of time intervals;

determining a percentage of hypoglycemic incidence for each of the time intervals which recurs daily and is equal to about one eighth of a day;

determining whether the percentage of hypoglycemic incidence for at least one of the time intervals is statistically significantly different;

displaying a message upon one of the patterns being indicative of a pattern of glycemia outside at least a predetermined range for such pattern with the display;

using the microprocessor, utilizing a chi-squared test to determine if any of the time intervals is statistically significantly different wherein the chi-squared test uses a confidence level ranging from about 95% to about 99%, the number of glucose measurements is greater than about 27, the chi-squared test is of the form;

2. The method of claim 1, further comprising:

calculating Z_i using a Z test, the Z test comprising;

3. The method of claim 1, wherein the generating comprises determining hyperglycemic patterns by:

obtaining a number of glucose measurements over a total time period;

dividing the total time period into a plurality of time intervals;

determining percentage of hyperglycemic incidence for each of the time intervals which recurs daily and is equal to about one eighth of a day;

determining whether the percentage of hyperglycemic incidence for at least one of the time intervals is statistically significantly different with a chi squared test χ

² with a confidence level ranging from about 95% to about 99% that comprises;