Means and method for improved glycemic control for diabetic patients

• US 10,629,294 B2
• Filed: 07/23/2019
• Issued: 04/21/2020
• Est. Priority Date: 09/11/2012
• Status: Active Grant

• Current Assignee: Glytec LLC (Aseko, Inc.)
• Original Assignee: Aseko, Inc.
• Inventors: Booth, Robert C., Fischell, Robert E.
• Primary Examiner(s): Kanaan, Maroun P
• Application Number:
  US16/519,502
• Publication Number:
  US 20190348157A1
• Time in Patent Office: 273 Days
• CPC Class Codes: A61B 2562/0295 Strip shaped analyte sensors for apparatus classified in A61B5/145 or A61B5/157 disposable multilayered or laminated electrodes G01N27/307; details of handling chemical test elements G01N33/4875
• CPC Class Codes: A61B 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• 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: G06F 3/04847 Interaction techniques to control parameter settings, e.g. interaction with sliders or dials
• CPC Class Codes: G16H 10/40 for data related to laboratory analysis, e.g. patient specimen analysis
• CPC Class Codes: G16H 20/10 relating to drugs or medications, e.g. for ensuring correct administration to patients
• CPC Class Codes: G16H 20/17 delivered via infusion or injection
• CPC Class Codes: G16H 20/30 relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• CPC Class Codes: G16H 20/60 relating to nutrition control, e.g. diets
• 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 80/00 ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass

Abstract

A glycemic control system includes a physician processor, remote processor, and a portable telephone having a data input mechanism, a display, and an internal processor for bi-directional communication with the physician'"'"'s processor and the remote processor. A patient inputs data to the internal processor responsive to input from the physician'"'"'s processor and then transmits the information to the remote processor where an optimized number of units to be administered is sent back and displayed on the portable telephone.

Claims

1. A method comprising:

obtaining, at data processing hardware, a glucose measurement of a patient and patient condition parameters during a pre-meal time, the patient condition parameters comprising a number of carbohydrates to be consumed by the patient, and the pre-meal time associated with a meal type corresponding to one of breakfast, lunch, or dinner;

determining, by the data processing hardware, a recommended meal bolus for the patient based on the obtained patient condition parameters;

obtaining, by the data processing hardware, an insulin sensitivity factor for the patient and a target glucose range defined by upper and lower glucose limits for the patient;

determining, by the data processing hardware, whether the glucose measurement exceeds a midpoint of the target glucose range for the patient;

when the glucose measurement exceeds the midpoint of the target glucose range for the patient, determining, by the data processing hardware, a correction dose by calculating;

2. The method of claim 1, wherein determining the recommended meal bolus comprises:

obtaining a carbohydrate-to-insulin ratio for the patient; and

dividing the number of carbohydrates to be consumed by the patient by the carbohydrate-to-insulin ratio to determine the recommended meal bolus.

3. The method of claim 2, wherein the carbohydrate-to-insulin ratio is calculated as follows:

CIR=450×

TDD,

wherein CIR is the carbohydrate-to-insulin ratio and TDD is a total prescribed daily dose of insulin for the patient based on a weight of the patient.

4. The method of claim 2, wherein the carbohydrate-to-insulin ratio is inputted into memory hardware in communication with the data processing hardware by a medical professional computing device associated with an authorized medical professional.

5. The method of claim 1, wherein the user device is configured to:

receive, in the user interface, inputs from the patient for each of the patient condition parameters during the pre-meal time; and

transmit the patient condition parameters to the data processing hardware.

6. The method of claim 1, wherein the user device is configured to:

receive, in the user interface, a glucose input from the patient indicating the glucose measurement; and

transmit the glucose measurement of the patient to the data processing hardware.

7. The method of claim 1, wherein the insulin sensitivity factor and the target glucose range are inputted into memory hardware in communication with the data processing hardware by a medical professional computing device associated with an authorized medical professional.

8. The method of claim 1, wherein the obtained patient condition parameters further comprise an exercise parameter indicating a duration and/or severity of an exercise planned by the patient or recently completed by the patient.

9. The method of claim 8, further comprising:

determining, by the data processing hardware, carbohydrate intake instructions for the patient including a predetermined amount of carbohydrates for the patient to consume based on the duration and/or severity of the exercise; and

transmitting the carbohydrate intake instructions to the user device, the carbohydrate intake instructions when received by the user device, causing the user interface executing on the user device to display the predetermined amount of carbohydrates for the patient to consume.

10. A system comprising:

a user device controlled by a patient and having a screen, the user device configured to execute a user interface for display on the screen; and

data processing hardware in communication with the user device, the data processing hardware configured to perform operations comprising;

obtaining a glucose measurement of the patient and patient condition parameters during a pre-meal time, the patient condition parameters comprising a number of carbohydrates to be consumed by the patient, and the pre-meal time associated with a meal type corresponding to one of breakfast, lunch, or dinner;

determining a recommended meal bolus for the patient based on the obtained patient condition parameters;

obtaining an insulin sensitivity factor for the patient and a target glucose range defined by upper and lower glucose limits for the patient;

determining whether the obtained glucose measurement exceeds a midpoint of the target glucose range for the patient;

when the glucose measurement exceeds the midpoint of the target glucose range for the patient, determining a correction dose by calculating;

11. The system of claim 10, wherein determining the recommended meal bolus comprises:

obtaining a carbohydrate-to-insulin ratio for the patient; and

dividing the number of carbohydrates to be consumed by the patient by the carbohydrate-to-insulin ratio to determine the recommended meal bolus.

12. The system of claim 11, wherein the carbohydrate-to-insulin ratio is calculated as follows:

CIR=450×

TDD,

wherein CIR is the carbohydrate-to-insulin ratio and TDD is a total prescribed daily dose of insulin for the patient based on a weight of the patient.

13. The system of claim 11, wherein the carbohydrate-to-insulin ratio are inputted into memory hardware in communication with the data processing hardware by a medical professional computing device associated with an authorized medical professional.

14. The system of claim 10, wherein the user device is configured to:

receive, in the user interface, inputs from the patient for each of the patient condition parameters during the pre-meal time; and

transmit the patient condition parameters to the data processing hardware.

15. The system of claim 10, wherein the user device is configured to:

receive, in the user interface, a glucose input from the patient indicating the glucose measurement; and

transmit the glucose measurement of the patient to the data processing hardware.

16. The system of claim 10, wherein the insulin sensitivity factor and the target glucose range are inputted into memory hardware in communication with the data processing hardware by a medical professional computing device associated with an authorized medical professional.

17. The system of claim 10, wherein the obtained patient condition parameters further comprise an exercise parameter indicating a duration and/or severity of an exercise planned by the patient or recently completed by the patient.

18. The system of claim 17, wherein the operations further comprise:

determining carbohydrate intake instructions for the patient including a predetermined amount of carbohydrates for the patient to consume based on the duration and/or severity of the exercise; and

transmitting the carbohydrate intake instructions to the user device, the carbohydrate intake instructions when received by the user device, causing the user interface executing on the user device to display the predetermined amount of carbohydrates for the patient to consume.