Glycemic health metric determination and application

• US 10,779,754 B2
• Filed: 08/18/2016
• Issued: 09/22/2020
• Est. Priority Date: 12/29/2010
• Status: Active Grant

• Current Assignee: Medtronic Minimed Incorporated (Medtronic Plc)
• Original Assignee: Medtronic Minimed Incorporated (Medtronic Plc)
• Inventors: Desborough, Lane, Palerm, Cesar C.
• Primary Examiner(s): Wise, Olivia M.
• Application Number:
  US15/240,275
• Publication Number:
  US 20160354019A1
• Time in Patent Office: 1,496 Days
• Field of Search: None
• 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 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/4839 combined with drug delivery
• CPC Class Codes: A61B 5/6849 in combination with a needle set
• CPC Class Codes: A61B 5/7225 Details of analog processing, e.g. isolation amplifier, gain or sensitivity adjustment, filtering, baseline or drift compensation A61B5/30, A61B5/316 take precedence; transformers for specific applications H01F38/00; amplifiers H03F
• 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 20/17 delivered via infusion or injection
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment

Abstract

Disclosed are methods, apparatuses, etc. for determination and application of a unidimensional metric for assessing a patient'"'"'s glycemic health. In one particular implementation, a computed metric may be used to balance short-term and long-term risks associated with a particular therapy. In another implementation, a computed unidimensional metric may be used to balance risks of hyperglycemia and hypoglycemia.

Claims

1. An apparatus for use with a plurality of glucose monitoring devices, with a plurality of patients, and with an insulin delivery system, the apparatus comprising:

one or more processors to;

obtain a plurality of observations of blood glucose concentrations of the plurality of patients received at the plurality of glucose monitoring devices;

compute a plurality of profiles of blood glucose concentrations based, at least in part, on the plurality of the observations;

for the plurality of patients, determine an associated plurality of unidimensional metrics indicative of glycemic health of the plurality of patients, the plurality of unidimensional metrics to be computed based, at least in part, on a convolution of a cost or loss function and the plurality of profiles of blood glucose concentrations of the plurality of patients;

rank the plurality of patients for treatment according to a triage policy based, at least in part, on the plurality of unidimensional metrics; and

control the insulin delivery system for balancing hypoglycemic and hyperglycemic tendencies in one of the plurality of patients based, at least in part, on the ranking of the plurality of patients for treatment according to the triage policy.

2. The apparatus of claim 1, wherein the apparatus is further for use with computing platforms co-located with the plurality of patients, and with a communication network, the apparatus further comprising communication interface components to receive information from the communication network,

wherein the plurality of unidimensional metrics are further to be computed based, at least in part, on messages received through the communication interface components from the computing platforms co-located with the plurality of patients.

3. The apparatus of claim 2, wherein the messages comprise the plurality of blood glucose concentrations.

4. The apparatus of claim 2, wherein the messages comprise the unidimensional metrics computed at the computing platforms co-located with the plurality of patients.

5. An article for use with a plurality of glucose monitoring devices, with a plurality of patients, with an insulin delivery system, and with a special purpose computing apparatus, the article comprising:

a non-transitory storage medium comprising machine-readable instructions stored thereon which are executable by the special purpose computing apparatus to;

obtain a plurality of observations of blood glucose concentrations of the plurality of patients from the plurality of glucose monitoring devices;

compute a plurality of profiles of blood glucose concentrations based, at least in part, on the plurality of the observations;

determine an associated plurality of unidimensional metrics indicative of glycemic health of the plurality of patients, the plurality of unidimensional metrics to be computed based, at least in part, on a convolution of a cost or loss function and the plurality of profiles of blood glucose concentrations of the plurality of patients;

rank the plurality of patients for treatment according to a triage policy based, at least in part, on the plurality of unidimensional metrics; and

control the insulin delivery system to balance hypoglycemic and hyperglycemic tendencies in one of the plurality of patients based, at least in part, on the ranking of the plurality of patients for treatment according to the triage policy.

6. The article of claim 5 wherein the article is further for use with computing platforms co-located with the plurality of patients, and with a communication network, the article further comprising machine-readable instructions that when executed by the special purpose computing apparatus are to:

obtain messages received from the computing platforms co-located with the plurality of patients through the communication network;

wherein the plurality of unidimensional metrics are further to be computed based, at least in part, on the obtained messages.

7. The article of claim 6, wherein the received messages comprise the plurality of blood glucose concentrations.

8. The article of claim 6, wherein the messages comprise the unidimensional metrics computed at the computing platforms co-located with the plurality of patients.

9. A method comprising:

obtaining a plurality of observations of blood glucose concentrations of a plurality of patients using a plurality of glucose monitoring devices;

at a special purpose computing apparatus, computing a plurality of profiles of blood glucose concentrations based, at least in part, on the plurality of the observations;

at the special purpose computing apparatus, for the plurality of patients, determining an associated plurality of unidimensional metrics indicative of glycemic health of the plurality of patients, the plurality of unidimensional metrics being computed based, at least in part, on a convolution of a cost or loss function and the plurality of profiles of blood glucose concentrations of the plurality of patients, the plurality of profiles of blood glucose concentrations being obtained for the plurality of patients under a plurality of predefined therapies; and

controlling, by the special purpose computing apparatus, an insulin delivery system for balancing hypoglycemic and hyperglycemic tendencies in one of the plurality of patients based, at least in part, on ranking by the special purpose computing apparatus of the plurality of predefined therapies,

wherein the ranking the plurality of predefined therapies is based, at least in part, on the plurality of unidimensional metrics.

10. The method of claim 9, wherein the plurality of predefined therapies are defined, at least in part, by closed-loop system design features.

11. The method of claim 9, further comprising:

receiving messages from computing platforms co-located with the plurality of patients through a communication network;

wherein the plurality of unidimensional metrics are further to be computed based, at least in part, on the received messages.

12. The method of claim 11, wherein the received messages comprise the plurality of the observations of the blood glucose concentrations.

13. The method of claim 11, wherein the received messages comprise the unidimensional metrics computed at the computing platforms co-located with the plurality of patients.