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EP-4736760-A2 - SYSTEMS AND METHODS FOR MULTI-ANALYTE SENSING

EP4736760A2EP 4736760 A2EP4736760 A2EP 4736760A2EP-4736760-A2

Abstract

An apparatus includes an analyte sensor, a memory, and a processor. The processor monitors, using the analyte sensor, an analyte of a patient during a time period to obtain measured analyte data for the analyte and monitors other measured sensor data indicative of a physiological state of the patient during the time period. The processor also determines, based on the physiological state of the patient during the time period, expected analyte data for the analyte and determines a correction factor based on the expected analyte data and the measured analyte data. The correction factor is indicative of an error in calibration of the analyte sensor. The processor also determines whether recalibration of the analyte sensor is possible. If recalibration is possible, the processor recalibrates the analyte sensor based on the correction factor, and if recalibration is not possible, the processor recommends, to the patient, to replace the analyte sensor.

Inventors

  • CHENG, KEVIN KA WING
  • FRANK, Spencer Troy
  • Headen, Devon M.
  • AN, Qi
  • DAMLE, SAMIR SUDHIR
  • APOLLO, NICHOLAS VINCENT
  • LIONG, SYLVIE
  • VANRENTERGHEM, Hadley Faith
  • HELAYHEL, Mohamed R.
  • SIMPSON, PETER CHARLES

Assignees

  • DexCom, Inc.

Dates

Publication Date
20260506
Application Date
20230222

Claims (15)

  1. An apparatus comprising: a first analyte sensor; a second analyte sensor; a memory; and a processor communicatively coupled to the memory, the processor configured to: receive data indicative of a historical relationship between a first analyte and a second analyte of a patient during a first time period; obtain first analyte data during a second time period from the first analyte sensor; obtain second analyte data from the second analyte sensor during the second time period; determine a current relationship between the first analyte and the second analyte based on the first analyte data and the second analyte data; determine a difference between the historical relationship and the current relationship; and calibrate the first analyte sensor or the second analyte sensor based on the determined difference.
  2. The apparatus of claim 1, wherein the processor is further configured to determine that recalibration of the first analyte sensor or second analyte sensor is possible, wherein recalibrating the first analyte sensor or the second analyte sensor is in response to determining that recalibration of the first analyte sensor or second analyte sensor is possible.
  3. The apparatus of claim 1, wherein the first analyte is glucose and the second analyte is lactate.
  4. The apparatus of claim 1 or claim 2, wherein the first analyte and/or the second analyte include glucose, lactate, ketones, glycerol, or electrolytes such as sodium and potassium.
  5. The apparatus of claim 1 or claim 2, wherein the first analyte comprises glucose, and the second analyte comprises one or more of lactate, ketones, glycerol, electrolytes such as sodium and potassium.
  6. The apparatus of any preceding claim, wherein the processor is further configured to monitor other measured sensor data indicative of a physiological state of the patient during the first or second time period.
  7. The apparatus of clause 6, wherein the physiological state comprises an oxygen level of the patient or a temperature of the patient.
  8. The apparatus of claim 6, wherein the other measured sensor data includes one or more of accelerometer data, gyrometer data, acoustic data, global positioning system (GPS) data, heart rate, heart rate reserve, heart rate variability (HRV), electrocardiogram (EKG) data, sweat, electromyogram (EMG), respiration rate, temperature, blood pressure, galvanic skin response, oxygen uptake data (e.g., V0 2 max), sleep, and impedance data.
  9. The apparatus of claim 8, wherein the other measured sensor data is utilized to calculate metrics.
  10. The apparatus of claim 9, wherein metrics include glucose levels, glucose thresholds, glucose trends, lactate levels, lactate baseline, lactate threshold, lactate trends, ketone levels, ketone production rates, insulin sensitivity, insulin on board, meal state, meal habits, physical fitness, metabolic rate, body temperature, blood pressure, heart rate, heart rate variability, respiratory rate, or blood-alcohol concentration.
  11. The apparatus of any of claims 6 to 10, wherein the processor is further configured to determine whether a compression event has occurred based on the first and second analyte data and the physiological state of the patient.
  12. The apparatus of claim 11, wherein the processor is further configured to provide an alert or notification to the user that a compression event is detected.
  13. The apparatus of any preceding claim, wherein the processor is further configured to determine a wear location of the first sensor and/or second sensor based on at least the measured first analyte data.
  14. The apparatus of any preceding claim, wherein the processor is further configured to determine a wear location of the first sensor and/or second sensor based on secondary sensor data.
  15. The apparatus of any preceding claim, wherein the processor is further configured to determine a wear location of the first sensor and/or second sensor based on accelerometer data.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS This application claims priority to and benefit of U.S. Provisional Patent Application No. 63/268,334, filed February 22, 2022, which is hereby assigned to the assignee hereof and hereby expressly incorporated by reference in its entirety as if fully set forth below and for all applicable purposes. BACKGROUND Diabetes mellitus is a metabolic condition relating to the production or use of insulin by the body. Insulin is a hormone that allows the body to use glucose for energy, or store glucose as fat. When a person eats a meal that contains carbohydrates, the digestive system absorbs nutrients, ultimately depositing glucose in the person's blood. Blood glucose can be used for energy or stored as fat. The body normally maintains blood glucose levels in a range that provides sufficient energy to support bodily functions and avoids problems that can arise when glucose levels are too high, or too low. Regulation of blood glucose levels depends on the production and use of insulin, which regulates the movement of blood glucose into cells. When the body does not produce enough insulin, or when the body is unable to effectively use insulin that is present, blood sugar levels can elevate beyond normal ranges. The state of having a higher than normal blood sugar level is called "hyperglycemia." Chronic hyperglycemia can lead to a number of health problems, such as cardiovascular disease, cataract and other eye problems, nerve damage (neuropathy), skin ulcers, and kidney damage. Hyperglycemia can also lead to acute problems, such as diabetic ketoacidosis-a state in which the body becomes excessively acidic due to the production of excess ketones, or body acids. The state of having lower than normal blood glucose levels is called "hypoglycemia." Severe hypoglycemia can lead to damage of the heart muscle, neurocognitive dysfunction, and in certain cases, acute crises that can result in seizures or even death. A patient living with diabetes can receive insulin to manage blood glucose levels. Insulin can be received, for example, through a manual injection with a needle. Wearable insulin pumps are also available. Diet and exercise also affect blood glucose levels. Diabetes conditions are sometimes referred to as "Type 1" and "Type 2". A Type 1 diabetes patient is typically able to use insulin when it is present, but the body is unable to produce sufficient amounts of insulin, because of a problem with the insulin-producing beta cells of the pancreas. A Type 2 diabetes patient may produce some insulin, but the patient has become "insulin resistant" due to a reduced sensitivity to insulin. The result is that even though insulin is present in the body, the insulin is not sufficiently used by the patient's body to effectively regulate blood sugar levels. Patients with diabetes can benefit from real-time diabetes management guidance, as determined based on a physiological state of the patient, in order to stay within a target glucose range and avoid physical complications. In certain cases, the physiological state of the patient is determined using diagnostics systems that measure glucose levels, which inform the identification and/or prediction of adverse glycemic events, such as hyperglycemia and hypoglycemia, and the type of guidance provided to the patient. For example, such diagnostics systems may utilize a continuous glucose monitor (CGM) to measure a patient's glucose levels over time. The measured glucose levels may then be processed by the diagnostics system to identify and/or predict adverse glycemic events, and/or to provide guidance to the patient for treatment and or actions to abate or prevent the occurrence of such adverse glycemic events. For example, trends, statistics, or other metrics may be derived from the glucose levels and used to identify and/or predict adverse glycemic events. Or, in certain cases, the glucose levels themselves may be used to identify and/or predict adverse glycemic events. Management of diabetes, however, presents many challenges for patients, clinicians, and caregivers, as a confluence of various factors can impact a patient's glucose levels, thus affecting the accuracy of glycemic event prediction and the guidance provided by diagnostics systems. As such, in order to provide a more comprehensive or accurate characterization of the patient's physiological state at any given moment, a plurality of different analytes, including glucose, may be monitored. The monitoring of one or more of multiple analytes, in addition to or in alternative to glucose, may provide a more complete picture of the physiological state of the patient, since multiple analytes may affect or be affected by the same physiological events/conditions, and/or may affect or be affected by related physiological events/conditions. Examples of such analytes include, ketones, lactate, insulin, electrolytes, creatinine, as well as a number of other biomarkers including proteins, metab