WO2009146445A1 - Procédé et système fournissant un contrôle glycémique - Google Patents

Procédé et système fournissant un contrôle glycémique Download PDF

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Publication number
WO2009146445A1
WO2009146445A1 PCT/US2009/045766 US2009045766W WO2009146445A1 WO 2009146445 A1 WO2009146445 A1 WO 2009146445A1 US 2009045766 W US2009045766 W US 2009045766W WO 2009146445 A1 WO2009146445 A1 WO 2009146445A1
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WIPO (PCT)
Prior art keywords
patient
level
received
hbalc
glucose
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Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
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PCT/US2009/045766
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English (en)
Inventor
Marc B. Taub
Timothy Christian Dunn
Nathan Crouther
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Abbott Diabetes Care Inc
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Abbott Diabetes Care Inc
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Publication of WO2009146445A1 publication Critical patent/WO2009146445A1/fr
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Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration or pH-value ; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid or cerebral tissue
    • A61B5/1468—Measuring characteristics of blood in vivo, e.g. gas concentration or pH-value ; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid or cerebral tissue using chemical or electrochemical methods, e.g. by polarographic means
    • A61B5/1486—Measuring characteristics of blood in vivo, e.g. gas concentration or pH-value ; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid or cerebral tissue using chemical or electrochemical methods, e.g. by polarographic means using enzyme electrodes, e.g. with immobilised oxidase
    • A61B5/14865—Measuring characteristics of blood in vivo, e.g. gas concentration or pH-value ; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid or cerebral tissue using chemical or electrochemical methods, e.g. by polarographic means using enzyme electrodes, e.g. with immobilised oxidase invasive, e.g. introduced into the body by a catheter or needle or using implanted sensors
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration or pH-value ; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid or cerebral tissue
    • A61B5/14532—Measuring characteristics of blood in vivo, e.g. gas concentration or pH-value ; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid or cerebral tissue for measuring glucose, e.g. by tissue impedance measurement
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
    • G16H10/60—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/10—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
    • G16H20/17—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients delivered via infusion or injection
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H30/00—ICT specially adapted for the handling or processing of medical images
    • G16H30/20—ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7271—Specific aspects of physiological measurement analysis
    • A61B5/7275—Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor

Definitions

  • the detection of the level of analytes, such as glucose, lactate, oxygen, and the like, in certain individuals is vitally important to their health.
  • the monitoring of glucose is particularly important to individuals with diabetes.
  • Diabetics may need to monitor glucose levels to determine when insulin is needed to reduce glucose levels in their bodies or when additional glucose is needed to raise the level of glucose in their bodies.
  • devices that allow a user to test for one or more analytes, and provide glycemic control and therapy management.
  • Embodiments of the present disclosure include method and apparatus for receiving mean glucose value information of a patient based on a predetermined time period, receiving an HbAlC level of the patient, determining a correlation between the received mean glucose value information and the HbAlC level, and calculating a target HbAlC level based on the determined correlation.
  • Embodiments of the present disclosure also include method and apparatus for receiving mean glucose value information of a patient based on a predetermined time period, receiving a current HbAlC level of the patient and a target HbAlC level of the patient, determining a correlation between the received mean glucose value information and the retrieved current and target HbAlC levels, updating the target HbAlC level based on the determined correlation, and determining one or more parameters associated with the physiological condition of the patient based on the updated target HbAlC level.
  • FIG. 1 shows a block diagram of an embodiment of a data monitoring and management system according to the present disclosure
  • FIG. 2 shows a block diagram of an embodiment of the transmitter unit of the data monitoring and management system of FIG. 1;
  • FIG. 3 shows a block diagram of an embodiment of the receiver/monitor unit of the data monitoring and management system of FIG. 1;
  • FIG. 4 shows a schematic diagram of an embodiment of an analyte sensor according to the present disclosure
  • FIGS. 5A-5B show a perspective view and a cross sectional view, respectively of another embodiment an analyte sensor
  • FIG. 6 provides a tabular illustration of the demographic and characteristics of participants in the 90 days continuous glucose monitoring system use study in one aspect
  • FIG. 7 is a chart illustrating the relationship between the 90 day mean continuously monitored glucose level and the mean 90 day discrete blood glucose test results compared with the HbAlC level in one aspect
  • FIG. 8 provides a graphical illustration of the individual rates of glycation distribution in one aspect
  • FIG. 9 provides a graphical illustration of the slope and correlation of the continuously monitored glucose level to the HbAlC level on a weekly basis in one aspect
  • FIG. 10 is a graphical illustration of the frequency of the obtained glucose levels between the SMBG (self monitored blood glucose) measurements and the CGM (continuously monitored glucose) measurement on a daily basis in one aspect
  • FIG. 11 is a graphical illustration of the glucose measurement distribution by time of day between the SMBG (self monitored blood glucose) measurements and the
  • CGM continuously monitored glucose
  • FIG. 12 is a tabular illustration of the study subject characteristics by baseline HbAlC level in one aspect
  • FIG. 13 is a graphical illustration of the increase in the number of study subjects that achieved in-target HbAlC during the 90 day study duration in one aspect;
  • FIG. 14 is a graphical illustration of the difference between the mean glucose level of subjects with in-target HbAlC level compared to above-target HbAlC level during the study duration of 90 days in one aspect;
  • FIG. 15 is a graphical illustration of the glucose variation between subjects with in-target HbAlC level compared to above-target HbAlC level during the study duration of 90 days in one aspect
  • FIG. 16 is a graphical illustration of the average percentage HbAlC level change based on the number of times the study subjects viewed the continuously monitored glucose level in one aspect
  • FIG. 17 graphically illustrates the weekly glycemic control results based on the number of times daily the subjects viewed the real time continuously monitored glucose levels in one aspect
  • FIG. 18 is a graphical illustration of the glycemic variability measured as the standard deviation on a weekly basis of the subjects between the number of times daily the subjects viewed the real time continuously monitored glucose levels in one aspect
  • FIG. 19 is a tabular illustration of three hypothetical subjects to evaluate and modify target continuously monitored glucose levels based on HbAlC measurements, average 30 day CGM data, and percentage of duration in hypoglycemic condition over the 30 day period in one aspect;
  • FIG. 20 illustrates routines for managing diabetic conditions based on HbAlC level and mean glucose data in one aspect
  • FIG. 21 illustrates routines for managing diabetic conditions based on HbAlC level and mean glucose data in another aspect
  • FIG. 22 is a flowchart illustrating a therapy guidance routine based in part on the HbAlC level in one aspect.
  • embodiments of the present disclosure relate to methods and devices for detecting at least one analyte such as glucose in body fluid.
  • Embodiments relate to the continuous and/or automatic in vivo monitoring of the level of one or more analytes using a continuous analyte monitoring system that includes an analyte sensor at least a portion of which is to be positioned beneath a skin surface of a user for a period of time and / or the discrete monitoring of one or more analytes using an in vitro blood glucose (“BG”) meter and an analyte test strip.
  • BG in vitro blood glucose
  • Embodiments include combined or combinable devices, systems and methods and/or transferring data between an in vivo continuous system and a BG meter system.
  • Embodiments of the present disclosure include method and apparatus for receiving mean glucose value information of a patient based on a predetermined time period, receiving an HbAlC (also referred to as AlC) level of the patient, determining a correlation between the received mean glucose value information and the HbAlC level, and determining a target HbAlC level based on the determined correlation, for example, for diabetes management or physiological therapy management.
  • HbAlC also referred to as AlC
  • a method, apparatus, and system for receiving mean glucose value information of a patient based on a predetermined time period receiving a current HbAlC level of the patient and a target HbAlC level of the patient, determining a correlation between the received mean glucose value information and the retrieved current and target HbAlC levels, updating the target HbAlC level based on the determined correlation, and determining one or more parameters associated with the physiological condition of the patient based on the updated target HbAlC level.
  • embodiments include analyte monitoring devices and systems that include an analyte sensor- at least a portion of which is positionable beneath the skin of the user - for the in vivo detection, of an analyte, such as glucose, lactate, and the like, in a body fluid.
  • an analyte such as glucose, lactate, and the like
  • Embodiments include wholly implantable analyte sensors and analyte sensors in which only a portion of the sensor is positioned under the skin and a portion of the sensor resides above the skin, e.g., for contact to a transmitter, receiver, transceiver, processor, etc.
  • the sensor may be, for example, subcutaneous Iy positionable in a patient for the continuous or periodic monitoring of a level of an analyte in a patient's interstitial fluid.
  • continuous monitoring and periodic monitoring will be used interchangeably, unless noted otherwise.
  • the sensor response may be correlated and/or converted to analyte levels in blood or other fluids.
  • an analyte sensor may be positioned in contact with interstitial fluid to detect the level of glucose, which detected glucose may be used to infer the glucose level in the patient's bloodstream.
  • Analyte sensors may be insertable into a vein, artery, or other portion of the body containing fluid.
  • Embodiments of the analyte sensors of the subject disclosure may be configured for monitoring the level of the analyte over a time period which may range from minutes, hours, days, weeks, or longer.
  • analyte sensors such as glucose sensors, that are capable of in vivo detection of an analyte for about one hour or more, e.g., about a few hours or more, e.g., about a few days of more, e.g., about three or more days, e.g., about five days or more, e.g., about seven days or more, e.g., about several weeks or at least one month.
  • Future analyte levels may be predicted based on information obtained, e.g., the current analyte level at time to, the rate of change of the analyte, etc.
  • Predictive alarms may notify the user of a predicted analyte levels that may be of concern in advance of the user's analyte level reaching the future level. This provides the user an opportunity to take corrective action.
  • FIG. 1 shows a data monitoring and management system such as, for example, an analyte (e.g., glucose) monitoring system 100 in accordance with certain embodiments.
  • an analyte e.g., glucose
  • the analyte monitoring system may be configured to monitor a variety of analytes at the same time or at different times.
  • Analytes that may be monitored include, but are not limited to, acetyl choline, amylase, bilirubin, cholesterol, chorionic gonadotropin, creatine kinase (e.g., CK-
  • MB creatine, creatinine, DNA, fructosamine, glucose, glutamine, growth hormones, hormones, ketone bodies, lactate, peroxide, prostate-specific antigen, prothrombin, RNA, thyroid stimulating hormone, and troponin.
  • concentration of drugs such as, for example, antibiotics (e.g., gentamicin, vancomycin, and the like), digitoxin, digoxin, drugs of abuse, theophylline, and warfarin, may also be monitored. In those embodiments that monitor more than one analyte, the analytes may be monitored at the same or different times.
  • the analyte monitoring system 100 includes a sensor 101, a data processing unit 102 connectable to the sensor 101, and a primary receiver unit 104 which is configured to communicate with the data processing unit 102 via a communication link 103.
  • the primary receiver unit 104 may be further configured to transmit data to a data processing terminal 105 to evaluate or otherwise process or format data received by the primary receiver unit 104.
  • the data processing terminal 105 may be configured to receive data directly from the data processing unit 102 via a communication link which may optionally be configured for bi-directional communication.
  • the data processing unit 102 may include a transmitter or a transceiver to transmit and/or receive data to and/or from the primary receiver unit 104 and/or the data processing terminal 105 and/or optionally the secondary receiver unit 106.
  • an optional secondary receiver unit 106 which is operatively coupled to the communication link and configured to receive data transmitted from the data processing unit 102.
  • the secondary receiver unit 106 may be configured to communicate with the primary receiver unit 104, as well as the data processing terminal 105.
  • the secondary receiver unit 106 may be configured for bidirectional wireless communication with each of the primary receiver unit 104 and the data processing terminal 105.
  • the secondary receiver unit 106 may be a de-featured receiver as compared to the primary receiver, i.e., the secondary receiver may include a limited or minimal number of functions and features as compared with the primary receiver unit 104.
  • the secondary receiver unit 106 may include a smaller (in one or more, including all, dimensions), compact housing or embodied in a device such as a wrist watch, arm band, etc., for example.
  • the secondary receiver unit 106 may be configured with the same or substantially similar functions and features as the primary receiver unit 104.
  • the secondary receiver unit 106 may include a docking portion to be mated with a docking cradle unit for placement by, e.g., the bedside for night time monitoring, and/or a bi-directional communication device.
  • a docking cradle may recharge a powers supply.
  • analyte monitoring system 100 may include more than one sensor 101 and/or more than one data processing unit 102, and/or more than one data processing terminal 105.
  • analyte information obtained by a first positioned sensor may be employed as a comparison to analyte information obtained by a second sensor. This may be useful to confirm or validate analyte information obtained from one or both of the sensors. Such redundancy may be useful if analyte information is contemplated in critical therapy-related decisions.
  • a first sensor may be used to calibrate a second sensor.
  • the analyte monitoring system 100 may be a continuous monitoring system, or semi-continuous, or a discrete monitoring system.
  • each component may be configured to be uniquely identified by one or more of the other components in the system so that communication conflict may be readily resolved between the various components within the analyte monitoring system 100.
  • unique IDs, communication channels, and the like may be used.
  • the senor 101 is physically positioned in or on the body of a user whose analyte level is being monitored.
  • the sensor 101 may be configured to at least periodically sample the analyte level of the user and convert the sampled analyte level into a corresponding signal for transmission by the data processing unit 102.
  • the data processing unit 102 is coupleable to the sensor 101 so that both devices are positioned in or on the user's body, with at least a portion of the analyte sensor 101 positioned transcutaneously.
  • the data processing unit may include a fixation element such as adhesive or the like to secure it to the user's body.
  • a mount may include an adhesive surface.
  • the data processing unit 102 performs data processing functions, where such functions may include but are not limited to, filtering and encoding of data signals, each of which corresponds to a sampled analyte level of the user, for transmission to the primary receiver unit 104 via the communication link 103.
  • the sensor 101 or the data processing unit 102 or a combined sensor/data processing unit may be wholly implantable under the skin layer of the user.
  • the primary receiver unit 104 may include an analog interface section including and RF receiver and an antenna that is configured to communicate with the data processing unit 102 via the communication link 103, and a data processing section for processing the received data from the data processing unit 102 such as data decoding, error detection and correction, data clock generation, data bit recovery, etc., or any combination thereof.
  • the primary receiver unit 104 in certain embodiments is configured to synchronize with the data processing unit 102 to uniquely identify the data processing unit 102, based on, for example, an identification information of the data processing unit 102, and thereafter, to periodically receive signals transmitted from the data processing unit 102 associated with the monitored analyte levels detected by the sensor 101.
  • the data processing terminal 105 may include a personal computer, a portable computer such as a laptop or a handheld device (e.g., personal digital assistants (PDAs), telephone such as a cellular phone (e.g., a multimedia and Internet-enabled mobile phone such as an iPhone, Blackberry device, a Palm device or similar phone), mp3 player, pager, GPS (global positioning system) device and the like), drug delivery device, each of which may be configured for data communication with the receiver via a wired or a wireless connection. Additionally, the data processing terminal 105 may further be connected to a data network (not shown) for storing, retrieving, updating, and/or analyzing data corresponding to the detected analyte level of the user.
  • PDAs personal digital assistants
  • telephone such as a cellular phone (e.g., a multimedia and Internet-enabled mobile phone such as an iPhone, Blackberry device, a Palm device or similar phone), mp3 player, pager, GPS (global positioning system) device and the like
  • the data processing terminal 105 may include an infusion device such as an insulin infusion pump or the like, which may be configured to administer insulin to patients, and which may be configured to communicate with the primary receiver unit
  • the primary receiver unit 104 for receiving, among others, the measured analyte level.
  • the primary receiver unit 104 may be configured to integrate an infusion device therein so that the primary receiver unit 104 is configured to administer insulin (or other appropriate drug) therapy to patients, for example, for administering and modifying basal profiles, as well as for determining appropriate boluses for administration based on, among others, the detected analyte levels received from the data processing unit 102.
  • An infusion device may be an external device or an internal device (wholly implantable in a user).
  • the data processing terminal 105 which may include an insulin pump, may be configured to receive the analyte signals from the data processing unit 102, and thus, incorporate the functions of the primary receiver unit 104 including data processing for managing the patient's insulin therapy and analyte monitoring.
  • the communication link 103 as well as one or more of the other communication interfaces shown in FIG. 1, may use one or more of: an RF communication protocol, an infrared communication protocol, a Bluetooth enabled communication protocol, an 802.1 Ix wireless communication protocol, or an equivalent wireless communication protocol which would allow secure, wireless communication of several units (for example, per HIPPA requirements), while avoiding potential data collision and interference.
  • FIG. 2 shows a block diagram of an embodiment of a data processing unit of the data monitoring and detection system shown in FIG. 1.
  • User input and/or interface components may be included or a data processing unit may be free of user input and/or interface components.
  • one or more application- specific integrated circuits (ASIC) may be used to implement one or more functions or routines associated with the operations of the data processing unit (and/or receiver unit) using for example one or more state machines and buffers.
  • the sensor unit 101 (FIG. 1) includes four contacts, three of which are electrodes - work electrode (W) 210, reference electrode (R) 212, and counter electrode (C) 213, each operatively coupled to the analog interface 201 of the data processing unit 102.
  • This embodiment also shows optional guard contact (G) 211. Fewer or greater electrodes may be employed.
  • the counter and reference electrode functions may be served by a single counter/reference electrode, there may be more than one working electrode and/or reference electrode and/or counter electrode, etc.
  • FIG. 3 is a block diagram of an embodiment of a receiver/monitor unit such as the primary receiver unit 104 of the data monitoring and management system shown in FIG. 1.
  • the primary receiver unit 104 includes one or more of: a blood glucose test strip interface 301, an RF receiver 302, an input 303, a temperature detection section 304, and a clock 305, each of which is operatively coupled to a processing and storage section 307.
  • the primary receiver unit 104 also includes a power supply 306 operatively coupled to a power conversion and monitoring section 308. Further, the power conversion and monitoring section 308 is also coupled to the receiver processor
  • the test strip interface 301 includes a glucose level testing portion to receive a blood (or other body fluid sample) glucose test or information related thereto.
  • the interface may include a test strip port to receive a glucose test strip. The device may determine the glucose level of the test strip, and optionally display (or otherwise notice) the glucose level on the output 310 of the primary receiver unit 104.
  • test strips that only require a very small amount (e.g., one microliter or less, e.g., 0.5 microliter or less, e.g., 0.1 microliter or less), of applied sample to the strip in order to obtain accurate glucose information, e.g. FreeStyle ® blood glucose test strips from
  • Glucose information obtained by the in vitro glucose testing device may be used for a variety of purposes, computations, and the like.
  • the information may be used to calibrate sensor 101, confirm results of the sensor 101 to increase the confidence thereof (e.g., in instances in which information obtained by sensor 101 is employed in therapy related decisions).
  • the data processing unit 102 and/or the primary receiver unit 104 and/or the secondary receiver unit 105, and/or the data processing terminal/infusion section 105 may be configured to receive the blood glucose value wirelessly over a communication link from, for example, a blood glucose meter.
  • FIG. 1 may manually input the blood glucose value using, for example, a user interface (for example, a keyboard, keypad, voice commands, and the like) incorporated in the one or more of the data processing unit 102, the primary receiver unit 104, secondary receiver unit 105, or the data processing terminal/infusion section 105.
  • a user interface for example, a keyboard, keypad, voice commands, and the like
  • FIG. 4 schematically shows an embodiment of an analyte sensor in accordance with the present disclosure.
  • This sensor embodiment includes electrodes 401, 402 and 403 on a base 404. Electrodes (and/or other features) may be applied or otherwise processed using any suitable technology, e.g., chemical vapor deposition (CVD), physical vapor deposition, sputtering, reactive sputtering, printing, coating, ablating
  • CVD chemical vapor deposition
  • sputtering reactive sputtering
  • printing e.g., coating, ablating
  • Materials include but are not limited to aluminum, carbon (such as graphite), cobalt, copper, gallium, gold, indium, iridium, iron, lead, magnesium, mercury (as an amalgam), nickel, niobium, osmium, palladium, platinum, rhenium, rhodium, selenium, silicon (e.g., doped polycrystalline silicon), silver, tantalum, tin, titanium, tungsten, uranium, vanadium, zinc, zirconium, mixtures thereof, and alloys, oxides, or metallic compounds of these elements.
  • the sensor may be wholly implantable in a user or may be configured so that only a portion is positioned within (internal) a user and another portion outside (external) a user.
  • the sensor 400 may include a portion positionable above a surface of the skin 410, and a portion positioned below the skin.
  • the external portion may include contacts (connected to respective electrodes of the second portion by traces) to connect to another device also external to the user such as a transmitter unit. While the embodiment of FIG.
  • FIG. 4 shows three electrodes side-by-side on the same surface of base 404, other configurations are contemplated, e.g., fewer or greater electrodes, some or all electrodes on different surfaces of the base or present on another base, some or all electrodes stacked together, electrodes of differing materials and dimensions, etc.
  • FIG. 5 A shows a perspective view of an embodiment of an electrochemical analyte sensor 500 having a first portion (which in this embodiment may be characterized as a major portion) positionable above a surface of the skin 510, and a second portion (which in this embodiment may be characterized as a minor portion) that includes an insertion tip 530 positionable below the skin, e.g., penetrating through the skin and into, e.g., the subcutaneous space 520, in contact with the user's biofluid such as interstitial fluid.
  • Contact portions of a working electrode 501, a reference electrode 502, and a counter electrode 503 are positioned on the portion of the sensor 500 situated above the skin surface 510.
  • Working electrode 501, a reference electrode 502, and a counter electrode 503 are shown at the second section and particularly at the insertion tip 530. Traces may be provided from the electrode at the tip to the contact, as shown in FIG. 5 A. It is to be understood that greater or fewer electrodes may be provided on a sensor.
  • a sensor may include more than one working electrode and/or the counter and reference electrodes may be a single counter/reference electrode, etc.
  • FIG. 5B shows a cross sectional view of a portion of the sensor 500 of FIG. 5A.
  • the electrodes 510, 502 and 503, of the sensor 500 as well as the substrate and the dielectric layers are provided in a layered configuration or construction.
  • the sensor 500 (such as the sensor unit 101 FIG. 1), includes a substrate layer 504, and a first conducting layer 501 such as carbon, gold, etc., disposed on at least a portion of the substrate layer 504, and which may provide the working electrode. Also shown disposed on at least a portion of the first conducting layer 501 is a sensing layer 508.
  • a first insulation layer such as a first dielectric layer 505 is disposed or layered on at least a portion of the first conducting layer 501, and further, a second conducting layer 509 may be disposed or stacked on top of at least a portion of the first insulation layer (or dielectric layer) 505.
  • the second conducting layer 509 may provide the reference electrode 502, and in one aspect, may include a layer of silver/silver chloride (Ag/ AgCl), gold, etc.
  • a second insulation layer 506 such as a dielectric layer in one embodiment may be disposed or layered on at least a portion of the second conducting layer 509. Further, a third conducting layer 503 may provide the counter electrode 503. It may be disposed on at least a portion of the second insulation layer 506. Finally, a third insulation layer may be disposed or layered on at least a portion of the third conducting layer 503. In this manner, the sensor 500 may be layered such that at least a portion of each of the conducting layers is separated by a respective insulation layer (for example, a dielectric layer).
  • the embodiment of FIGS. 5A and 5B show the layers having different lengths. Some or all of the layers may have the same or different lengths and/or widths.
  • some or all of the electrodes 501, 502, 503 may be provided on the same side of the substrate 504 in the layered construction as described above, or alternatively, may be provided in a co-planar manner such that two or more electrodes may be positioned on the same plane (e.g., side -by side (e.g., parallel) or angled relative to each other) on the substrate 504.
  • co-planar electrodes may include a suitable spacing there between and/or include dielectric material or insulation material disposed between the conducting layers/electrodes.
  • one or more of the electrodes 501, 502, 503 may be disposed on opposing sides of the substrate 504.
  • contact pads may be one the same or different sides of the substrate.
  • an electrode may be on a first side and its respective contact may be on a second side, e.g., a trace connecting the electrode and the contact may traverse through the substrate.
  • analyte sensors may include an analyte-responsive enzyme to provide a sensing component or sensing layer. Some analytes, such as oxygen, can be directly electrooxidized or electroreduced on a sensor, and more specifically at least on a working electrode of a sensor. Other analytes, such as glucose and lactate, require the presence of at least one electron transfer agent and/or at least one catalyst to facilitate the electrooxidation or electroreduction of the analyte.
  • each working electrode includes a sensing layer (see for example sensing layer 408 of FIG. 5B) proximate to or on a surface of a working electrode.
  • a sensing layer is formed near or on only a small portion of at least a working electrode.
  • the sensing layer includes one or more components designed to facilitate the electrochemical oxidation or reduction of the analyte.
  • the sensing layer may include, for example, a catalyst to catalyze a reaction of the analyte and produce a response at the working electrode, an electron transfer agent to transfer electrons between the analyte and the working electrode (or other component), or both.
  • the sensing layer is deposited on the conductive material of a working electrode.
  • the sensing layer may extend beyond the conductive material of the working electrode.
  • the sensing layer may also extend over other electrodes, e.g., over the counter electrode and/or reference electrode (or counter/reference is provided).
  • a sensing layer that is in direct contact with the working electrode may contain an electron transfer agent to transfer electrons directly or indirectly between the analyte and the working electrode, and/or a catalyst to facilitate a reaction of the analyte.
  • a glucose, lactate, or oxygen electrode may be formed having a sensing layer which contains a catalyst, such as glucose oxidase, lactate oxidase, or laccase, respectively, and an electron transfer agent that facilitates the electrooxidation of the glucose, lactate, or oxygen, respectively.
  • the sensing layer is not deposited directly on the working electrode. Instead, the sensing layer 64 may be spaced apart from the working electrode, and separated from the working electrode, e.g., by a separation layer.
  • a separation layer may include one or more membranes or films or a physical distance. In addition to separating the working electrode from the sensing layer the separation layer may also act as a mass transport limiting layer and/or an interferent eliminating layer and/or a biocompatible layer.
  • one or more of the working electrodes may not have a corresponding sensing layer, or may have a sensing layer which does not contain one or more components (e.g., an electron transfer agent and/or catalyst) needed to electrolyze the analyte.
  • the signal at this working electrode may correspond to background signal which may be removed from the analyte signal obtained from one or more other working electrodes that are associated with fully- functional sensing layers by, for example, subtracting the signal.
  • the sensing layer includes one or more electron transfer agents.
  • Electron transfer agents that may be employed are electroreducible and electrooxidizable ions or molecules having redox potentials that are a few hundred millivolts above or below the redox potential of the standard calomel electrode (SCE).
  • the electron transfer agent may be organic, organometallic, or inorganic. Examples of organic redox species are quinones and species that in their oxidized state have quinoid structures, such as Nile blue and indophenol. Examples of organometallic redox species are metallocenes such as ferrocene. Examples of inorganic redox species are hexacyanoferrate (III), ruthenium hexamine etc.
  • electron transfer agents have structures or charges which prevent or substantially reduce the diffusional loss of the electron transfer agent during the period of time that the sample is being analyzed.
  • electron transfer agents include but are not limited to a redox species, e.g., bound to a polymer which can in turn be disposed on or near the working electrode.
  • the bond between the redox species and the polymer may be covalent, coordinative, or ionic.
  • the redox species is a transition metal compound or complex, e.g., osmium, ruthenium, iron, and cobalt compounds or complexes. It will be recognized that many redox species described for use with a polymeric component may also be used, without a polymeric component.
  • polymeric electron transfer agent contains a redox species covalently bound in a polymeric composition.
  • An example of this type of mediator is poly(vinylferrocene).
  • Another type of electron transfer agent contains an ionically- bound redox species.
  • This type of mediator may include a charged polymer coupled to an oppositely charged redox species.
  • Examples of this type of mediator include a negatively charged polymer coupled to a positively charged redox species such as an osmium or ruthenium polypyridyl cation.
  • an ionically-bound mediator is a positively charged polymer such as quaternized poly(4-vinyl pyridine) or poly(l -vinyl imidazole) coupled to a negatively charged redox species such as ferricyanide or ferrocyanide.
  • electron transfer agents include a redox species coordinatively bound to a polymer.
  • the mediator may be formed by coordination of an osmium or cobalt 2,2'-bipyridyl complex to poly(l-vinyl imidazole) or poly(4-vinyl pyridine).
  • Suitable electron transfer agents are osmium transition metal complexes with one or more ligands, each ligand having a nitrogen-containing heterocycle such as 2,2'-bipyridine, 1,10-phenanthroline, 1 -methyl, 2-pyridyl biimidazole, or derivatives thereof.
  • the electron transfer agents may also have one or more ligands covalently bound in a polymer, each ligand having at least one nitrogen-containing heterocycle, such as pyridine, imidazole, or derivatives thereof.
  • an electron transfer agent includes (a) a polymer or copolymer having pyridine or imidazole functional groups and (b) osmium cations complexed with two ligands, each ligand containing 2,2'-bipyridine, 1,10-phenanthroline, or derivatives thereof, the two ligands not necessarily being the same.
  • Some derivatives of 2,2'-bipyridine for complexation with the osmium cation include but are not limited to 4,4'-dimethyl-2,2'-bipyridine and mono-, di-, and polyalkoxy-2,2'-bipyridines, such as 4,4'-dimethoxy-2,2'- bipyridine.
  • 1,10-phenanthroline for complexation with the osmium cation include but are not limited to 4, 7-dimethyl- 1,10-phenanthroline and mono, di-, and polyalkoxy-l,10-phenanthro lines, such as 4, 7-dimethoxy- 1,10-phenanthroline.
  • Polymers for complexation with the osmium cation include but are not limited to polymers and copolymers of poly(l -vinyl imidazole) (referred to as "PVI”) and poly(4-vinyl pyridine) (referred to as "PVP").
  • Suitable copolymer substituents of poly(l -vinyl imidazole) include acrylonitrile, acrylamide, and substituted or quaternized N-vinyl imidazole, e.g., electron transfer agents with osmium complexed to a polymer or copolymer of poly(l -vinyl imidazole).
  • Embodiments may employ electron transfer agents having a redox potential ranging from about -200 mV to about +200 mV versus the standard calomel electrode (SCE).
  • the sensing layer may also include a catalyst which is capable of catalyzing a reaction of the analyte.
  • the catalyst may also, in some embodiments, act as an electron transfer agent.
  • One example of a suitable catalyst is an enzyme which catalyzes a reaction of the analyte.
  • a catalyst such as a glucose oxidase, glucose dehydrogenase (e.g., pyrroloquinoline quinone (PQQ), dependent glucose dehydrogenase, flavine adenine dinucleotide (FAD), or nicotinamide adenine dinucleotide (NAD) dependent glucose dehydrogenase), may be used when the analyte of interest is glucose.
  • PQQ pyrroloquinoline quinone
  • dependent glucose dehydrogenase e.g., flavine adenine dinucleotide (FAD), or nicotinamide adenine dinucleotide (NAD) dependent glucose dehydrogenase
  • a lactate oxidase or lactate dehydrogenase may be used when the analyte of interest is lactate.
  • Laccase may be used when the analyte of interest is oxygen or when oxygen is generated or consumed in response to a reaction of the
  • the sensing layer may also include a catalyst which is capable of catalyzing a reaction of the analyte.
  • the catalyst may also, in some embodiments, act as an electron transfer agent.
  • One example of a suitable catalyst is an enzyme which catalyzes a reaction of the analyte.
  • a catalyst such as a glucose oxidase, glucose dehydrogenase (e.g., pyrroloquinoline quinone (PQQ), dependent glucose dehydrogenase or oligosaccharide dehydrogenase, flavine adenine dinucleotide (FAD) dependent glucose dehydrogenase, nicotinamide adenine dinucleotide (NAD) dependent glucose dehydrogenase), may be used when the analyte of interest is glucose.
  • PQQ glucose dehydrogenase
  • FAD flavine adenine dinucleotide
  • NAD nicotinamide adenine dinucleotide dependent glucose dehydrogenase
  • a lactate oxidase or lactate dehydrogenase may be used when the analyte of interest is lactate.
  • Laccase may be used when the analyte of interest is oxygen or when oxygen is generated or consumed in response to a reaction of the analyte.
  • a catalyst may be attached to a polymer, cross linking the catalyst with another electron transfer agent (which, as described above, may be polymeric.
  • a second catalyst may also be used in certain embodiments. This second catalyst may be used to catalyze a reaction of a product compound resulting from the catalyzed reaction of the analyte. The second catalyst may operate with an electron transfer agent to electrolyze the product compound to generate a signal at the working electrode.
  • a second catalyst may be provided in an interferent- eliminating layer to catalyze reactions that remove interferents.
  • Certain embodiments include a Wired EnzymeTM sensing layer (Abbott Diabetes Care) that works at a gentle oxidizing potential, e.g., a potential of about +40 mV.
  • This sensing layer uses an osmium (Os) -based mediator designed for low potential operation and is stably anchored in a polymeric layer.
  • the sensing element is redox active component that includes (1) Osmium-based mediator molecules attached by stable (bidente) ligands anchored to a polymeric backbone, and (2) glucose oxidase enzyme molecules. These two constituents are crosslinked together.
  • a mass transport limiting layer (not shown), e.g., an analyte flux modulating layer, may be included with the sensor to act as a diffusion-limiting barrier to reduce the rate of mass transport of the analyte, for example, glucose or lactate, into the region around the working electrodes.
  • the mass transport limiting layers are useful in limiting the flux of an analyte to a working electrode in an electrochemical sensor so that the sensor is linearly responsive over a large range of analyte concentrations and is easily calibrated.
  • Mass transport limiting layers may include polymers and may be biocompatible.
  • a mass transport limiting layer may provide many functions, e.g., biocompatibility and/or interferent-eliminating, etc.
  • a mass transport limiting layer is a membrane composed of crosslinked polymers containing heterocyclic nitrogen groups, such as polymers of polyvinylpyridine and polyvinylimidazole.
  • Embodiments also include membranes that are made of a polyurethane, or polyether urethane, or chemically related material, or membranes that are made of silicone, and the like.
  • a membrane may be formed by crosslinking in situ a polymer, modified with a zwitterionic moiety, a non-pyridine copolymer component, and optionally another moiety that is either hydrophilic or hydrophobic, and/or has other desirable properties, in an alcohol-buffer solution.
  • the modified polymer may be made from a precursor polymer containing heterocyclic nitrogen groups.
  • a precursor polymer may be polyvinylpyridine or polyvinylimidazole.
  • hydrophilic or hydrophobic modifiers may be used to "fine-tune" the permeability of the resulting membrane to an analyte of interest.
  • Optional hydrophilic modifiers such as poly(ethylene glycol), hydroxyl or polyhydroxyl modifiers, may be used to enhance the biocompatibility of the polymer or the resulting membrane.
  • a membrane may be formed in situ by applying an alcohol-buffer solution of a crosslinker and a modified polymer over an enzyme-containing sensing layer and allowing the solution to cure for about one to two days or other appropriate time period.
  • the crosslinker-polymer solution may be applied to the sensing layer by placing a droplet or droplets of the solution on the sensor, by dipping the sensor into the solution, or the like.
  • the thickness of the membrane is controlled by the concentration of the solution, by the number of droplets of the solution applied, by the number of times the sensor is dipped in the solution, or by any combination of these factors.
  • a membrane applied in this manner may have any combination of the following functions: (1) mass transport limitation, i.e., reduction of the flux of analyte that can reach the sensing layer, (2) biocompatibility enhancement, or (3) interferent reduction.
  • the electrochemical sensors may employ any suitable measurement technique.
  • sensing systems may be optical, colorimetric, and the like.
  • the sensing system detects hydrogen peroxide to infer glucose levels.
  • a hydrogen peroxide-detecting sensor may be constructed in which a sensing layer includes enzyme such as glucose oxides, glucose dehydrogensae, or the like, and is positioned proximate to the working electrode.
  • the sending layer may be covered by a membrane that is selectively permeable to glucose. Once the glucose passes through the membrane, it is oxidized by the enzyme and reduced glucose oxidase can then be oxidized by reacting with molecular oxygen to produce hydrogen peroxide.
  • Certain embodiments include a hydrogen peroxide-detecting sensor constructed from a sensing layer prepared by crosslinking two components together, for example: (1) a redox compound such as a redox polymer containing pendent Os polypyridyl complexes with oxidation potentials of about +200 mV vs. SCE, and (2) periodate oxidized horseradish peroxidase (HRP).
  • a redox compound such as a redox polymer containing pendent Os polypyridyl complexes with oxidation potentials of about +200 mV vs. SCE
  • HRP horseradish peroxidase
  • a potentiometric sensor can be constructed as follows.
  • a glucose-sensing layer is constructed by crosslinking together (1) a redox polymer containing pendent Os polypyridyl complexes with oxidation potentials from about - 200 mV to +200 mV vs. SCE, and (2) glucose oxidase.
  • This sensor can then be used in a potentiometric mode, by exposing the sensor to a glucose containing solution, under conditions of zero current flow, and allowing the ratio of reduced/oxidized Os to reach an equilibrium value.
  • the reduced/oxidized Os ratio varies in a reproducible way with the glucose concentration, and will cause the electrode's potential to vary in a similar way.
  • a sensor may also include an active agent such as an anticlotting and/or antiglycolytic agent(s) disposed on at least a portion a sensor that is positioned in a user.
  • An anticlotting agent may reduce or eliminate the clotting of blood or other body fluid around the sensor, particularly after insertion of the sensor.
  • useful anticlotting agents include heparin and tissue plasminogen activator (TPA), as well as other known anticlotting agents.
  • Embodiments may include an antiglycolytic agent or precursor thereof. Examples of antiglycolytic agents are glyceraldehyde, fluoride ion, and mannose.
  • Sensors may be configured to require no system calibration or no user calibration.
  • a sensor may be factory calibrated and need not require further calibrating.
  • calibration may be required, but may be done without user intervention, i.e., may be automatic.
  • the calibration may be according to a predetermined schedule or may be dynamic, i.e., the time for which may be determined by the system on a real-time basis according to various factors, such as but not limited to glucose concentration and/or temperature and/or rate of change of glucose, etc.
  • Calibration may be accomplished using an in vitro test strip (or other reference), e.g., a small sample test strip such as a test strip that requires less than about 1 microliter of sample (for example FreeStyle ® blood glucose monitoring test strips from Abbott Diabetes Care). For example, test strips that require less than about 1 nano liter of sample may be used.
  • a sensor may be calibrated using only one sample of body fluid per calibration event. For example, a user need only lance a body part one time to obtain sample for a calibration event (e.g., for a test strip), or may lance more than one time within a short period of time if an insufficient volume of sample is firstly obtained.
  • Embodiments include obtaining and using multiple samples of body fluid for a given calibration event, where glucose values of each sample are substantially similar. Data obtained from a given calibration event may be used independently to calibrate or combined with data obtained from previous calibration events, e.g., averaged including weighted averaged, etc., to calibrate. In certain embodiments, a system need only be calibrated once by a user, where recalibration of the system is not required. Analyte systems may include an optional alarm system that, e.g., based on information from a processor, warns the patient of a potentially detrimental condition of the analyte.
  • an alarm system may warn a user of conditions such as hypoglycemia and/or hyperglycemia and/or impending hypoglycemia, and/or impending hyperglycemia.
  • An alarm system may be triggered when analyte levels approach, reach or exceed a threshold value.
  • An alarm system may also, or alternatively, be activated when the rate of change, or acceleration of the rate of change, in analyte level increase or decrease approaches, reaches or exceeds a threshold rate or acceleration.
  • a system may also include system alarms that notify a user of system information such as battery condition, calibration, sensor dislodgment, sensor malfunction, etc. Alarms may be, for example, auditory and/or visual. Other sensory-stimulating alarm systems may be used including alarm systems which heat, cool, vibrate, or produce a mild electrical shock when activated.
  • the embodiments of the present disclosure also include sensors used in sensor-based drug delivery systems.
  • the system may provide a drug to counteract the high or low level of the analyte in response to the signals from one or more sensors.
  • the system may monitor the drug concentration to ensure that the drug remains within a desired therapeutic range.
  • the drug delivery system may include one or more (e.g., two or more) sensors, a processing unit such as a transmitter, a receiver/display unit, and a drug administration system. In some cases, some or all components may be integrated in a single unit.
  • a sensor-based drug delivery system may use data from the one or more sensors to provide necessary input for a control algorithm/mechanism to adjust the administration of drugs, e.g., automatically or semi-automatically.
  • a glucose sensor may be used to control and adjust the administration of insulin from an external or implanted insulin pump.
  • HbAlC is the standard metric for determining an individual's glycemic control. Studies have recently derived relationships of HbAlC to mean blood glucose levels. The advent of continuous glucose monitoring (CGM) has enabled accurate and continuous measurements of mean glucose levels over extended periods of time.
  • CGM continuous glucose monitoring
  • mean glucose values may be associated or correlated with the HbAlC levels. For example, a slope of 36 mg/dL per 1% HbAlC illustrates the relationship between the regression analysis relating HbAlC level to mean glucose values. Further, a lower slope of approximately 18 mg/dL may indicate the relationship between HbAlC level and mean glucose values.
  • HbAlC level variability may exist between diabetic patients as pertains to the relationship between the HbAlC level and mean glucose values, indicating a potentially individualized characteristic of the rate of protein glycation that may effect long term complications of poorly controlled diabetic condition.
  • Other variables such as race and ethnicity also may have effect in the HbAlC level adjusted for glycemic indices.
  • embodiments of the present disclosure include improvement in the HbAlC level estimation with the knowledge or information of the patient's individualized relationship between HbAlC level and the mean glucose values.
  • a diabetic patient or a subject with a lower slope may be able to achieve a greater improvement in HbAlC level for a given decrease in average glucose levels, as compared with a patient with a higher slope.
  • the patient with the lower slope may be able to achieve a reduced risk of chronic diabetic complications by lower HbAlC level with a minimal increase in the risk of potentially severe hypoglycemia (due to a relatively modest reduction in the average glucose values in view of their lower slope).
  • a physician or a care provider in one aspect may determine a suitable glycemic targets for the particular patient such that the calculated reduction in the HbAlC level may be attained while minimizing the risk of severe hypoglycemia.
  • a blood glucose meter or monitor with sufficient data capacity for storing and processing glucose values, or a data processing terminal 105 in the analyte monitoring system 100 (FIG. 1), a blood glucose meter or monitor with sufficient data capacity for storing and processing glucose values, or a data processing terminal 105 (FIG.
  • HbAlC measurement may be obtained either manually entered or downloaded from the patient's medical records, and an average glucose level is calculated over a predetermined time period (such as 30 days, 45 days, 60 days 90 days and so on).
  • a patient's individual relationship between average glucose/HbAIC may be determined.
  • the determined individual relationship may be represented or output as a slope (lower slope or higher slope in graphical representation, for example), based upon a line fit to two or more determinations of average glucose and HbAlC, for example.
  • the individualized relationship may be based upon a single assessment of average glucose level and HbAlC and an intercept value, which may correspond to an HbAlC of zero at zero mean glucose level.
  • the physician or the health care provider may to determine appropriate or suitable individualized glycemic targets to achieve the desired reductions in HbAlC without the undesired risk of severe hypoglycemia.
  • the analysis may be repeated one or more times (for example, quarterly with each regularly scheduled HbAlC test) to update the glycemic targets so as to optimize therapy management and treatment, and to account for or factor in any intra-person variability.
  • glycemic targets based upon the relationship between the mean glucose values (as may be determined using a continuous glucose monitoring system or a discrete in vitro blood glucose meter tests) and their HbAlC level, and a determination of an acceptable level of risk of severe hypoglycemia.
  • embodiments of the present disclosure provide individualized glycemic targets to be determined for a particular patient based upon their individualized rate of protein glycation, measured by the relationship between the mean glucose values and the HbAlC levels, such that the physician or the care provider, or the analyte monitoring system including data management software, for example, may determine the glycemic targets to achieve the desired reduction in HbAlC level without the unnecessary risk for hypoglycemic condition.
  • embodiments of the present disclosure may be used to improve the estimation of subsequent HbAlC values based upon measured or monitored glucose values of a patient. In this manner the HbAlC level estimation may be improved by using the patient's individualized relationship between prior or past HbAlC levels, and means glucose values to more accurately predict or estimate current HbAlC levels.
  • the HbAlC level estimation may be improved or enhanced based on a predetermined individualized relationship between a patient's average glucose values and their HbAlC and the current mean glucose level.
  • SMBG mean glucose level
  • HbAlC HbAlC
  • ADA Diabetes Association
  • the low slope of less than 1 for mean CGM data compared to mean SMBG levels may indicate the measurement selection bias of SMBG levels before and after meals and in response to CGM system alarms or notification. This bias did not greatly affect the relationship to HbAlC levels. However, mean CGM data correlated more closely to the HbAlC levels and thus a better indicator of the HbAlC level.
  • That the CGM data had an r 2 (Pearson's correlation coefficient) value of only 0.52 indicates that individual differences in rates of protein glycation at a given blood glucose concentration may be an important factor when addressing glycemic control. The individual differences may be relevant in determining risk of future diabetic complications, and may suggest personalized goals of mean glucose for a given HbAlC target.
  • FIG. 6 provides a tabular illustration of the demographic and characteristics of participants in the 90 days continuous glucose monitoring system use study in one aspect. As can be seen from the table shown in
  • FIG. 6 the 88 subjects for the 90 day study were selected to cover a wide range of characteristics typical for the general population of people with diabetic conditions, and who generally have a controlled diabetic condition, with a maximum HbAlC level of 9.1%.
  • FIG. 7 is a chart illustrating the relationship between the 90 day mean continuously monitored glucose level and the mean 90 day discrete blood glucose test results compared with the HbAlC level in one aspect. Referring to FIG. 7, it can be seen that the CGM data and the SMBG readings were observed to have similar relationship to HbAlC levels, despite the less frequency of the SMBG readings.
  • the level of the relationship to the HbAlC levels are relatively moderate, indicating other variables which may affect the relationship, including, for example, genetic factors that may impact the glycation of the hemoglobin molecule in the presence of glucose, or individuals may have longer or shorter average erythrocyte lifespans.
  • FIG. 7 provides a graphical illustration of the individual rates of glycation distribution in one aspect. Referring to FIG. 7
  • the rate of glycation including the 90 day mean glucose value divided by the HbAlC level characterizes an individual's sensitivity to changes in HbAlC level at a given blood glucose concentration.
  • FIG. 8 illustrates the distribution of rates of glycation for the subjects in the study. As shown, approximately 15% of the participants may be considered "sensitive glycators" with a glycation ratio of approximately 19 or less. These individuals would need to maintain their blood glucose level to a lower-than-average value to maintain relatively the same HbAlC level as other individuals. For example, if the glycation ratio is 15, than the mean blood glucose level must be kept at approximately 75mg/dL to expect and HbAlC level of approximately 5%.
  • approximately 22% of the study participants may be considered "insensitive glycators" with a glycation ratio of approximately 23 or more. That is, these insensitive glycators may keep their blood glucose higher-than-average level and maintain approximately the same HbAlC level as other individuals. For example, if the glycation ratio is 25, then the mean blood glucose level can be maintained at approximately 125 mg/dL to expect an HbAlC level of approximately 5%.
  • FIG. 9 provides a graphical illustration of the slope and correlation of the continuously monitored glucose level to the HbAlC level on a weekly basis in one aspect.
  • HbAlC is considered to be weighted average of blood glucose levels for the 90 day period based on the average lifespan of erythrocytes.
  • the weighted average may or may not be a linear relationship. More recent blood glucose levels may influence the HbAlC level more strongly (thus weighting more heavily) than the more distant (in time) blood glucose levels.
  • FIG. 9 illustrates the Pearson's correlation (r 2 ) and linear regression slope for each of the 12 weeks prior to the HbAlC measurement.
  • the horizontal lines as shown in the Figure illustrate the values when all weeks in the study are pooled together. From FIG. 9, it can be seen that the more recent weeks (for example, weeks 6 to 13) have a stronger influence on HbAlC level (that is, a having a higher correlation and slope) than the more distant weeks (for example weeks 1 to 5).
  • FIG. 10 is a graphical illustration of the frequency of the obtained glucose levels between the SMBG (self monitored blood glucose) measurements and the
  • CGM continuously monitored glucose
  • SMBG episodic measurements
  • CGM continuous measurements
  • the frequency of the glucose levels per day is shown for the two measurements/.
  • 5.4 SMBG measurements were performed per day (e.g., once per 4.4 hours) compared to 121.5 CGM measurements per day (once per 12 minutes).
  • FIG. 11 is a graphical illustration of the glucose measurement distribution by time of day between the SMBG (self monitored blood glucose) measurements and the CGM (continuously monitored glucose) measurement in one aspect. As shown in FIG. 11, on average, it can be seen that the SMBG measurements were performed during the day, with spikes near typical meal times, as compared to substantially steady continuous CGM measurements.
  • SMBG infrequent and inconsistently timed glucose measurements
  • real-time monitored CGM data may significantly improve the management of diabetes through the availability of glucose values, trend indicators, and alarms/alerts, it may be also used for the determination of mean glucose level and for the prediction of HbAlC level. These metrics have been shown to track long-term complications and are essential for physiological condition or therapy management.
  • Improved understanding of inter- and intra-individual variation in the relationship between mean glucose level and HbAlC level may be useful in the determination of glucose targets designed to optimize both the reduction in an individual's risk of the long-term complications of diabetes and their short-term risk of hypoglycemia.
  • patients with different relationships between mean glucose and HbAlC may be able to achieve similar reductions in the risk of microvascular complications of diabetes with markedly different decreases in mean glucose, with those patients with the lowest ratios of mean glucose to HbAlC experiencing the least risk of hypoglycemia.
  • FIG. 12 is a tabular illustration of the study subject characteristics by baseline HbAlC level in one aspect. It can be seen form FIG. 12 that the participants of the study had an initial in-target (defined by the
  • FIG. 13 is a graphical illustration of the increase in the number of study subjects that achieved in-target HbAlC during the 90 day study duration in one aspect. Referring to FIG. 13, it can be observed that during the 90 day study duration, the number of participants able to achieve an in-target HbAlC level increased from approximately 40% to approximately 57%.
  • FIG. 13 is a graphical illustration of the increase in the number of study subjects that achieved in-target HbAlC during the 90 day study duration in one aspect. Referring to FIG. 13, it can be observed that during the 90 day study duration, the number of participants able to achieve an in-target HbAlC level increased from approximately 40% to approximately 57%.
  • FIG. 14 is a graphical illustration of the difference between the mean glucose levels of subjects with in-target HbAlC level (1420) compared to above-target HbAlC level (1410) during the study duration of 90 days in one aspect.
  • the participants with the initial in-target HbAlC level (1420) had a lower mean glucose level than those with an initial above-target HbAlC level (1410).
  • the weekly mean glucose level remained relatively stable for these participants with the initial in-target HbAlC level (1420), as compared with the participants with an above target HbAlC level (1410) whose weekly mean glucose level was relatively higher and increased towards the end of the 90 day study period.
  • FIG. 14 is a graphical illustration of the difference between the mean glucose levels of subjects with in-target HbAlC level (1420) compared to above-target HbAlC level (1410) during the study duration of 90 days in one aspect.
  • FIG. 15 is a graphical illustration of the glucose variation between subjects with in-target HbAlC level (1520)compared to above-target HbAlC level (1510) during the study duration of 90 days in one aspect. It can be seen from FIG. 15 that during the study duration, the participants who had initial in-target HbAlC level (1520) had a lower glucose variation (measured by standard deviation per week), than those with an above-target HbAlC level (1510), and the glucose values remained relatively stable over study period.
  • FIG. 16 is a graphical illustration of the average percentage HbAlC level change based on the number of times the study subjects viewed the continuously monitored glucose level in one aspect. It can be seen from FIG. 16 that the average change in HbAlC level during the 90 day study period for the participants as correlated with the number of times per day the participants reported viewing or seeing the real time CGM data display. It can be observed that the participants that were viewing the monitored glucose levels had their HbAlC levels reduced relatively more than those who viewed the monitored glucose levels less frequently.
  • FIG. 17 graphically illustrates the weekly glycemic control results based on the number of times daily the subjects viewed the real time continuously monitored glucose levels in one aspect.
  • the graphical illustration provides the glycemic control (i.e., measured as the percentage of time between 70 to 180 mg/dL) per week for participants associated with the number of times per day the participants reported viewing or looking at the continuously monitored real time glucose (CGM) data.
  • CGM real time glucose
  • FIG. 18 is a graphical illustration of the glycemic variability measured as the standard deviation on a weekly basis of the subjects between the number of times daily the subjects viewed the real time continuously monitored glucose levels in one aspect. Again, it can be observed that based on the glycemic variability per week associated with the number of times per day they reported viewing or looking at the CGM data as shown in FIG. 18, the participants that viewed the real time glucose data less frequently had degraded glycemic variability (1830), compared with the participants that viewed the glucose data more frequently (1810, 1820) .
  • FIG. 19 is a tabular illustration of three hypothetical subjects to evaluate and modify target continuously monitored glucose levels based on HbAlC measurements, average 30 day CGM data, and percentage of duration in hypoglycemic condition
  • patient 1 may be considered a "sensitive glycator" (see, e.g., FIG. 8) with a glycability ratio of 17.
  • a therapy recommendation or compromise may include a target predicted HbAlC level of 6.5% which, for the sensitive glycator may translate to an average CGM level of 113 mg/dL.
  • patient 2 profile is similar to patient 1, but is note quite as sensitive a glycator , and thus, the CGM target may be at 118mg/dL, with a predicted or anticipated HbAlC to 6.0% (which is considered to be still "in-target").
  • Patient 3 as shown may be considered an "insensitive glycator" and has a very low rate of hypoglycemia.
  • the recommended therapy management may include a more controlled HbAlC level of
  • Patient A may begin at an HbAlC of 8.0%. He may be knowledgeable about food-insulin balancing and mealtime glucose corrections, but still feels overwhelmed by mealtime decisions. Looking at HbAlC and CGM data summary, Patient A's health care provider (HCP) sees that at meal times he has the following characteristics:
  • embodiments of the present disclosure provide determination of individualized HbAlC target levels based on mean glucose values as well as other parameters such as the patient's prior HbAlC levels (determined based on a laboratory result or by other ways) to improve glycemic control.
  • other metrics or parameters may be factored into the determination of the individualized HbAlC target level such as, for example, conditions that may be relevant to the patient's hypoglycemic conditions including patient's age, hypoglycemia unawareness, whether the patient is living alone or in assisted care, or with others, history hypoglycemia, whether the patient is an insulin pump user, or is under insulin or other medication therapy, the patient's activity levels and the like.
  • other parameters may also include different or variable weighing functions to determine the mean glucose values, based on, for example, the time of day, or time weighted measures, and the like.
  • the determination of the individualized HbAlC target level may also include patient specific relationship between HbAlC and mean glucose values, including the rate of glycation, erythrocyte lifespan, among others.
  • embodiments may include weighing functions or parameters based on the patient's risk of high and low blood glucose levels.
  • the individualized HbAlC target level may be provided to the patient in real time or retrospectively, and further, one or more underlying therapy related parameters may be provided to the patient or programmed in an analyte monitoring system such as, for example, but not limited to the receiver unit 104 of the analyte monitoring system 100
  • therapy management settings for example, on the receiver unit 104 such as alarm threshold settings, projected alarm sensitivities, target glucose levels, modification to insulin basal level, recommendation of a bolus intake, and the like may be presented to the patient or provided to the patient's healthcare provider to improve the patient's therapy management.
  • FIG. 20 illustrates routines for managing diabetic conditions based on HbAlC (also referred to as AlC) level and mean glucose data in one aspect.
  • HbAlC also referred to as AlC
  • a linear or nonlinear model may be applied to the glucose data and the HbAlC data in conjunction with the individualized relationship or correlation between the mean glucose data and the HbAlC data.
  • the individualized relationship or correlation may include, but not limited to, the rate of glycation, and/or the erythrocyte lifespan, for example, among others.
  • individualized HbAlC level may be determined either in real time, or retrospectively. For example, using a retrospective data management system based on one or more data processing algorithms or routines, for example, based on the CoPilot system discussed above, determination of future or prediction of current HbAlC level may be ascertained based, for example, on feedback on performance over a predetermined time duration.
  • the individualized HbAlC level determination may be performed in real time, based on real time CGM data, with trend arrows or indicators on the CGM system reflecting a trend or glucose data rate of change over a
  • glucose summary measures may include mean, median, standard deviation, interquartile range, median percentage, below, within or above certain thresholds.
  • the weighted measures by time of day may include, for example, all day, specific time ranges, fasting time period, post-prandial time period, post- breakfast time, post lunch time, post dinner time, pre-meal time, as well as post breakfast/lunch/dinner time relative to therapy administration and/or activity and the like.
  • the time weighted measures may include, in one aspect, weighted measures over a predetermined time periods spaced, for example, differently, such as by, 1, 5, 10, 15, or 30 day bins.
  • FIG. 21 illustrates routines for managing diabetic conditions based on HbAlC level and mean glucose data in another aspect. Compared to the illustration provided in FIG. 20, in embodiments shown in FIG.
  • the linear/non-linear model may include a cost function which may be configured to weigh an individual's risk of high and/or low blood glucose levels, in addition to accepting or factoring other input parameters, such as, for example, HbAlC level targets and/or conditions associated or relevant to hypoglycemia.
  • conditions relevant to hypoglycemia provided as one or more input parameters includes, for example, age, hypoglycemia unawareness, living conditions (e.g., living alone), history of hypoglycemia, insulin pump user, frequency or manner of insulin or medication ingestion or administration, activity level, among others.
  • a further output or results in addition to the individualized HbAlC level determination or prediction may include device or CGM system settings recommendation including, for example, glucose level threshold alarm settings, projected alarm sensitivities associated with the monitored glucose values, alarm settings or progression (e.g., increasing loudness/softness/ strength in vibration etc), glucose level target levels, and the like.
  • the setting recommendations or output may include treatment recommendations such as, for example, insulin/medication dosage information and/or timing of administration of the same, information or recommendation related to exercise, meals, consultation with a healthcare provider, and the like.
  • ADA guidelines (90-130 mg/dL premeal, ⁇ 180 mg/dL peak postmeal) for 31% and 47% of meals, respectively. Only 20% of all meals were in target both before and after meals. On a per subject basis, the results indicate a correlation between HbAlC levels and mealtime glucose control, and CGM system use illustrates trends and patterns around meals that differentiated those with higher and lower HbAlC values.
  • summary and assessment of glucose control around meals may be determined that can be effectively understood and acted upon by analyte monitoring system users and their health care providers.
  • Mealtime therapy decisions are complex, as there are many interacting variables or complications to arriving at a decision that will result in good glucose level control.
  • time, amount and nutrient content to be consumed there may be different factors such as: (1) time, amount and nutrient content to be consumed, (2) accuracy of the consumed nutrient content estimation (ie.
  • FIG. 22 is a flowchart illustrating a therapy guidance routine based in part on the HbAlC level in one aspect. It can be seen from FIG.
  • HbAlC level whether it is in target or out of target is a significant factor in determining or guiding the therapy guidance routine, to determine or prompt the patient to decide whether improvement in HbAlC level (with in target range) is desired, and/or to determine whether the start meal in target range that is greater than approximately 50% as illustrated in the figure.
  • nonlimiting recommendations based on the routine set forth above include, for example, (1) improve understanding and enable improvement of estimates of meal amount and nutrient content, (2) improve understanding and enable adjustment of insulin dose needs, (3) improve understanding and enable adjustment of insulin-to-carbohydrate ratio, (4) improve understanding and enable adjustment of insulin sensitivity ratio, (5) improve understanding of effect of meal choices on glucose control, (6) improve understanding of effect of exercise choices on glucose control, (7) improve understanding of effect of states of health (sickness, menses, stress, other medications) on glucose control, (8) identify patients in need of additional training in different aspects of therapy-decision making, (9) balancing food and insulin, (10) correcting glucose level with insulin, and/or (10) balancing food intake and correcting glucose level with insulin In this manner, in one aspect, summary and assessment of glucose control around meal events may be determined that can be effectively understood and acted upon by analyte monitoring system users and their health care providers.
  • a method in one embodiment may comprise receiving mean glucose value information of a patient based on a predetermined time period, receiving a current
  • HbAlC level of the patient determining whether the current HbAlC level of the patient received is within a predefined target range, and if it is determined that the current HbAlC level is not within the predefined target range, determining one or more corrective action for output to the patient, and if it is determined that the current HbAlC level is within the predetermined target range, analyzing the glucose directional change information around one or more meal events, and determining a modification to a current therapy profile.
  • An apparatus in one embodiment may comprise, a communication interface, one or more processors operatively coupled to the communication interface, and a memory for storing instructions which, when executed by the one or more processors, causes the one or more processors to receive mean glucose value information of a patient based on a predetermined time period, receive a current HbAlC level of the patient, determine whether the current HbAlC level of the patient received is within a predefined target range, if it is determined that the current HbAlC level is not within the predefined target range, determine one or more corrective action for output to the patient, and if it is determined that the current HbAlC level is within the predetermined target range, to analyze the glucose directional change information around one or more meal events, and determining a modification to a current therapy profile.
  • the various processes described above including the processes performed by the processor 204 (FIG. 2) in the software application execution environment in the analyte monitoring system (FIG. 1) as well as any other suitable or similar processing units embodied in the processing & storage unit 307 (FIG. 3) of the primary/secondary receiver unit 104/106, and/or the data processing terminal/infusion section 105, including the processes and routines described hereinabove, may be embodied as computer programs developed using an object oriented language that allows the modeling of complex systems with modular objects to create abstractions that are representative of real world, physical objects and their interrelationships.
  • the software required to carry out the inventive process which may be stored in a memory or storage unit (or similar storage devices in the one or more components of the system 100 and executed by the processor, may be developed by a person of ordinary skill in the art and may include one or more computer program products.

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Abstract

L’invention concerne des procédés et un système fournissant un contrôle glycémique et une prise en charge thérapeutique basée sur la surveillance des résultats glycémiques, et des taux d’HbA1C actuels et/ou ciblés.
PCT/US2009/045766 2008-05-30 2009-05-30 Procédé et système fournissant un contrôle glycémique Ceased WO2009146445A1 (fr)

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Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2012084157A1 (fr) * 2010-12-22 2012-06-28 Roche Diagnostics Gmbh Étalonnage d'un dispositif portatif de gestion du diabète recevant des données d'une sonde de glycémie continue
EP2660606A4 (fr) * 2010-12-28 2015-03-25 Terumo Corp Dispositif de mesure de glycémie
EP2925404A4 (fr) * 2012-11-29 2016-08-03 Abbott Diabetes Care Inc Procédés, dispositifs, et systèmes associés à la surveillance d'analytes
CN109661196A (zh) * 2016-07-08 2019-04-19 诺和诺德股份有限公司 具有自适应目标葡萄糖水平的基础滴定
US11202586B2 (en) 2009-08-31 2021-12-21 Abbott Diabetes Care Inc. Displays for a medical device
US12226239B2 (en) 2021-09-15 2025-02-18 Lingo Sensing Technology Unlimited Company Systems, devices, and methods for applications for communication with ketone sensors
US12397111B2 (en) 2009-05-22 2025-08-26 Abbott Diabetes Care Inc. Continuous glucose monitoring system

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20070010950A1 (en) * 2004-12-03 2007-01-11 Abensour Daniel S Method to determine the degree and stability of blood glucose control in patients with diabetes mellitus via the creation and continuous update of new statistical indicators in blood glucose monitors or free standing computers
US20080125636A1 (en) * 2006-11-28 2008-05-29 Isense Corporation Method and apparatus for managing glucose control

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20070010950A1 (en) * 2004-12-03 2007-01-11 Abensour Daniel S Method to determine the degree and stability of blood glucose control in patients with diabetes mellitus via the creation and continuous update of new statistical indicators in blood glucose monitors or free standing computers
US20080125636A1 (en) * 2006-11-28 2008-05-29 Isense Corporation Method and apparatus for managing glucose control

Cited By (20)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US12397111B2 (en) 2009-05-22 2025-08-26 Abbott Diabetes Care Inc. Continuous glucose monitoring system
US12440172B2 (en) 2009-08-31 2025-10-14 Abbott Diabetes Care Inc. Displays for a medical device
US11730429B2 (en) 2009-08-31 2023-08-22 Abbott Diabetes Care Inc. Displays for a medical device
US12440173B2 (en) 2009-08-31 2025-10-14 Abbott Diabetes Care Inc. Displays for a medical device
US11202586B2 (en) 2009-08-31 2021-12-21 Abbott Diabetes Care Inc. Displays for a medical device
US11241175B2 (en) 2009-08-31 2022-02-08 Abbott Diabetes Care Inc. Displays for a medical device
US8589106B2 (en) 2010-12-22 2013-11-19 Roche Diagnostics Operations, Inc. Calibration of a handheld diabetes managing device that receives data from a continuous glucose monitor
WO2012084157A1 (fr) * 2010-12-22 2012-06-28 Roche Diagnostics Gmbh Étalonnage d'un dispositif portatif de gestion du diabète recevant des données d'une sonde de glycémie continue
EP2660606A4 (fr) * 2010-12-28 2015-03-25 Terumo Corp Dispositif de mesure de glycémie
US9872641B2 (en) 2012-11-29 2018-01-23 Abbott Diabetes Care Inc. Methods, devices, and systems related to analyte monitoring
US10806382B2 (en) 2012-11-29 2020-10-20 Abbott Diabetes Care Inc. Methods, devices, and systems related to analyte monitoring
US11576593B2 (en) 2012-11-29 2023-02-14 Abbott Diabetes Care Inc. Methods, devices, and systems related to analyte monitoring
US11633126B2 (en) 2012-11-29 2023-04-25 Abbott Diabetes Care Inc. Methods, devices, and systems related to analyte monitoring
US11633127B2 (en) 2012-11-29 2023-04-25 Abbott Diabetes Care Inc. Methods, devices, and systems related to analyte monitoring
EP2925404A4 (fr) * 2012-11-29 2016-08-03 Abbott Diabetes Care Inc Procédés, dispositifs, et systèmes associés à la surveillance d'analytes
EP4331659A3 (fr) * 2012-11-29 2024-04-24 Abbott Diabetes Care, Inc. Procédés, dispositifs et systèmes associés à la surveillance d'analytes
CN109661196A (zh) * 2016-07-08 2019-04-19 诺和诺德股份有限公司 具有自适应目标葡萄糖水平的基础滴定
US11373746B2 (en) 2016-07-08 2022-06-28 Novo Nordisk A/S Basal titration with adaptive target glucose level
CN109661196B (zh) * 2016-07-08 2022-03-29 诺和诺德股份有限公司 具有自适应目标葡萄糖水平的基础滴定
US12226239B2 (en) 2021-09-15 2025-02-18 Lingo Sensing Technology Unlimited Company Systems, devices, and methods for applications for communication with ketone sensors

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