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510(k) Data Aggregation

    K Number
    K231476
    Manufacturer
    Date Cleared
    2023-12-01

    (193 days)

    Product Code
    Regulation Number
    862.1345
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    TRUENESS™ AIR Blood Glucose Monitoring System; TRUENESS™ Blood Glucose Monitoring System

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The TRUENESS™ AIR Blood Glucose Monitoring System is intended for use in the quantitative measurement of glucose in capillary whole blood from the finger. It is intended for use by people with diabetes mellitus at home as an aid in monitoring the effectiveness of their diabetes control program. The TRUENESS™ AIR Blood Glucose Monitoring System is intended to be used by a single person and should not be shared. It is for in vitro diagnostic use only. The TRUENESS™ AIR Blood Glucose Monitoring System is not intended for the diagnosis of, or screening for diabetes. It is not intended for use on neonates.

    The TRUENESS™ AIR Blood Glucose Monitoring System is comprised of the TRUENESS™ AIR blood glucose meter and the TRUENESS™ blood glucose test strip.

    The TRUENESS™ Blood Glucose Monitoring System is intended for use in the quantitative measurement of glucose in capillary whole blood from the finger. It is intended for use by people with diabetes mellitus at home as an aid in monitoring the effectiveness of their diabetes control program. The TRUENESS™ Blood Glucose Monitoring System is intended to be used by a single person and should not be shared. It is for in vitro diagnostic use only. The TRUENESS™ Blood Glucose Monitoring System is not intended for the diagnosis of, or screening for diabetes. It is not intended for use on neonates.

    The TRUENESS™ Blood Glucose Monitoring System is comprised of the TRUENESS™ blood glucose meter and the TRUENESS™ blood glucose test strip.

    Device Description

    The TRUENESS Blood Glucose Monitoring System and TRUENESS AIR Blood Glucose Monitoring System mainly consist of two parts as below:
    (1) TRUENESS Blood Glucose Meter or TRUENESS AIR Blood Glucose Meter (With Bluetooth function)
    (2) TRUENESS Blood Glucose Test Strip

    A glucose test is based on measurement of electrical current caused by the reaction of glucose with flavin adenine dinucleotide (FAD) glucose dehydrogenase on the electrode of the test strip. The blood or control solution sample is drawn into the tip of the TRUENESS Blood Glucose Test Strip through capillary action. Glucose in the sample reacts with the FAD glucose dehydrogenase and generate electrons. The magnitude of the resultant current is proportional to the concentration of glucose in the blood and is converted to a glucose concentration. The glucose concentration is displayed on the meter display for the user.

    AI/ML Overview

    The provided text primarily focuses on the FDA's 510(k) clearance for the TRUENESS™ AIR Blood Glucose Monitoring System and the TRUENESS™ Blood Glucose Monitoring System. It outlines the regulatory process, device descriptions, and a high-level summary of testing. However, it does not contain the detailed acceptance criteria or the specific study results in the format requested.

    The document indicates that "Design verification and validation testing consisted of performance tests (precision, linearity, interference, flex studies), electrical/mechanical safety tests, as well as disinfection, cleaning, and robustness studies." It also mentions "A user evaluation confirmed the system accuracy, operation according to design, and ease of use to support the intended use as described in the proposed labeling."

    Therefore, I cannot populate the table or answer all your questions with the information given. I can, however, extract the general statement about accuracy.

    Here's a breakdown of what can and cannot be answered based on the provided text:

    1. A table of acceptance criteria and the reported device performance

    Acceptance CriteriaReported Device Performance
    System AccuracyConfirmed by user evaluation
    PrecisionTested
    LinearityTested
    InterferenceTested
    Flex studiesTested
    Electrical/Mechanical SafetyTested
    DisinfectionTested
    CleaningTested
    RobustnessTested

    2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective)

    • Sample Size: Not specified for any of the tests.
    • Data Provenance: Not specified.

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g., radiologist with 10 years of experience)

    • Not specified. The document mentions a "user evaluation" confirmed system accuracy, but does not detail the nature or qualifications of these users as "experts" for establishing ground truth in a clinical sense.

    4. Adjudication method (e.g., 2+1, 3+1, none) for the test set

    • Not specified.

    5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

    • Not applicable/mentioned. This device is a blood glucose monitoring system, not an AI-assisted diagnostic tool that involves human readers.

    6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done

    • The device performs quantitative measurement of glucose. The "system accuracy" would refer to its standalone performance, confirmed by user evaluation. The specifics of this standalone performance are not detailed in terms of metrics.

    7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

    • Not specified. For blood glucose monitoring systems, ground truth is typically established by comparing the device's readings against a laboratory reference method (e.g., YSI analyzer), but this is not explicitly stated in the document provided.

    8. The sample size for the training set

    • Not applicable/mentioned. Blood glucose monitoring systems typically don't have a "training set" in the machine learning sense. Their performance is validated through defined chemical and user studies against reference methods.

    9. How the ground truth for the training set was established

    • Not applicable/mentioned for the same reason as above.
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