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510(k) Data Aggregation

    K Number
    K022046
    Date Cleared
    2002-07-23

    (29 days)

    Product Code
    Regulation Number
    864.5425
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    VITAL SCIENTIFIC COAGULATION CONTROL,COAGULATION CONTROL LEVEL 1,2,3,QUIKCOAG COAGULATION CONTROL

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

    The Coagulation Controls Levels 1, 2, and 3 are in-vitro diagnostic reagents intended for clinical use as a control to monitor the performance of coagulation testing of Prothrombin Time (PT) and activated Partial Thromboplastin time (APTT). Level 1 yields result in the normal range. Level 2 yields results in the moderately abnormal range. Level 3 is intended to yield results in the extremely abnormal range.

    Device Description

    The Coagulation Control Levels 1, 2 and 3 are lyophilized preparations of citrated plasma obtained from healthy donors, which are adjusted to yield prolonged PT and APTT values. Prior to lyophilization buffer and a stabilizer are added. The bulk plasma is tested using an FDA approved method for HBsAG, HIV antibodies and HCV antibodies and is certified for negativity for each batch.

    AI/ML Overview

    The provided document describes a 510(k) summary for "Coagulation Control Level 1, 2, 3" by Vital Scientific NV. The document focuses on demonstrating substantial equivalence to predicate devices through precision studies rather than establishing acceptance criteria against a predefined performance target for a novel device. The study design is a comparison to legally marketed predicate devices.

    1. Table of Acceptance Criteria and Reported Device Performance

    The document does not explicitly state "acceptance criteria" in the traditional sense of a predefined target that the device must meet for approval. Instead, it demonstrates performance by comparing its precision data to that of existing, legally marketed predicate devices. The implicit acceptance criterion is that the new device's precision (measured by Average and %CV) should be "substantially equivalent" to that of the predicate devices.

    Control LevelParameterVital Controls Performance (Average ± %CV, n=20)Reference Controls Performance (Average ± %CV, n=20)Implicit Acceptance Criteria (Substantial Equivalence)
    Within-run Precision
    Level 1 (Normal)PT12.0 ± 1.1%11.6 ± 0.7%Vital Control's precision should be comparable to the reference.
    Level 2 (Low abnormal)PT18.8 ± 1.4%18.7 ± 1.2%Vital Control's precision should be comparable to the reference.
    Level 3 (High abnormal)PT32.6 ± 3.5%32.6 ± 2.7%Vital Control's precision should be comparable to the reference.
    Level 1 (Normal)APTT28.5 ± 2.3%24.9 ± 2.3%Vital Control's precision should be comparable to the reference.
    Level 2 (Low abnormal)APTT47.0 ± 1.7%54.8 ± 2.2%Vital Control's precision should be comparable to the reference.
    Level 3 (High abnormal)APTT61.2 ± 1.9%95.7 ± 2.3%Vital Control's precision should be comparable to the reference.
    Between-run Precision
    Level 1PT %CV1.5%1.2%Vital Control's %CV should be comparable to the reference.
    Level 2PT %CV3.5%2.0%Vital Control's %CV should be comparable to the reference.
    Level 3PT %CV4.5%3.3%Vital Control's %CV should be comparable to the reference.
    Level 1APTT %CV1.8%0.5%Vital Control's %CV should be comparable to the reference.
    Level 2APTT %CV0.7%2.0%Vital Control's %CV should be comparable to the reference.
    Level 3APTT %CV3.9%2.7%Vital Control's %CV should be comparable to the reference.

    Note: The document states "substantially equivalent data" were yielded, implying the reported performance met this implicit criterion.

    2. Sample Size Used for the Test Set and Data Provenance

    • Test Set Sample Size: For within-run precision studies, n = 20 for both Vital Controls and Reference Controls for each level (1, 2, 3) and for both PT and APTT. ("Average ± %CV, n = 20"). For between-run precision, the sample size is not explicitly stated as 'n' but implies multiple measurements over several days ("Day to Day Precision Results").
    • Data Provenance: Not explicitly stated. The study was conducted for a US 510(k) submission, but the location of the actual testing is not specified. It is a prospective study as it involves specific experiments for the submission. The plasma itself is obtained from healthy donors, but the origin of these donors (country) is not mentioned.

    3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications

    Not applicable. This study is a precision study comparing a control device to predicate control devices, not a diagnostic device where "ground truth" on patient samples would be established by experts. The "truth" here is the performance of the predicate devices.

    4. Adjudication Method for the Test Set

    Not applicable. There is no adjudication method described as it's a quantitative measurement of precision rather than a qualitative diagnostic outcome requiring expert consensus.

    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. This is not a study involving human readers or AI assistance. It's a laboratory precision and substantial equivalence study for a diagnostic control.

    6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

    Not applicable. This is not an algorithm; it is a physical control plasma. The comparison is between the new control plasma and existing control plasmas run on a coagulometer (MLA-900C Coagulometer). The performance described is "standalone" in the sense that the control itself is being evaluated for its inherent precision characteristics.

    7. The Type of Ground Truth Used

    The "ground truth" in this context is the established performance characteristics (precision, i.e., average and %CV) of the legally marketed predicate devices. The goal is to show the new device's performance is substantially equivalent to these established benchmarks.

    8. The Sample Size for the Training Set

    Not applicable. There is no "training set" in the context of this device. This is not a machine learning model.

    9. How the Ground Truth for the Training Set Was Established

    Not applicable, as there is no training set mentioned.

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