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510(k) Data Aggregation

    K Number
    K982999
    Date Cleared
    1998-10-16

    (50 days)

    Product Code
    Regulation Number
    862.1675
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    GREINER MINICOLLECT EDTA BLOOD COLLECTION TUBE

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

    To collect, transport, store, and evaluate capillary blood specimens for hematology and lead tests.

    Device Description

    The Greiner MiniCollect® EDTA K3 tube is a non-sterile, non-evacuated blood collection device containing EDTA K3 anticoagulant additive, and is intended for use in evaluations of capillary blood specimens. The Greiner MiniCollect® tube cap is made from rubber and has "cross-cuts" to allow for direct collection into and sampling from the tube without having to remove the cap.

    AI/ML Overview

    The provided text is a 510(k) summary for a blood collection tube (Greiner MiniCollect® EDTA K3 tube) and does not describe an AI medical device. Therefore, much of the requested information, such as acceptance criteria for AI performance metrics, sample sizes for training/test sets, expert adjudication methods, MRMC studies, or standalone algorithm performance, is not applicable.

    However, I can extract the relevant information regarding the device's equivalency study.

    Acceptance Criteria and Study for Greiner MiniCollect® EDTA K3 Blood Collection Tube

    This device is a blood collection tube and not an AI medical device. The "acceptance criteria" in this context refers to demonstrating substantial equivalence to a legally marketed predicate device, rather than performance metrics for an AI algorithm. The study aimed to show that the new device yielded comparable assay results to the predicate device.

    1. Table of Acceptance Criteria and Reported Device Performance

    ParameterAcceptance CriteriaReported Device Performance
    Equivalency of Assay ResultsGood correlation between test results from paired samples for 15 hematology parameters and lead tests when collected in Greiner MiniCollect® EDTA K3 tubes and Becton Dickinson Microtainer® Brand EDTA K2 tubes."Test results from paired samples for 15 hematology parameters and lead tests were evaluated and good correlation was observed."

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

    • Sample Size: The document states "paired samples" were used, but it does not specify the number of samples (n) involved in the study.
    • Data Provenance: Not specified, but generally, such studies involve prospective collection of samples for comparison. The country of origin is not mentioned.

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

    This is not applicable as the study involved comparing assay results from two different blood collection tubes, not establishing ground truth for an AI algorithm's predictions. The "ground truth" here would be the actual values obtained from laboratory analysis, not expert consensus.

    4. Adjudication Method for the Test Set

    Not applicable. This was a direct comparison of analytical results, not an assessment requiring expert adjudication.

    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 an AI device, and no MRMC study was conducted.

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

    Not applicable. This is not an AI device.

    7. The type of ground truth used

    The "ground truth" was the analytical results from standard laboratory assays for 15 hematology parameters and lead tests. These results were obtained from blood specimens collected in both the investigational device and the predicate device.

    8. The sample size for the training set

    Not applicable. This is not an AI device, and therefore, no training set was used.

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

    Not applicable. As there is no training set for an AI algorithm, this question is not relevant.

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