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510(k) Data Aggregation

    K Number
    K021232
    Date Cleared
    2002-05-16

    (28 days)

    Product Code
    Regulation Number
    870.1220
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    CONSTELLATION CATHETERS, MODEL 8031M

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

    For use in right atrial electrophysiology procedures to assist in the diagnosis of complex arrhythmias that may be difficult to identify using conventional mapping systems alone (i.e., linear mapping catheters). The Constellation® Multiple Electrode Recording and Pacing Catheter System may also be used for delivery of externally generated pacing stimuli.

    Device Description

    The Boston Scientific/EP Technologies (EPT) Constellation® Multiple Electrode Recording and Pacing Catheter is a sterile, single use device used to detect and record electrical potentials from the endocardial surfaces of the heart, and to deliver externally generated pacing stimuli. The distal, expandable "basket" assembly is, in essence, eight miniature octapolar "catheters". The basket assembly contains an array of between 32 to 64 electrodes mounted along eight resilient support structures called "splines". Several configurations are available, including unipolar (electrodes evenly spaced), bipolar (electrodes evenly distributed into pairs), and lower density arrays. EPT furnishes the Constellation® Catheter either with or without the Duraflo® coating. EPT also furnishes accessories that include EPT Constellation Accessory Cables (sterile, reuseable), an EPT Constellation Pacing Switchbox (non-sterile, re-useable), and EPT Constellation extension cables (non-sterile, re-useable).

    AI/ML Overview

    The provided document is limited to a 510(k) summary for a medical device (Constellation® Multiple Electrode Recording and Pacing Catheter System) and primarily focuses on demonstrating substantial equivalence to a predicate device. It does not contain information about acceptance criteria or a study that proves the device meets specific acceptance criteria in the way one might expect for a new AI/software-driven device.

    The study described is a non-clinical bench test. Here's a breakdown based on the available information:

    1. Table of acceptance criteria and the reported device performance
      The document does not explicitly state quantitative acceptance criteria or a detailed performance report in the context of specific metrics. The "performance testing" mentioned is qualitative and aimed at demonstrating "substantial equivalence" to a predicate device, rather than meeting predefined numerical targets of a new device.

    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. The document only mentions "electrical integrity testing."
      • Data provenance: Not applicable, as this was non-clinical bench testing.
    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 applicable. Ground truth is not established by human experts for this type of non-clinical device testing.
    4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

      • Not applicable. There is no mention of adjudication for this non-clinical testing.
    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

      • No. This is a medical device (catheter), not an AI-driven diagnostic or assistive tool for human readers.
    6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

      • Yes, in a sense. The "bench testing" represents the device's standalone non-clinical performance to confirm its functional characteristics. However, this is not an "algorithm-only" performance in the AI context.
    7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

      • For the non-clinical testing, the "ground truth" would be established by the expected design specifications and engineering standards for electrical integrity and physical characteristics of the device.
    8. The sample size for the training set

      • Not applicable. This is not a machine learning or AI device that requires a training set.
    9. How the ground truth for the training set was established

      • Not applicable. No training set was used.
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