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510(k) Data Aggregation

    K Number
    K142022
    Manufacturer
    Date Cleared
    2014-12-19

    (147 days)

    Product Code
    Regulation Number
    874.4140
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    MEDLINE RENEWAL REPROCESSED GYRUS-DIEGO SINUS APPLICATION BLADES

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

    Medline ReNewal Reprocessed Gyrus-Diego Sinus Application Blades are designed for use in limited sinus applications involving soft tissue and thin bone such as lamina papyracea.

    Device Description

    Medline ReNewal Reprocessed Gyrus-Diego Sinus Application Blades are sterile single use devices that have been cleaned, disinfected, inspected, refurbished, tested, packaged, labeled, and sterilized. The Medline ReNewal Reprocessed Gyrus-Diego Sinus Application Blades are originally manufactured by OLYMPUS/Gyrus ACMI.

    AI/ML Overview

    This document is a 510(k) premarket notification for Medline ReNewal Reprocessed Gyrus-Diego Sinus Application Blades. It focuses on demonstrating substantial equivalence to a predicate device, rather than providing a detailed study that defines and proves acceptance criteria for a novel device or AI algorithm.

    Therefore, most of the requested information regarding acceptance criteria, specific performance metrics, sample sizes for test and training sets, expert involvement, and ground truth establishment is not present in this document. This document primarily describes the regulatory process for reprocessed medical devices.

    Here's an attempt to answer the questions based on the available information:

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

    The document does not explicitly present a table of quantitative acceptance criteria with corresponding performance results. Instead, it states that "The functional characteristics of the proposed devices have been evaluated and found to be equivalent to the predicate devices after the specified number of reprocessing cycles." The "acceptance criteria" appear to be that the reprocessed blades perform equivalently to the new predicate devices.

    Acceptance Criteria (Implied)Reported Device Performance
    Biocompatibility (in accordance with ISO 10993-1:2009)Testing performed and results were acceptable.
    Cleaning validationTesting performed and results were acceptable.
    Product stabilityTesting performed and results were acceptable.
    Product performance (bench tests, including device integrity)Testing found devices equivalent to predicate after reprocessing.
    Use and operation using simulated clinical use and artificial test soilTesting found devices equivalent to predicate after reprocessing.
    Blade sharpnessTesting found devices equivalent to predicate after reprocessing.
    Irrigation functionTesting found devices equivalent to predicate after reprocessing.
    Outflow functionTesting found devices equivalent to predicate after reprocessing.

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

    The document does not specify the sample sizes used for the various tests (biocompatibility, cleaning validation, product stability, product performance). The data provenance is not mentioned, but given it's a 510(k) submission to the US FDA, the testing would typically be conducted to US regulatory standards. It would be considered prospective for the reprocessed device, as tests are conducted on the reprocessed products.

    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)

    This information is not provided in the document. The testing described (biocompatibility, cleaning validation, bench tests for device function) does not typically involve "experts establishing ground truth" in the same way an AI algorithm for medical imaging would. It involves laboratory testing and comparison to manufacturing specifications or predicate device performance.

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

    This is not applicable and not provided. Adjudication methods are typically used in clinical studies or studies involving human interpretation of data where consensus among multiple reviewers is needed to establish ground truth or evaluate performance. The tests described are laboratory-based and objective performance measurements.

    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

    This is not applicable and not provided. This device is a reprocessed surgical blade, not an AI-assisted diagnostic tool. Therefore, an MRMC study related to human readers and AI assistance would not be relevant.

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

    This is not applicable. This device is a physical surgical tool and does not involve any algorithms.

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

    The "ground truth" in this context is the performance specifications of a new, original equipment manufacturer (OEM) device (the predicate device) and accepted industry standards (e.g., ISO 10993-1 for biocompatibility). The reprocessed device's performance is compared against these established benchmarks.

    8. The sample size for the training set

    This is not applicable. There is no "training set" as this is not an AI/machine learning device.

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

    This is not applicable. There is no "training set."

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