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510(k) Data Aggregation

    K Number
    K132313
    Device Name
    PESSARY
    Manufacturer
    Date Cleared
    2014-12-05

    (498 days)

    Product Code
    Regulation Number
    884.3575
    Reference & Predicate Devices
    Why did this record match?
    Applicant Name (Manufacturer) :

    EIS CORPORATION

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

    EIS Vaginal Pessaries are indicated for the use as removable structures placed in the vagina to treat uterine prolapse, including cystocele and rectocele, as well as stress urinary incontinence in women

    Device Description

    The subject device is a silicone vaqinal pessary. The submission includes the following designs: cube, dish, donut, marland, oval, gellhorn, gellhorn short, shaatz, and ring.

    AI/ML Overview

    The provided document is a 510(k) premarket notification decision letter from the FDA for a device named "Pessary" manufactured by EIS Corporation. This type of submission aims to demonstrate that a new device is substantially equivalent to a legally marketed predicate device.

    The essential nature of a 510(k) submission, particularly for a device like a vaginal pessary, means that the "acceptance criteria" and "study that proves the device meets the acceptance criteria" are typically related to demonstrating substantial equivalence to a predicate device, rather than proving novel clinical efficacy or diagnostic performance. Therefore, the "acceptance criteria" in this context refer to showing that the new device shares fundamental technological characteristics and intended use with the predicate, and does not raise new questions of safety or effectiveness. The "study" refers to non-clinical performance testing confirming that these characteristics are maintained.

    Based on the provided text, here's the information broken down:

    1. Table of Acceptance Criteria and Reported Device Performance

    For a 510(k) for a physical medical device like a pessary, the acceptance criteria are not typically expressed in terms of diagnostic metrics like accuracy or sensitivity. Instead, they relate to material properties, safety assessments, and functional comparison to a predicate.

    Acceptance Criteria CategorySpecific Acceptance Criteria (Inferred from 510(k) process and provided text)Reported Device Performance (from K132313 Summary)
    Intended Use EquivalenceNew device's intended use is substantially equivalent to the predicate."EIS Vaginal Pessaries are indicated for the use as removable structures placed in the vagina to treat uterine prolapse, including cystocele and rectocele, as well as stress urinary incontinence in women." This is identical to the predator device's intended use as stated in the comparison table.
    Material EquivalenceNew device material is the same as or equivalent to the predicate and biocompatible."silicone" (same as predicate). Biocompatibility tests performed and "completed" per ISO 10993-1.
    Technological Characteristics EquivalenceNew device's fundamental technological characteristics (shape, size, class) are substantially equivalent to the predicate."Various and similar" shapes and sizes to the predicate. Classified as Class 2 (same as predicate).
    BiocompatibilityDevice material must be biocompatible according to recognized standards.Biocompatibility tests completed per ISO 10993-1, including Cytotoxicity, Intracutaneous (intradermal) reactivity, Skin sensitization, and Acute systemic toxicity.
    Shelf LifeDevice maintains integrity and functionality over its claimed shelf life.Shelf life testing was performed and included in the performance testing.

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

    This document describes a 510(k) for a physical device, not an AI/ML diagnostic or prognostic device. The "test set" in this context would refer to samples used for non-clinical performance testing (e.g., material testing, biocompatibility).

    • Sample size: Not specified. Standard practice for biocompatibility and shelf-life testing involves a sufficient number of samples to achieve statistical confidence or meet regulatory requirements, but the exact number isn't in this summary.
    • Data provenance: Not explicitly stated regarding country of origin for the non-clinical tests. The manufacturer is based in Korea. The studies are "non-clinical study performance," meaning laboratory-based rather than human clinical trials. Thus, the data is prospective within the lab setting.

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

    Not applicable. For a physical device 510(k), experts are typically involved in designing and interpreting the non-clinical tests (e.g., toxicologists for biocompatibility, engineers for material properties), but their "ground truth establishment" is not in the same vein as expert consensus for diagnostic interpretation. The "ground truth" for these tests would be objective measurements against established scientific standards.

    4. Adjudication Method for the Test Set

    Not applicable. Adjudication methods (like 2+1) are relevant for reconciling differing expert opinions in diagnostic studies. For non-clinical material and performance testing, results are typically objective measurements or observations against predetermined criteria.

    5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, What Was the Effect Size of How Much Human Readers Improve with AI vs. Without AI Assistance

    Not applicable. This is not an AI/ML device.

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

    Not applicable. This is not an AI/ML device.

    7. The Type of Ground Truth Used

    The "ground truth" for the non-clinical studies (biocompatibility, shelf life) would be:

    • Established scientific standards and regulatory guidelines: For biocompatibility, this refers to the criteria outlined in ISO 10993-1, where specific chemical, biological, and physical parameters are measured and compared against acceptable thresholds.
    • Material specifications: For physical properties, performance is compared against predefined engineering specifications for the silicone material.

    8. The Sample Size for the Training Set

    Not applicable. This is not an AI/ML device, so there is no training set in the machine learning sense. The "training" for such a device is in its manufacturing and material selection process.

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

    Not applicable. See #8.

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