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510(k) Data Aggregation

    K Number
    K210411
    Manufacturer
    Date Cleared
    2022-05-05

    (448 days)

    Product Code
    Regulation Number
    874.3620
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    PosiSep EAR Fragmentable Ear Dressing

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

    PosiSep® EAR Fragmentable Ear Dressing is indicated for use in patients undergoing outer ear surgery:
    As a space occupying stent to separate and prevent adhesions between mucosal surfaces; and
    To help control minimal bleeding following surgery or trauma by tamponade effect, blood absorption and platelet aggregation.
    PosiSep® Ear is intended for use under the direction of a licensed healthcare provider.

    Device Description

    The Hemostasis PosiSep® EAR Fragmentable Ear Dressing is a sterile dressing comprised of modified Chitosan particles and polysaccharide binder. Chitosan has well known hemostasis properties and when combined with hydroxyethyl cellulose binder, forms a foam-type dressing that has an affinity to absorb and hold water. PosiSep® EAR Fragmentable Ear Dressing is used in patients undergoing outer ear surgery as a space occupying stent and to help control minimal bleeding. The dressing quickly dehydrates blood, thereby causing rapid hemoconcentration of platelets, serum proteins and fibrinogen, leading to clotting that limits and controls bleeding and edema.
    PosiSep® EAR is fragmentable and eliminated from the site of application by natural excretion via the ear canal.

    AI/ML Overview

    This document describes the PosiSep® EAR Fragmentable Ear Dressing, a medical device, and its acceptance criteria as demonstrated through a substantial equivalence submission to the FDA. The information provided focuses on comparing the device to a predicate device (NasoPore® Ear) and reference devices (PosiSep/PosiSep X) rather than detailing a specific clinical study with granular data on acceptance criteria and performance metrics.

    1. Table of Acceptance Criteria and Reported Device Performance

    The document does not explicitly provide a table of acceptance criteria with numerical targets and corresponding reported device performance. Instead, substantial equivalence is claimed based on comparable characteristics to predicate devices. The key "acceptance criteria" are implied through the comparison parameters.

    Acceptance Criteria (Implied)PosiSep® EAR Fragmentable Ear Dressing Performance (Reported/Claimed)
    ClassificationENT Synthetic Polymer Material, Class II, Product Code NHB
    Indications for UseSame as predicate: Space-occupying stent, control minimal bleeding
    SterilitySupplied sterile (Gamma Sterilized)
    Single-useSingle-use
    BiocompatibilityBiocompatible (ISO 10993-1, non-cytotoxic, non-irritating, non-sensitive, non-pyrogenic, non-toxic)
    Material Composition EffectivenessCarboxymethyl Chitosan and Hydroxyethyl Cellulose (effective for stated indications)
    Tamponade EffectHelps control minimal bleeding by tamponade effect
    Blood AbsorptionHelps control minimal bleeding by blood absorption
    Platelet AggregationHelps control minimal bleeding by platelet aggregation
    Fragmentability/EliminationFragmentable and eliminated by natural excretion
    Physical and Functional Requirements (Bench Testing)Achieved after Design Verification Testing

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

    The document primarily relies on non-clinical performance data, specifically biocompatibility testing and performance bench testing. It does not mention a "test set" in the context of clinical data or patient samples for evaluating device performance against the specified indications. The evaluation appears to be based on:

    • Biocompatibility testing: Performed internally, demonstrating compliance with ISO 10993 and FDA guidelines.
    • Performance bench testing: Performed internally to demonstrate physical and functional requirements were met.
    • Comparison to predicate devices: The primary data provenance is the established safety and effectiveness of the legally marketed predicate devices (NasoPore® Ear, PosiSep/PosiSep X).

    The document does not specify a sample size for these non-clinical tests. As it's a 510(k) submission, the focus is on demonstrating "substantial equivalence" rather than conducting a de novo clinical trial with a large patient sample.

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

    This information is not provided because the submission primarily relies on non-clinical data and comparisons to predicate devices for demonstrating substantial equivalence, not on a clinical test set with human expert-adjudicated ground truth.

    4. Adjudication Method for the Test Set

    Not applicable, as no clinical test set with expert adjudication is described.

    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. The device described is a physical ear dressing, not an AI-powered diagnostic or assistive tool. Therefore, an MRMC comparative effectiveness study involving human readers and AI assistance is not relevant to this submission.

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

    Not applicable, as the device is a physical medical dressing, not an algorithm.

    7. The Type of Ground Truth Used

    For biocompatibility, the ground truth is established by standardized biological tests (e.g., cytotoxicity, irritation, sensitization) following ISO 10993 guidelines, where "ground truth" means the objective results of these tests (e.g., non-cytotoxic). For performance, the "ground truth" relates to the physical and functional properties of the device meeting predetermined engineering specifications during bench testing.

    8. The Sample Size for the Training Set

    Not applicable. The device is not an AI/ML algorithm requiring a training set.

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

    Not applicable, as the device is not an AI/ML algorithm.

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