Search Filters

Search Results

Found 1 results

510(k) Data Aggregation

    K Number
    K963999
    Date Cleared
    1996-11-27

    (51 days)

    Product Code
    Regulation Number
    876.1500
    Reference & Predicate Devices
    Why did this record match?
    Reference Devices :

    K944415

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

    The AUTO SUTURE* Modified Endoscopic Fascia Stapler** device is intended for use in affixing prosthetic material or approximating tissue. This device may be used both endoscopically and in open procedures.

    Device Description

    The AUTO SUTURE* Modified Endoscopic Fascia Stapler** device is an endoscopic stapling device. The device is disposable and is supplied sterile.

    AI/ML Overview

    This 510(k) premarket notification (K96399) for the United States Surgical Corporation's AUTO SUTURE* Modified Endoscopic Fascia Stapler** is very limited in the detail it provides regarding performance testing. It lacks sufficient information to address most of your specific questions.

    Here's an analysis based on the provided text, highlighting what's available and what's missing:

    1. Table of Acceptance Criteria and Reported Device Performance

    Acceptance CriteriaReported Device Performance
    Fastener Security"adequate fastener strength."
    • Comment: The document doesn't provide specific quantitative acceptance criteria (e.g., minimum tensile strength in Newtons, or a pass/fail rate for fastener pull-out). It simply states the device was tested to evaluate fastener security and that the results demonstrated "adequate fastener strength." This is a very high-level and subjective statement.

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

    • Sample Size: Not specified.
    • Data Provenance: Not specified (e.g., country of origin, retrospective or prospective).
    • Comment: The document only mentions "tested both in-vivo and in-vitro." No details on the number of staples, animals, or human subjects used for either type of testing are provided.

    3. Number of Experts Used to Establish Ground Truth and Qualifications

    • Not Applicable. This device is a surgical stapler, not an diagnostic imaging or AI device. Ground truth as typically understood in the context of expert review for AI performance is not relevant here. The "ground truth" would be the mechanical integrity and biological response to the staples, evaluated through direct measurement or observation.

    4. Adjudication Method for the Test Set

    • Not Applicable. See point 3.

    5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

    • No. This is not relevant for a surgical stapler. MRMC studies are typically used for diagnostic or screening devices where human readers interpret data (e.g., medical images), and the effect of AI on their performance is being evaluated.

    6. Standalone Performance Study

    • Yes, implicitly. The document states "The AUTO SUTURE* Modified Endoscopic Fascia Stapler** device was tested both in-vivo and in-vitro to evaluate fastener security." This testing would represent the standalone performance of the device itself.
    • Comment: While "standalone" is usually used in the context of AI, for a physical medical device, testing its performance without human intervention (i.e., the device's inherent mechanical properties) would be considered standalone.

    7. Type of Ground Truth Used

    • Mechanical Measurement and Biological Observation: The "ground truth" for fastener security would likely have been established through:
      • In-vitro: Mechanical testing (e.g., pull-out strength, sheer strength, burst pressure in model tissue) using standardized methods.
      • In-vivo: Direct observation of staple line integrity, healing, and absence of complications (e.g., leakage, dehiscence) in animal models.
    • Comment: No specific details are provided in the document.

    8. Sample Size for the Training Set

    • Not Applicable. This is a physical medical device, not an AI/machine learning algorithm. The concept of a "training set" for AI is not relevant here. The design and manufacturing process would be informed by prior engineering principles and potentially previous device data, but not in the same way an AI algorithm is "trained."

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

    • Not Applicable. See point 8.

    Summary of Limitations:

    This 510(k) summary provides very sparse information about the performance testing. It lacks granular details such as:

    • Specific quantitative acceptance criteria.
    • The number of test articles or subjects.
    • The specific tests performed (e.g., what kind of in-vitro tests, what animal model for in-vivo).
    • The actual numerical results obtained from these tests.
    • A direct comparison to the predicate device in terms of performance metrics.

    This level of detail is typical for older 510(k) summaries which were often considerably less comprehensive than current submissions. The statement "The results of this testing demonstrate that the subject device provides adequate fastener strength" is a very broad conclusion without supporting data in this summary.

    Ask a Question

    Ask a specific question about this device

    Page 1 of 1