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510(k) Data Aggregation

    K Number
    K060988
    Date Cleared
    2006-12-06

    (240 days)

    Product Code
    Regulation Number
    888.3660
    Reference & Predicate Devices
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The DVOTM Total and Hemi Shoulder System is intended for use in total or hemi-arthroplasty.

    The DVO™ Total and Hemi Sl»vulder System is indicated for:

      1. A severely painful and/or disabled joint resulting from osteoarthritis, traumatic arthritis or rheumatoid arthritis:
    • Fracture/dislocations of the proximal humerus where the articular surface is severely comminuted, 2. separated from its blood supply or where the surgeon's experience indicates that alternative methods of treatment are unsatisfactory;
    • నే. Other difficult clinical problems where shoulder anthrodesis or resection arthroplasty are not acceptable (c.g., revision of a failed primary component).

    Hemi-shoulder replacement is also indicated for:

      1. Ununited humeral head fractures;
      1. Avascular necrosis of the humeral head.
      1. Rotator cuff tear arthropathy.

    Humeral stems and glenoids labeled "for cemented use only" are indicated only for use with bone cement. Humeral stems are indicated for press-fit uncemented use or for use with bone cement.

    This is a single use device.

    Device Description

    This sterile modular total and hemi shoulder system is comprised of a humeral stem, two styles of humeral heads (standard and exentric) and two styles of glenoids (pegged or keeled). The heads mate on the stems through a locking taper. The heads are highly polished and articulate with the glenoids.

    The humeral stems are offered in two lengths: standard (110mm with diameters of 6 to 16mm) or long (200 to 220mm in length with diameters of 8 to 14mm). The stems are fluted, except for the 6mm diameter stem. The stems also have fins with suture holes. The head is available in 15 standard sizes (40 to 56mm in heights of 15, 18 and 21 mm) and 10 eccentric sizes (40 to 56mm in heights of 18mm or 21mm).

    Materials include titanium humeral stems, cobalt chrome humeral heads and ultrahigh molecular weight polyethylene glenoids.

    AI/ML Overview

    The provided text describes a 510(k) premarket notification for a medical device, the DVOTM Total and Hemi Shoulder System. This type of submission focuses on demonstrating "substantial equivalence" to a legally marketed predicate device, rather than proving safety and effectiveness through clinical trials with specific acceptance criteria and detailed performance studies.

    Therefore, the document does not contain details about acceptance criteria or a study that proves the device meets specific performance metrics in the way that would be typical for an AI/software device or a novel medical device requiring de novo authorization.

    Instead, the submission for the DVOTM Total and Hemi Shoulder System primarily relies on demonstrating substantial equivalence to predicate devices based on:

    • Intended Use: Similar for total or hemi shoulder replacement.
    • Performance Characteristics: Overall comparable.
    • Materials of Construction: Titanium alloy, cobalt chrome alloy, and UHMWPE are common in both.
    • Methods of Sterilization, Packaging, Manufacturing Methods, and Design: All are similar.
    • Technological Characteristics and Dimensional Analysis: These were compared.
    • Nonclinical Testing: This is mentioned as evidence, specifically stating that the subject device's "fatigue load carrying capability exceeds the predicate devices." This is the closest thing to a performance metric and a "study" result, but it's a nonclinical bench test, not a clinical study.

    Given this context, I cannot provide the requested information in the format of acceptance criteria and a study demonstrating performance because the type of device registration (510(k)) and the provided document do not include such details.

    However, I can extract information related to what was presented to establish equivalence:


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

    As explained above, specific clinical acceptance criteria and device performance metrics from a human or clinical study are not applicable to this 510(k) submission as presented. The primary "performance" discussed is nonclinical:

    Criterion (Nonclinical)Reported Device Performance
    Fatigue load capability"Exceeds the predicate devices."

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

    This information is not provided in the document. The "test set" for the fatigue load capability would refer to the number of devices or components tested during nonclinical 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)

    This information is not provided in the document, as it pertains to nonclinical testing, not expert-adjudicated clinical data.

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

    This information is not provided. It is not relevant for nonclinical bench testing which does not involve human adjudication.

    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, an MRMC comparative effectiveness study was not done. This is a submission for an orthopedic implant, not an AI or imaging diagnostic device.

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

    This question is not applicable. This is an orthopedic implant and does not involve an algorithm.

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

    For the stated "fatigue load carrying capability," the "ground truth" would be the engineering specifications and test standards (e.g., ISO standards for implant testing) to which the device was subjected. It is not based on expert consensus, pathology, or outcomes data, as those apply to clinical evaluations.

    8. The sample size for the training set

    This question is not applicable. This is an orthopedic implant, not a software device, and therefore does not have a "training set" in the context of machine learning.

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

    This question is not applicable for the reasons stated above.

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