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1. Non-inflammatory degenerative joint disease including osteoarthritis, traumatic arthritis , and avascular necrosis.
2. Rheumatoid Arthritis.
3. Correction of functional deformity.
4. Treatment of non-union, femoral neck fracture, and trochanteric fractures of the proximal femur with head involvement, unmanageable using other techniques.
5. Revision of previously failed total hip arthroplasty.
   Cemented and Uncemented Applications

The purpose of this Special 510(k) is to expand the Provident Hip System with a line extension to the existing Provident Hip Stems. The new stems are to be marketed as the Provident II Hip Stems and feature a shortened stem.

This is a medical device submission for a Hip Stem, not an AI/ML device. Therefore, the requested information about acceptance criteria, study details, expert involvement, MRMC studies, standalone performance, ground truth, and training set specifics for an AI/ML device are not applicable.

The submission is for the Provident II Hip Stem, a physical medical device. The "acceptance criteria" and "study that proves the device meets the acceptance criteria" in this context refer to the engineering analyses and tests conducted to demonstrate the substantial equivalence of the Provident II Hip Stems to predicate devices.

Here's the relevant information that can be extracted:

1. Acceptance Criteria and Device Performance (as related to substantial equivalence to predicate devices):

2. Sample size used for the test set and the data provenance: Not applicable to this type of device submission. The "test set" here would refer to the physical hip stems undergoing engineering analysis and LAL testing, not a dataset in the AI/ML sense. Data provenance refers to the origin of the materials and manufacturing, not a clinical data source.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth as typically understood in AI/ML is not relevant here. The evaluation relies on engineering principles and regulatory standards.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable.

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. This is a physical orthopedic implant.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This is a physical orthopedic implant.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc): For the engineering analysis, the "ground truth" is established by recognized engineering standards and comparison to the performance of the legally marketed predicate devices, as demonstrated through testing and simulation. For pyrogen testing, the ground truth is established by the LAL assay and compliance with established pyrogen limits.

8. The sample size for the training set: Not applicable (this is not an AI/ML device).

9. How the ground truth for the training set was established: Not applicable (this is not an AI/ML device).

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The GENFlex2 Total Knee System is intended for:
· Total knee replacement due to osteoardis, theumatoid arthritis, and/or post-traumatic degenerative problems.
· Revision of failed previous reconstructions where sufficient bone stock and soft tissue integrity are present.
The device is intended for cemented use only.

The purpose of this Special 510(k) is to add the Ultra-Congruent CR Tibial Insert to the GENFlex2 Total Knee System. The Ultra-Congruent CR Tibial Insert is a component within a cemented total knee joint replacement system comprised of modular components with varying sizes available for each component. The articulating geometry of the Ultra-Congruent CR Tibial Insert provides for increased stability relative to the predicate CR insert. The inserts are manufactured from EXp Vitamin E Polyethylene and Conventional Polyethylene.

The provided text describes a 510(k) premarket notification for a medical device, specifically a knee replacement system component. It focuses on demonstrating substantial equivalence to a predicate device rather than presenting a study proving that the device meets specific acceptance criteria related to its performance in a clinical or diagnostic setting. Therefore, most of the information requested in the prompt, such as an acceptance criteria table, sample sizes for test sets, expert consensus, MRMC studies, standalone performance, and ground truth establishment for AI/diagnostic devices, is not applicable to this submission type.

The document discusses bench testing to demonstrate the physical performance of the device (A/P constraint testing and contact area analyses), but these are engineering verification tests, not clinical performance studies with human subjects or expert readers establishing ground truth for diagnostic accuracy.

Here's a breakdown of the relevant information provided in the given text, and why other parts of your request cannot be fulfilled:

Acceptance Criteria and Device Performance (Not directly addressing the prompt for diagnostic/AI devices):

• A/P constraint testing: Performed on the modified GENFlex2 Ultra-Congruent CR Tibial Inserts and compared to results for the predicate inserts. The statement says, "All results demonstrate that the modified device performs similarly to the predicate device."
• Contact area analyses: Performed on the modified and predicate devices. Again, "All results demonstrate that the modified device performs similarly to the predicate device."
• Limulus Amebocyte Lysate (LAL) testing: Performed to establish that the device meets pyrogen limit specifications.

Table of Acceptance Criteria and Reported Device Performance:

• The document states that the "modified geometry of the Ultra-Congruent CR Tibial Insert meets the pre-determined acceptance criteria for the verification activities." However, it does not provide a table with specific numerical acceptance criteria or the exact reported performance values from these engineering tests. It only states that the performance was "similar" to the predicate device and met pyrogen limits.

Applicable Information from the Text:

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

   • Acceptance Criteria: "meets the pre-determined acceptance criteria for the verification activities" (no specific numerical criteria provided). "meets pyrogen limit specifications."
   • Reported Device Performance:
     • A/P constraint testing: "All results demonstrate that the modified device performs similarly to the predicate device."
     • Contact area analyses: "All results demonstrate that the modified device performs similarly to the predicate device."
     • LAL testing: Confirmed device meets pyrogen limit specifications.

2. Sample sized used for the test set and the data provenance: Not applicable in the context of clinical/diagnostic AI device testing. The tests mentioned are engineering bench tests, not involving human data or a "test set" in the diagnostic sense.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. This is not a study requiring expert readers or ground truth establishment for diagnostic accuracy.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable.

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. This is not an AI/diagnostic device.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This is not an AI/diagnostic device.

7. The type of ground truth used (expert concensus, pathology, outcomes data, etc): Not applicable. The "ground truth" here is the engineering specifications and performance of the predicate device, for which the new device demonstrated "similarity."

8. The sample size for the training set: Not applicable. There is no training set mentioned as this is not an AI/machine learning device.

9. How the ground truth for the training set was established: Not applicable.

In summary, the provided text describes a 510(k) submission for a physical medical device (knee implant component) that demonstrates substantial equivalence through engineering bench testing and material compatibility, rather than a study on a diagnostic AI device requiring the detailed "acceptance criteria" and "ground truth" information for accuracy performance.

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The GENFlex2 Total Knee System is intended for:
● Total knee replacement due to osteoarthritis, osteonecrosis
rheumatoid arthritis, and/or post-traumatic degenerative
problems.
● Revision of failed previous reconstructions where
sufficient bone stock and soft tissue integrity are present.
The device is intended for cemented use only.

The GENflex2 System is a cemented total knee joint replacement system comprised of modular components with varying sizes available for each component. The purpose of this Special 510(k) is to modify the geometries of the Posterior Stabilized and the Cruciate Retaining tibial insert and femoral component. These components are manufactured from EXp Vitamin E Polyethylene, Conventional Polyethylene and Cobalt Chrome Alloy. Each component is available in a range of sizes that complement each other.

I am sorry, but based on the provided text, there is no information about an AI/ML-based medical device, a study proving its performance, acceptance criteria, or any of the specific details you requested (like sample sizes, expert qualifications, adjudication methods, MRMC studies, standalone performance, ground truth establishment, or training set details).

The document is a 510(k) premarket notification for a traditional medical device: the "GENflex2 Total Knee System," which is a knee joint replacement system. The review focuses on its substantial equivalence to predicate devices based on materials, geometry, and mechanical performance (e.g., static and fatigue testing, engineering analyses of contact area).

Therefore, I cannot populate the table or answer the specific questions related to AI/ML device performance and validation.

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