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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.
6. Cemented and uncemented applications.

The Provident II Hip Stem is a femoral prosthesis intended to replace a hip joint. The subject stem is a line extension of the Provident II Hip System and is fully compatible with existing femoral heads and liners. The stem is composed of titanium alloy, and is coated with commercially pure titanium.

This appears to be a 510(k) premarket notification for a medical device, specifically the Provident II Hip Stems, and not a study describing acceptance criteria and device performance in the context of an AI/ML medical device. Therefore, I cannot extract the requested information such as test set sample size, ground truth establishment, or clinical study details.

The document discusses:

• Device: Provident II Hip Stems
• Purpose: Clearance for additional implants (line extension)
• Indications for Use: Standard indications for hip arthroplasty (degenerative joint disease, rheumatoid arthritis, fracture treatment, revision, etc.)
• Technological Characteristics: States it has the same characteristics as predicate devices.
• Performance Testing: Mentions mechanical testing (Stem Fatigue, Neck Fatigue) conducted in accordance with ISO standards and FDA guidance for femoral stem prostheses. This is physical mechanical testing of the implant itself, not a clinical study involving patients or AI performance.
• Substantial Equivalence: Basis is stated to be similar technological characteristics, performance, design, and intended use to predicate devices.

There is no mention of:

• Any AI/ML component.
• Acceptance criteria for an AI algorithm.
• A "study that proves the device meets the acceptance criteria" in the context of AI/ML performance.
• Test sets, training sets, ground truth, experts, or adjudication methods related to diagnostic or analytical performance.
• MRMC studies or standalone algorithm performance.

Therefore, I cannot provide the requested table or answer the specific questions related to AI/ML device performance. The provided text describes a traditional medical device clearance based on substantial equivalence and mechanical performance testing, not an AI efficacy study.

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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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