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-Osteoarthritis, traumatic arthritis, polyarthritis, and/or severe chondrocalcinosis of the patellofemoral joint;
-The salvage of previously failed surgical attempts (e.g., arthroscopy, lateral release, cartilage transplantation);
-History of patellar dislocation or patella fracture;
-Dysplasia-induced degeneration
This device is intended for cemented use only.

The Zimmer Patellofemoral Joint (PFJ) Prosthesis is designed to closely replicate the anatomic features of the patellar groove on the femur. The implant's articulating surface incorporates the NexGen® knee system's frontal profile geometry for optimal patella tracking for both resurfaced and unresurfaced patellas. The construct of the PFJ prosthesis accommodates a wide range of patients, both female and male. Five sizes in left and right configurations are being offered for this implant.

Here's an analysis of the provided text regarding the Zimmer® Patellofemoral Joint Prosthesis:

Description of Acceptance Criteria and Study to Prove Device Meets Acceptance Criteria

The provided document is a 510(k) Summary for the Zimmer® Patellofemoral Joint Prosthesis (K070695). For this type of device, a 510(k) clearance is typically based on demonstrating substantial equivalence to a legally marketed predicate device, rather than explicit "acceptance criteria" and a detailed "study" in the sense of a clinical trial proving specific performance metrics against those criteria.

The acceptance criteria here would be understood as the device being as safe and effective as the predicate devices. The "study" demonstrating this involves non-clinical performance data and a comparison to the predicate device.

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size for Test Set: Not applicable. This submission relies on non-clinical testing, which typically involves laboratory or benchtop tests on components or the complete device itself, not a patient-based "test set" in the traditional clinical trial sense.
• Data Provenance: Not applicable for a "test set" as described above. The "non-clinical testing" would have been conducted by Zimmer, Inc., likely at their facilities or by contracted testing laboratories.

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

• Not applicable. As this is a non-clinical submission, ground truth related to patient outcomes or diagnoses is not established by clinical experts for a test set. The "ground truth" relates to engineering and material specifications, and the functionality of the device as tested in a lab setting.

4. Adjudication Method for the Test Set

• Not applicable. There is no mention of a human-read test set or any adjudication process.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done

• No. An MRMC study is a type of clinical comparative study involving multiple human readers interpreting medical images, typically with and without AI assistance, across multiple patient cases. This submission is for a prosthetic device, not an imaging diagnostic tool, and the data presented is non-clinical.

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

• Not applicable in the context of imaging algorithms. This device is a physical implant. The "standalone performance" is essentially the device's mechanical and functional performance demonstrated through non-clinical bench testing.

7. The Type of Ground Truth Used

• The "ground truth" for non-clinical testing refers to established engineering standards, biomechanical principles, material specifications, and performance targets derived from the predicate devices and general orthopedic requirements. It's based on engineering specifications and established mechanical/material properties, rather than clinical outcomes or pathology.

8. The Sample Size for the Training Set

• Not applicable. In the context of medical devices like prostheses, there isn't a "training set" in the sense of machine learning. The design and development of the device would involve iterative engineering, simulations, and prototype testing, but not a dataset used to "train" an algorithm.

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

• Not applicable. See point 8. The design process is guided by anatomical studies, engineering principles, and experience with previous successful knee prosthesis designs (including the predicate devices).

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