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510(k) Data Aggregation
(30 days)
Patello-Femoral Wave (Kahuna) Arthroplasty System
Intended to be used in cemented arthroplasty in patients with osteoarthritis limited to the distal patello-femoral joint, patients with a history of patellar dislocation or patellar fracture, and those patients with failed previous surgery (arthroscopy, tibial tubercle elevation, lateral release, etc.) where pain, deformity or dysfunction persists.
The Patello-Femoral Wave《hung Arthroplasty System is a line extension to the Sponsor's previously cleared and commercially marketed HemiCAP™ Patello-Femoral Resurfacing System.
The line extension consists of a larger femoral component for increased coverage of the trochlear groove. The additional sizes will address larger defects of the superior aspect of the trochlea and provide greater coverage superiorly. The system also includes larger mating UHMWPE patella components as described within.
The larger PF Kahuna trochlear Patello-Femoral Wave"«ከ«ባ articular component is designed to mate with the currently marketed Arthrosurface Patello-Femoral fixation component.
The majority of the implantation technique steps are the same. The PF Kahuna trochlear component is implanted using the same Instrumentation Set as with the HemiCAP™ Patello-Femoral Resurfacing System, with the addition of a reaming operation to create the superior ream. The reamers, associated implant trials etc. are contained within an adjunct Patello-Femoral WaveKahuna Instrumentation Kit.
The provided text is a 510(k) premarket notification letter and summary for a medical device, the "Patello-Femoral Wave (Kahuna) Arthroplasty System." This document primarily focuses on demonstrating the device's substantial equivalence to a legally marketed predicate device (HemiCAP Patello-Femoral Resurfacing Prosthesis K071413) based on its design, materials, indications for use, and testing.
It is important to note that this document does NOT describe the acceptance criteria or a study that proves the device meets specific performance metrics in the way that an AI/ML medical device submission would. This is a traditional medical device (implant) 510(k) submission, and the "tests" mentioned are primarily about material compatibility, mechanical performance (e.g., contact area, subluxation testing), and sterility rather than a performance study involving diagnostic accuracy or clinical outcomes in the sense of an AI/ML device.
Therefore, most of the requested information regarding acceptance criteria, study sample sizes, expert involvement, ground truth, and AI/ML specific studies (MRMC, standalone performance) for an AI/ML device is not applicable or present in this document.
However, I can extract the information that is present:
Summary of Device Performance and Equivalence (based on the provided text):
The "Patello-Femoral Wave (Kahuna) Arthroplasty System" is a line extension of a previously cleared device. Its approval is based on demonstrating substantial equivalence to the predicate device by showing:
- Same Indications for Use
- Same operating principle
- Manufactured using the same implant grade orthopedic materials
- Utilizes similar instrumentation for proper placement
- Packaged and sterilized using the same materials and processes
1. A table of acceptance criteria and the reported device performance
(Not directly applicable in the AI/ML context, but here's what's presented for this traditional medical device):
Acceptance Criteria Category (Implied) | Reported Device Performance (as demonstrated for substantial equivalence) |
---|---|
Indications for Use Equivalence | The device "Has the same Indications for Use" as the predicate. |
Operating Principle Equivalence | The device "Uses the same operating principle" as the predicate. |
Material Equivalence | The device "Is manufactured using the same implant grade orthopedic materials" as the predicate. |
Instrumentation Equivalence | The device "Utilizes similar instrumentation for proper placement" as the predicate. |
Packaging/Sterilization Equivalence | The device "Is packaged and sterilized using the same materials and processes" as the predicate. |
Biocompatibility/Endotoxin | Met "the standard limit of 0.5 EU/mL or 20 EU/ Device per United States Pharmacopeia (USP) Chapter Bacterial Endotoxins Test, USP Chapter Transfusion and Infusion Assemblies and Similar Medical Devices, and AAMI ST72:2002/R2010, Bacterial Endotoxins—Test Methodologies, Routine Monitoring, and Alternatives to Batch Testing." |
Mechanical Performance | Demonstrated safety and effectiveness through "Device Comparative Analysis," "Contact Area Analysis," and "Lateral Subluxation Testing." (Specific quantitative acceptance criteria and results are not provided in this public summary). |
2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
- Sample Size: Not specified in terms of patient or case numbers for clinical tests. The "tests" listed are bench-top mechanical and material characterization tests.
- Data Provenance: Not applicable in the context of clinical data for this type of submission. The tests are laboratory-based.
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)
- Not applicable. This document does not describe a study involving expert readers or ground truth establishment for a diagnostic or AI/ML performance evaluation. The "experts" would be the engineers and scientists conducting the described non-clinical tests.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
- Not applicable. This is not a study assessing diagnostic accuracy or clinical outcomes via human interpretation.
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. This document does not mention or present any MRMC study, nor is it an AI/ML device.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- No. This document describes a physical implant, not an algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
- Not applicable in the AI/ML sense. The "ground truth" for this device's approval relates to established engineering and material science standards (e.g., USP chapters, AAMI standards for endotoxins, mechanical test methodologies) and comparison to the predicate device's known characteristics.
8. The sample size for the training set
- Not applicable. There is no "training set" as this is not an AI/ML device.
9. How the ground truth for the training set was established
- Not applicable. There is no "training set" or corresponding ground truth establishment for this traditional medical device.
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