(29 days)
The Klassic® Knee System is intended for prosthetic replacement in treatment of the following:
- Patient conditions of non-inflammatory degenerative joint disease (NIDJD): avascular necrosis and osteoarthritis
- Patient conditions of inflammatory joint disease (IJD): rheumatoid arthritis
- Patients with failed previous surgery where pain, deformity, or dysfunction persists
- Correctable varus-valgus deformity and moderate flexion contracture
- Revision of a previously failed knee arthroplasty
- Patients who require a total knee replacement
The Klassic® Knee System is indicated for cemented use only, except for the Klassic® Femur, with Cobalt 3D®, the Klassic® Tibial Baseplate with Ti-Coat® and the Universal Cones™ with Ti-Coat®, which are also indicated for cementless use.
The Klassic® Knee System is being updated with additional thicknesses of Tibial Inserts, PS-Post and Additional All Poly Tibia PS-Post implants. Both proposed geometries are fabricated from both Standard Poly and Vitamin E UHMWPE (E-Link).
This document is a 510(k) Pre-Market Notification from the FDA regarding the Klassic® Tibial Insert, PS-Post, and Klassic All Poly Tibia, PS-Post. It primarily focuses on demonstrating substantial equivalence to previously cleared predicate devices, rather than presenting a study of a novel AI-powered medical device.
Therefore, the requested information regarding acceptance criteria and a study proving a device (implying an AI or software as a medical device) meets these criteria cannot be fully extracted from the provided text. The document describes non-clinical testing and engineering analyses for mechanical components (tibial inserts), not a software or AI device.
However, I can extract the information that is present and explain why other requested information is not applicable to this document.
Information Extracted from the Document (Pertaining to Mechanical Device Evaluation):
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A table of acceptance criteria and the reported device performance:
The document states: "Testing and engineering analyses showed that the subject components met the pre-determined acceptance criteria identified in the Design Control Activities, demonstrating that the subject components perform as safe and effective compared to the predicate components, and is substantially equivalent to the predicate."
It lists the types of non-clinical tests performed:
- Femoral/Tibial Constraint Testing (ASTM F1223)
- Contact Area/Contact Stress (ASTM F2083)
- Post Fatigue Testing
- Range of Motion Evaluation
- Wear (ISO 14243-3)
- Tibial Insert Modular Disassembly Strength (ASTM F1814)
While the types of tests and the conclusion that criteria were met are stated, the specific quantitative acceptance criteria (e.g., minimum load for post fatigue, maximum wear rate) and the measured performance values are not provided in this summary document. This information would typically be in the full submission, not the public summary.
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Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):
This document describes testing of physical components (tibial inserts), not an AI algorithm. Therefore, "sample size" would refer to the number of physical components tested, which is not specified. "Data provenance" such as country of origin or retrospective/prospective is not applicable in the context of mechanical engineering testing on manufactured parts.
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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. Ground truth, in the context of an AI device, refers to expertly labeled data. Here, the "ground truth" (or standard) for mechanical performance is established by engineering standards (e.g., ASTM, ISO), not human experts labeling data.
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Adjudication method (e.g. 2+1, 3+1, none) for the test set:
Not applicable. Adjudication methods are relevant for human interpretation of complex data (e.g., medical images) to establish ground truth for AI training/testing. This document is about mechanical testing.
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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. An MRMC study assesses the impact of an AI algorithm on human diagnostic performance. This document concerns the substantial equivalence of a physical medical implant.
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If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
Not applicable. Standalone performance refers to the performance of an AI algorithm without human involvement. This evaluation is of a mechanical device.
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The type of ground truth used (expert concensus, pathology, outcomes data, etc):
The "ground truth" for the mechanical components is defined by established engineering and biological safety standards (e.g., ASTM F1223, ASTM F2083, ISO 14243-3, ASTM F1814, and LAL testing for orthopedic implants). These are quantitative, objective measurements against pre-defined engineering and material science criteria.
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The sample size for the training set:
Not applicable. There is no "training set" as this is not an AI/machine learning device. The design and testing are based on engineering principles and material science.
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How the ground truth for the training set was established:
Not applicable (no training set).
Summary of Applicable (and Not Applicable) Information from the Provided Text:
| Aspect | Information from Document | Justification/Notes |
|---|---|---|
| 1. Acceptance Criteria & Reported Performance | Acceptance Criteria (Types of Tests): |
- Femoral/Tibial Constraint Testing (ASTM F1223)
- Contact Area/Contact Stress (ASTM F2083)
- Post Fatigue Testing
- Range of Motion Evaluation
- Wear (ISO 14243-3)
- Tibial Insert Modular Disassembly Strength (ASTM F1814)
- LAL testing requirements for orthopedic implants.
Reported Performance: "Testing and engineering analyses showed that the subject components met the pre-determined acceptance criteria identified in the Design Control Activities, demonstrating that the subject components perform as safe and effective compared to the predicate components, and is substantially equivalent to the predicate." | The document confirms that specific mechanical tests were performed against pre-determined acceptance criteria, and the device met these criteria. However, the quantitative values of the acceptance criteria (e.g., "must withstand X N without deformation") and the specific measured results from each test are not detailed in this summary. This is typical for a 510(k) summary, as the full detailed test reports are part of the confidential submission. The "reported device performance" is given as a qualitative statement of meeting the criteria. |
| 2. Sample Size & Data Provenance (for test set) | Not disclosed. | This relates to mechanical testing of physical parts, not a data-driven AI model. The number of physical components tested is not provided. Data provenance (e.g., country, retrospective/prospective) is not relevant for this type of non-clinical, in-vitro testing. |
| 3. Number & Qualifications of Experts for Ground Truth | Not applicable. | Ground truth in this context is established by objective engineering standards and measurements (e.g., ASTM, ISO), not by human expert consensus or labeling of data. |
| 4. Adjudication Method (for test set) | Not applicable. | Adjudication is relevant for resolving discrepancies in human interpretation to establish ground truth for AI algorithms. This is mechanical testing. |
| 5. MRMC Comparative Effectiveness Study | Not applicable. | This type of study evaluates the impact of AI on human reader performance for diagnostic tasks. The device in question is a physical knee implant. |
| 6. Standalone (Algorithm Only) Performance | Not applicable. | This refers to the performance of an AI algorithm independent of human interaction. The device is a physical implant, not an algorithm. |
| 7. Type of Ground Truth Used | Established engineering and material science standards (e.g., ASTM, ISO) and LAL testing. | The "ground truth" for evaluating the performance of the physical device components is based on well-defined and quantitative performance specifications derived from these industry-standard test methods to ensure mechanical integrity, biocompatibility, and safety. |
| 8. Sample Size for Training Set | Not applicable. | This refers to data used to train an AI model. This device is a physical implant, not an AI. |
| 9. How Ground Truth for Training Set was Established (If any) | Not applicable. | As there is no training set for an AI model, this question is not applicable. |
§ 888.3560 Knee joint patellofemorotibial polymer/metal/polymer semi-constrained cemented prosthesis.
(a)
Identification. A knee joint patellofemorotibial polymer/metal/polymer semi-constrained cemented prosthesis is a device intended to be implanted to replace a knee joint. The device limits translation and rotation in one or more planes via the geometry of its articulating surfaces. It has no linkage across-the-joint. This generic type of device includes prostheses that have a femoral component made of alloys, such as cobalt-chromium-molybdenum, and a tibial component or components and a retropatellar resurfacing component made of ultra-high molecular weight polyethylene. This generic type of device is limited to those prostheses intended for use with bone cement (§ 888.3027).(b)
Classification. Class II.