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The Zimmer Zfx Titanium Abutment for NobelActive Implant System is designed for use as a terminal or intermediate abutment for cement retained prostheses. The abutment can be used with NobelActive and NobelReplace Conical Connection implants with a Narrow Platform (NP) Ø 3.5mm or Regular Platform (RP) Ø 3.9mm

The Zimmer Zfx Titanium Abutment for the NobelActive Implant system is designed for use with NobelActive and NobelReplace Conical Connection endosseous dental implants to support single or multi tooth restorations. The abutment/implant interface is an internal conical connection with a hexagonal interlock.

The Zimmer Zfx Titanium Abutment for NobelActive Implant System is a patient specific dental implant abutment with a competitor compatible interface. The purpose of a Patient-Specific abutment is to satisfy customer needs that are otherwise difficult to meet with off-the-shelf abutments. They can be manufactured in multiple sizes, shapes, and angles within the limits established in this submission. They frequently incorporate the modifications typically done at a dental laboratory or "chair-side" by a dentist. Traditional methodologies require the customer (dentist/laboratory technician) to begin with a "stock" abutment and use manual subtractive techniques to remove material from this original "stock" design. However, a Patient-Specific abutment will incorporate these same modifications desired by the customer (dentist/laboratory technician) at the time of fabrication at the manufacturing facility.

The engineering drawings list ranges in areas (attributes) of the abutment that may be modified depending upon patient-specific needs.

The abutment is composed of Titanium alloy (Ti6Al4V), and is secured to the implant with a separate Titanium alloy screw for retention.

The new abutments will all be available with a choice of 3.5mm and 3.9mm implant platform diameters.

This is a premarket notification for a dental abutment, a mechanical component, not an AI/ML device, therefore, the requested information regarding acceptance criteria and studies are not applicable in the context of AI/ML.

Here's why and what information is available about the non-clinical testing:

Device Type: The device is a "Zimmer Zfx Titanium Abutment for NobelActive Implant System," which is an endosseous dental implant abutment. This is a physical, mechanical medical device.

Absence of AI/ML Specifics: The document describes the materials, design, indications for use, and non-clinical testing (mechanical and compatibility) for this physical component. There is no mention of artificial intelligence, machine learning, or any software-based diagnostic or predictive capabilities. Therefore, criteria such as "acceptance criteria and the study that proves the device meets the acceptance criteria" in the context of AI/ML (e.g., sensitivity, specificity, AUC) are not relevant here.

However, I can extract information related to the non-clinical testing performed to determine substantial equivalence as described in the document:

The non-clinical testing aimed to support the decision of substantial equivalence to predicate devices, focusing on fit, function, and safety of the mechanical component.

1. Table of Acceptance Criteria and Reported Device Performance (as pertains to non-clinical testing for a mechanical device):

2. Sample size used for the test set and the data provenance:

• Mechanical Fatigue Testing: The document states "fatigue testing was completed using Zimmer fabricated abutments assembled to OEM implants." No specific sample size (N) for the number of abutments or implants tested is provided in this summary.
• Data Provenance: The testing was conducted by Zimmer Dental Inc. in support of their 510(k) submission. It is internal testing performed by the manufacturer. It is retrospective in the sense that it was done to support a pre-market submission, not ongoing clinical data collection.
• MRI Compatibility: Implied to be laboratory testing rather than patient data.

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 mechanical device evaluation, not an expert-driven diagnostic assessment. Ground truth is based on engineering specifications and physical test results against established standards.

4. Adjudication method for the test set:

• Not applicable for a mechanical device. The "adjudication" is through physical testing results and engineering analysis.

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 device is not an AI/ML diagnostic tool and thus does not involve "human readers" or "AI assistance."

6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:

• Not applicable. This is a physical device, not an algorithm.

7. The type of ground truth used:

• Compatibility & Dimensional Fit: Engineering drawings, physical measurements of predicate devices, and established dimensional tolerances.
• Mechanical Fatigue Testing: Industry standards (FDA guidance Class II Special Controls Guidance Document: Root-form Dental Implants and Endosseous Dental Implant Abutments) and performance data from legally marketed predicate devices.
• Sterilization: Regulatory standards for Sterility Assurance Level (SAL) of 10^-6.
• MRI Compatibility: FDA guidance: Establishing Safety and Compatibility of Passive Implants in the Magnetic Resonance (MR) Environment.

8. The sample size for the training set:

• Not applicable. This is not an AI/ML device that requires a training set. The "design input" could be considered analogous, which would include the engineering specifications and reverse-engineered dimensions from predicate devices.

9. How the ground truth for the training set was established:

• Not applicable. No training set is used for this type of device. The design specifications were derived from reverse engineering existing compatible systems and industry standards.

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