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The s-Clean TiN Coating Abutments is an endosseous dental implant that is indicated for surgical placement in the upper and lower jaw arches, to provide a root for single or multiple-units prosthetic appliance attachment to restore a patient's chewing function. Implants can be placed with a conventional two stage surgical process with an option for transmucosal healing or they can be placed in a single stage surgical process for immediate loading when good primary stability has been achieved and with appropriate occlusal loading.

The s-Clean TiN Coating Abutments are device made of pure titanium and titanium alloy intended for use as an aid in prosthetic restoration. The system consists of s-Clean TiN Half Coating Angled Abutment, s-Clean TiN Half and partial Coating Couple Abutment, s-Clean TiN Half Coating Free Abutment, s-Clean TiN Half Coating FreeMill Abutment, s-Clean TiN Half Coating MOA Abutment, s-Clean TiN Partial Sub-Octa Abutment, s-Clean TiN Partial Coating Sole Abutment, s-Clean DOA Ball Abutment, s-Clean DOA Snap Abutment, and s-Clean Sole Abutment Healing Cap. The surface of the abutments is partially or half TiN Coated by using PVD (Physical Vapor Deposition). The subject device is provided non-sterile and should be sterilized before use (End user sterilization).

This document is a 510(k) summary for a dental implant abutment, and as such, it focuses on demonstrating substantial equivalence to existing predicate devices rather than proving the device meets acceptance criteria through a standalone clinical study with detailed performance metrics.

Therefore, many of the requested sections (e.g., sample size for test set, number of experts, adjudication methods, MRMC studies, standalone performance, training set details) are not applicable to this type of submission. The information provided heavily relies on non-clinical testing and comparison to predicates.

Here's a breakdown of the available information based on your request:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria here are based on meeting the requirements of specific international and FDA guidance standards for medical devices, particularly for dental abutments. The reported device performance is that these tests were met.

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

• Not Applicable (N/A) for clinical data. This submission relies on non-clinical (laboratory) testing, not a clinical test set with patient data.
• The non-clinical tests (biocompatibility, fatigue, sterilization) are laboratory-based and would use a sample size appropriate for those specific engineering and biological tests, but this detail is not provided. The data provenance for these tests would be internal laboratory testing by the manufacturer or a contracted lab.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

• N/A. As mentioned, this is a non-clinical submission. Ground truth, in the context of clinical studies and expert consensus, is not relevant here. Decisions are made based on adherence to engineering and biocompatibility standards.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set

• N/A. No clinical test set requiring expert adjudication was conducted or described.

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

• N/A. This is a dental implant abutment, not an AI-powered diagnostic or assistive device. MRMC studies are not relevant here.

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

• N/A. This is a physical medical device (dental abutment), not an algorithm or AI system.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

• For the non-clinical tests, the "ground truth" is defined by the validated and accepted international standards (e.g., ISO, ANSI/AAMI) for mechanical performance and biocompatibility. Passing these tests according to the established metrics within the standards constitutes meeting the "ground truth" of safety and performance.

8. The sample size for the training set

• N/A. There is no "training set" as this is not a machine learning or AI product.

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

• N/A. There is no "training set" as this is not a machine learning or AI product.

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