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The OSSTEM Implant System - Abutment is intended for use with a dental implant to provide support for prosthetic restorations such as crowns, bridges, or overdentures.

The OSSTEM Implant System - Abutment is intended for use as an aid in prosthetic restoration. It consists of Abutments, components and Abutment Screws.

This document is a 510(k) Premarket Notification of the OSSTEM Implant System - Abutment, indicating it is a dental device and not an AI/ML medical device. Therefore, the information requested in the prompt, which pertains to the acceptance criteria and study proving an AI/ML device meets those criteria, cannot be fully provided from this document.

The document discusses the substantial equivalence of the OSSTEM Implant System - Abutment to predicate devices. This typically involves demonstrating that the new device is as safe and effective as a legally marketed predicate device, often through material comparisons, design comparisons, and performance testing for mechanical properties and biocompatibility, rather than clinical studies or performance against defined efficacy metrics tied to patient outcomes.

However, I can extract information related to the device and the type of testing performed that is relevant to its acceptance for market.

Here's a breakdown based on the provided text, addressing the points of your prompt where applicable, and highlighting what's not present due to the nature of the device:

Device Description: The OSSTEM Implant System - Abutment is intended for use with a dental implant to provide support for prosthetic restorations such as crowns, bridges, or overdentures. It consists of Abutments, components, and Abutment Screws.

Acceptance Criteria and Device Performance (General):
For this type of device, "acceptance criteria" revolve around demonstrating substantial equivalence to existing, legally marketed predicate devices. This means proving the new device is as safe and effective as the predicate. The performance is assessed through:

• Material composition: Comparing the materials used (e.g., Titanium Alloy, Zirconia, PEEK, PC, POM).
• Design and dimensions: Comparing the shapes, diameters, and lengths.
• Intended use: Confirming the device serves the same purpose.
• Technological characteristics: Ensuring the fundamental mechanism of action is similar.
• Nonclinical testing: Biocompatibility, sterilization validation, and mechanical properties.

Table of Acceptance Criteria and Reported Device Performance (as inferred from a 510(k) for a non-AI/ML device):

Here's how the remaining points of your prompt are addressed:

1. Sample sized used for the test set and the data provenance:

   • Test set sample size: Not applicable in the context of an AI/ML algorithm's test set. The "testing" here refers to nonclinical lab tests and comparison to predicates.
   • Data provenance: Not directly applicable. The "data" are internal company reports demonstrating compliance with standards or comparisons to their own previously cleared devices. The manufacturer is OSSTEM Implant Co., Ltd. and their correspondent is HIOSSEN Inc., based in Republic of Korea and Pennsylvania, USA, respectively. The data are typically generated in a prospective manner for regulatory submission (i.e., tests are performed specifically for the submission).

2. 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 physical medical device, not an AI/ML algorithm requiring ground truth from experts for image interpretation or diagnosis.

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

   • Not applicable. This concept pertains to consolidating expert opinions for ground truth in AI/ML performance studies.

4. 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 MRMC study was done, as this is not an AI/ML device. The document explicitly states: "No clinical studies are submitted." (page 12)

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

   • Not applicable, as this is not an AI/ML device.

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

   • Not applicable. For this device, "ground truth" is embodied by established engineering specifications, material properties, and performance benchmarks for dental implants, which are verified through nonclinical laboratory testing against international standards (e.g., ISO, ASTM) and comparison to predicate device characteristics.

7. The sample size for the training set:

   • Not applicable. There is no concept of a "training set" for this type of conventional physical device.

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

   • Not applicable. (See #7).

Summary of Acceptance:

The device's acceptance (clearance) by the FDA is based on demonstrating substantial equivalence to existing predicate devices (listed in section 3 and 6) in terms of:

• Indications for Use: Identical.
• Technological Characteristics: Very similar, with minor differences in design/dimensions that do not raise new safety/effectiveness concerns.
• Materials: Identical.
• Performance (Nonclinical): Biocompatibility is leveraged from predicate devices; sterilization validated according to relevant ISO standards.

The document explicitly states: "No clinical studies are submitted." This reinforces that the acceptance was based on nonclinical testing and comparison to predicates, as is common for many Class II medical devices in the 510(k) pathway.

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