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The ActivOrtho Nitinol Compression Screw System is indicated for use in bone reconstruction, osteotomy, arthrodesis, joint fusion, fracture repair and fracture fixation of small bones and small bone fragments.

The ActivOrtho Nitinol Compression Screw System includes cannulated, partially threaded bone screws having a 4mm diameter in a variety of lengths to accommodate various applications.

This is a 510(k) premarket notification for a medical device, not a study evaluating device performance against acceptance criteria using AI or human readers. Therefore, much of the requested information regarding acceptance criteria, study design, expert ground truth, and AI-related metrics is not applicable to this document.

However, I can extract the relevant information available:

Acceptance Criteria and Reported Device Performance

The document does not explicitly state "acceptance criteria" in the format of a table with numerical targets. Instead, it describes performance testing conducted to demonstrate substantial equivalence to predicate devices. The "reported device performance" is described qualitatively as meeting the standards.

The "Acceptance Criteria" here are inferred from the description of the performance data section, which lists the types of testing performed and the ASTM standards followed. The "Reported Device Performance" summarizes the findings as described in the document, without providing specific numerical results, but asserting that the tests demonstrate equivalency.

Study-Specific Information:

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

   • The document states "Torsional properties, driving torque and axial pullout strength testing was performed on a worst case device according to ASTM F543." This implies a very small sample size, potentially N=1, for each mechanical test, focusing on the most challenging configuration. The exact number of devices tested is not specified beyond "a worst case device."
   • Data Provenance: Not specified, but generally, such bench testing would be conducted in a laboratory environment, likely within the manufacturer's or a contracted testing facility. No information on country of origin of data or whether it was retrospective or prospective in a clinical sense.

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

   • This information is not applicable to this type of regulatory submission. The "ground truth" for mechanical testing is established by the specified ASTM test methods and a pass/fail criterion based on pre-defined engineering specifications or comparison to predicate device performance. It does not involve human expert interpretation of device performance in a clinical context.

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

   • This is not applicable. Mechanical and corrosion testing adheres to predefined standard protocols (ASTM F543, ASTM F2129). The results are quantitative measurements, not subjective interpretations requiring adjudication.

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:

   • This is not applicable. This document describes the substantial equivalence of a physical medical implant (Nitinol Compression Screw System) through bench testing. It does not involve AI, image analysis, or human readers.

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

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

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

   • The "ground truth" for this submission is based on engineering specifications and established ASTM standards for mechanical and material properties. The device's performance is compared against these standards and the known performance of predicate devices to establish substantial equivalence. It is not based on expert clinical consensus, pathology, or outcomes data, as this is a 510(k) for an implantable device, not a diagnostic or prognostic tool.

7. The sample size for the training set:

   • This is not applicable. This device submission does not involve machine learning or a "training set."

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

   • This is not applicable. This device submission does not involve machine learning or a "training set."

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