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The PREFERX Delivery System is intended to be used for the delivery of hydrated allograft, or synthetic bone graft material to an orthopedic surgical site.

The PREFERX Delivery System is a single use pre-sterilized and disposable system consisting of a Feeder including a CC Body, Stand, and Funnel; a Reduction Sleeve; a BC-Sleeve and BC-Sleeve Cap, used to load the graft material into the Biologic Cartridge. The Biologic Cartridge contains and delivers the graft material to the surgical site. A Plunger expresses the graft material from the Biologic Cartridge through an actuating trigger on the Gun that advances the Plunger down the length of the Biologic Cartridge via a ratcheting mechanism. The system is designed such that the Biologic Cartridge can be filled with the desired graft material, attached to the Gun and Plunger for use, then removed and refilled during the same procedure.

The Biologic Cartridge does not have a Luer lock mechanism; the device does not require a needle or similar attachment; the Biologic Cartridge contents being dispensed directly from the tip of the Biologic Cartridge into the graft site.

The device is packaged in a thermoformed tray with a Tyvek lid. Each tray is then packaged individually in an outer paperboard carton.

The PREFERX Delivery System is a single use pre-sterilized, disposable system intended to be used for the delivery of hydrated allograft, autograft, or synthetic bone graft material to an orthopedic surgical site.

The provided document is a 510(k) Summary for the PREFERX Delivery System. It describes the device, its intended use, and a comparison to a predicate device to establish substantial equivalence. However, this document does not contain explicit acceptance criteria tables for performance metrics or detailed study results demonstrating that the device meets such criteria.

The "Preformance data" section on page 4 primarily focuses on a risk analysis via FMEA and verification testing related to identified risks, rather than establishing specific performance acceptance criteria for typical AI/ML device metrics like sensitivity, specificity, or AUC. The device described, the PREFERX Delivery System, is a mechanical system for delivering bone graft material, not an AI/ML diagnostic or predictive tool.

Therefore, many of the requested elements for an AI/ML device are not applicable or present in this document. I will extract the information that is available and note when information is not provided.

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

1. A table of acceptance criteria and the reported device performance

As the PREFERX Delivery System is a mechanical device for delivering bone graft material, and not an AI/ML device, the typical performance metrics like sensitivity, specificity, or AUC with corresponding acceptance criteria are not relevant or reported in this document.

Instead, the document details a series of potential risks and the "Action Taken" (verification tests performed) to mitigate those risks, which implicitly serve as a form of performance validation for the identified failure modes.

Note: The "reported device performance" is not quantified with specific numerical targets for these actions (e.g., "burst strength > X MPa"). Instead, the document states that "Performance data, including worst-case scenario, was provided in support of the substantial equivalence determinations. ... The risks were reduced and are ranked as Acceptable. MD3 design control procedures, design verification and validation testing of the device were performed based on the results of the risk analysis." This implies that the tests were performed and the device passed the requirements, but the specific quantitative outcomes are not detailed in this summary.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

This information is not provided in the document. The general nature of the "Action Taken" suggests a series of engineering and laboratory tests rather than a clinical "test set" in the context of AI/ML evaluation.

3. 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)

This information is not applicable/provided. This device is a bone graft delivery system, not an AI/ML diagnostic tool requiring expert consensus for ground truth on medical data. The ground truth for the verification tests would be established by standard engineering and biocompatibility testing methodologies.

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

This information is not applicable/provided. Adjudication methods are typically used in clinical studies or for establishing ground truth for AI/ML performance evaluation, which is not the context here.

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

A Multi-Reader Multi-Case (MRMC) comparative effectiveness study is not applicable for this type of mechanical device and was not performed. The document explicitly states: "No clinical studies were performed."

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

This concept is not applicable as the PREFERX Delivery System is not an algorithm or AI device.

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

For the verification tests (e.g., biocompatibility, functionality, sterilization), the "ground truth" would be established by standard laboratory testing protocols and certifications against recognized industry standards (e.g., ASTM, USP, ISO). For example:

• Biocompatibility: Tests conform to ISO 10993 standards.
• Sterilization: Certification of Sterilization to a Sterility Assurance Level (SAL) of 10^-6.
• Dimensional accuracy: Compliance with specified engineering drawings and measurements.

8. The sample size for the training set

This information is not applicable/provided. There is no "training set" as this is not an AI/ML device.

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

This information is not applicable/provided as there is no "training set" for this device.

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