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The XPS Nexus™ System is indicated for the incision/cutting, removal and drilling of soft and hard tissue and bone in head and neck/ENT, oral/maxillofacial and plastic/reconstructive/aesthetic surgical procedures.

The XPS Nexus™ System is a powered microdebrider and drill system that removes soft tissue, hard tissue and bone during surgical procedures. The system consists of a power control console, a foot control unit and assorted hand-pieces to drive various burs, blades, drills, rasps and cannulas. Hand-piece options include the StraightShot® M2 Microdebrider, the StraightShot® M4 Microdebrider and the Indigo® Otology Drill. The power control console also includes integrated irrigation pump for irrigation of blades and burs. Optional accessories include an IV pole to hold a bag(s) of irrigation solution as well as a carrying case.

The provided document is a 510(k) summary for the Medtronic Xomed, Inc. XPS Nexus System. This type of submission is for demonstrating substantial equivalence to a legally marketed predicate device, rather than proving novel effectiveness. Therefore, the device is not an AI/ML powered device, and the information requested (acceptance criteria, study details, sample sizes, expert involvement, etc., in the context of an AI/ML device) is not directly applicable or available in this document.

However, I can extract the types of testing performed and the standards met, which serve as "acceptance criteria" for this conventional medical device's safety and performance in the context of a 510(k) submission.

Here's a breakdown of the available information, reframed to address the spirit of your request where possible, but highlighting that this is not an AI/ML device study:

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

For a conventional medical device like the XPS Nexus System, "acceptance criteria" typically refer to compliance with recognized standards for safety and fundamental performance. The reported "device performance" in a 510(k) for such a device is demonstrated by meeting these standards and showing equivalence to predicate devices.

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 document describes engineering and regulatory compliance testing rather than clinical or AI/ML performance testing involving patient data. For electrical, EMC, software, and general performance testing, a "sample size" of patient data is not applicable. The samples would be the device units tested, but the number is not specified.

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 and not provided. "Ground truth" established by experts is relevant for AI/ML diagnostic or prognostic devices that interpret medical data. This device is a surgical drill system; its "ground truth" relates to its mechanical and electrical function as per engineering specifications, not expert interpretation of medical images or patient outcomes.

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

This information is not applicable and not provided. Adjudication methods like 2+1 are typically used in clinical studies or AI/ML evaluations where there's disagreement among human readers or between AI and human readers. This document details engineering compliance testing.

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

This information is not applicable and not provided. MRMC studies are used for evaluating the impact of AI on human reader performance, typically in diagnostic imaging. This device is a surgical drill and does not involve "human readers" interpreting data with or without AI assistance.

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

This information is not applicable and not provided. This device is a physical surgical tool and does not involve a standalone algorithm for performance evaluation in the context of AI.

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

For this device, the "ground truth" would be established by engineering specifications, validated test methods (e.g., measuring power output, torque, temperature, electrical leakage), and compliance with the recognized consensus standards listed (e.g., IEC 60601 series). It's a functional "ground truth" based on physics and engineering, not medical interpretation or pathology.

8. The sample size for the training set

This information is not applicable and not provided. Training sets are used for machine learning models. This is a conventional medical device.

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

This information is not applicable and not provided.

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