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IPC® System is indicated for the incision/cutting, removal, drilling and sawing of soft and hard tissue and bone, and biomaterials in Neurosurgical (Craniofacial), Orthopedic, Arthroscopic, Spinal, Sternotomy, and General surgical procedures.

The IPC® POWEREASE™ System is indicated for drilling, tapping and driving screws and working end attachments during spinal surgery, including open and minimally invasive procedures. It is also used in placement or cutting of screws, posts and rods.

The POWEREASE™ System Working Ends consists of instruments such as taps, drill bits, screwdrivers, post cutter, set screw break-off tool, reduction nut driver and sleeves. The working ends have a manual alternative. The working ends, listed above, are compatible with the CD HORIZON® SOLERA® and the TSRH® 3Dx Spinal System implants. Of the working ends, only the taps, screwdrivers, drill bits, and sleeves are also compatible with Medtronic's NIM-ECLIPSE® Spinal System.

The provided text is related to a 510(k) premarket notification for the Medtronic Sofamor Danek POWEREASE™ System, which is a surgical instrument system. The content describes the device, its intended use, and a comparison to a predicate device.

Crucially, this document focuses on demonstrating substantial equivalence to a predicate device, as is common in 510(k) submissions, rather than presenting a performance study with specific acceptance criteria and detailed results from a clinical or non-clinical trial against those criteria. Therefore, the requested information about acceptance criteria and a study demonstrating performance against them (especially clinical performance metrics like accuracy, sensitivity, specificity, etc.) is largely absent from this particular document.

Here's a breakdown of what can and cannot be answered from the provided text:

Acceptance Criteria and Reported Device Performance

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

The document does not provide a table of acceptance criteria with specific quantitative performance metrics (e.g., accuracy, sensitivity, precision) that the device must meet, nor does it present a structured report of the device's performance against such criteria.

Instead, the submission relies on demonstrating substantial equivalence to a previously cleared predicate device (POWEREASE™ System K111520). The "acceptance" in this context is based on the FDA's determination that the new device does not raise new questions of safety and effectiveness compared to the predicate.

The document states:

• "Engineering rationales, based on engineering theoretical analysis, were completed using testing that had been performed on the predicate device."
• "The predicate testing was in accordance with IEC 60601 for Medical Electrical Equipment."
• "Information and data to support these engineering rationales, as well as surgeon validations and internal verification activities, were provided to demonstrate that the subject devices are substantially equivalent to the predicate devices."

This indicates that the "performance" demonstrated is primarily focused on safety and functional equivalence to the predicate, often through bench testing, materials characterization, and adherence to relevant standards like IEC 60601 for electrical medical equipment (though the specific aspects of IEC 60601 are not detailed, it typically covers electrical safety, electromagnetic compatibility, and basic performance).

Study Details (Based on available information)

Given the nature of a 510(k) summary relying on substantial equivalence, the detailed study information typically associated with AI-driven devices or novel therapies (like sample size, expert ground truth, adjudication) is not present.

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

• Not Applicable / Not Provided: The document does not describe a test set or data provenance in the context of clinical performance evaluation (e.g., diagnostic accuracy, outcome prediction). The "testing" referred to is against the predicate device, likely involving bench testing and engineering analysis rather than a clinical dataset with "samples."

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)

• Not Applicable / Not Provided: This information is not relevant to this 510(k) submission, which focuses on hardware and mechanical/electrical safety and function, not a clinical diagnostic or AI-driven device requiring expert-labeled ground truth. The submission mentions "surgeon validations," but these are likely qualitative assessments of usability and function rather than establishing ground truth for performance metrics.

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

• Not Applicable / Not Provided: No such adjudication method is mentioned or implied, as there is no "test set" in the context of typical AI/diagnostic studies.

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

• Not Applicable / Not Provided: The device is a system of powered surgical instruments (drills, taps, drivers). It is not an AI-assisted diagnostic or therapeutic device, and therefore, an MRMC study comparing human readers with and without AI assistance is irrelevant and was not performed.

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

• Not Applicable / Not Provided: This device is a surgical instrument and does not have an "algorithm" in the context of AI or standalone diagnostic interpretation. Its function is directly human-controlled or assists a human surgeon.

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

• Not Applicable / Not Provided: For this type of mechanical surgical device, "ground truth" would relate to engineering specifications, material properties, mechanical integrity, and functionality, verified through engineering analysis and bench testing, rather than clinical outcome data or expert consensus on a diagnostic interpretation.

8. The sample size for the training set

• Not Applicable / Not Provided: There is no "training set" as this device does not involve machine learning or AI algorithms requiring data for training.

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

• Not Applicable / Not Provided: As there is no training set, this question is not applicable.

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