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This device is designed to be used whenever monopolar electrosurgery is indicated. The intended use of this device is to conduct monopolar electrosurgical energy from target tissue of a patient back to one or two electrosurgical units (ESU), or generators.

Electrosurgical use is restricted to use with isolated monopolar electrosurgical generators. The device is not intended for RF ablation.

The MegaSoft Universal Patient Return Electrode is constructed of a layer of conductive material strain-relieved with two sheets of urethane material, and sealed between two symmetric layers of a viscoelastic polymer called Akton® The Akton polymer is encapsulated by a layer of urethane film. One twoconductor cable connects the conductive layer of the device to a two conductor DetachaCable . The DetachaCable is connected to a standard monopolar electrosurgical unit (ESU). The device cable is insulated, strain-relieved, and connected well inside the device to prevent patient or user burns. In use, this device will lay on the operating surface with the patient lying on either side of the pad.

The pad size is approximately 36" x 20" x 0.135" and is intended for patients weighing ≥ 0.8 lb (350 grams).

The provided text is related to a 510(k) submission for a medical device called the "MegaSoft Universal Patient Return Electrode." It describes the device, its intended use, and its technological characteristics, and references adherence to voluntary safety standards (IEC 60601-1:2005 and IEC 60601-2-2:2009).

However, the document does not contain information about:

• Specific acceptance criteria with numerical targets.
• A detailed study proving the device meets acceptance criteria, including sample sizes, data provenance, expert qualifications, or adjudication methods for a test set.
• Standalone algorithm performance or comparative effectiveness studies (MRMC study) for an AI device. The described device is a physical electrode, not an AI/software device.
• Training set details for an AI model.

Therefore, many of the requested fields cannot be populated from the provided text. The device is a physical electrosurgical accessory, and the regulatory submission heavily relies on demonstrating equivalence to a predicate device and adherence to industry safety standards through testing, rather than a clinical effectiveness study with AI-specific metrics.

Here is what can be extracted based on the provided text, and noted where information is not available:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size: Not specified. The document states "Megadyne has conducted extensive testing" but does not detail the size or nature of what would constitute a "test set" in the context of device performance studies.
• Data Provenance: Not applicable in the context of clinical data provenance for an AI device. For hardware testing, typically in-house lab testing data would be generated.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Their Qualifications

• Not applicable. The device is a physical electrosurgical accessory. The "ground truth" for its safety and performance would be established through compliance with engineering standards and specific electrical/thermal measurements, not expert review of clinical data.

4. Adjudication Method for the Test Set

• Not applicable. See point 3.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size

• No. This is a physical electrosurgical return electrode, not an AI-assisted diagnostic or therapeutic device. Therefore, no MRMC study comparing human readers with and without AI assistance was performed.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study Was Done

• No. This is a physical medical device, not an algorithm.

7. The Type of Ground Truth Used

• The "ground truth" for this device's performance relies on engineering and safety standards compliance (e.g., current limiting thresholds, electrical safety requirements, thermal limits) as defined by IEC 60601-1 and IEC 60601-2-2, and demonstration of substantial equivalence to a previously cleared predicate device.

8. The Sample Size for the Training Set

• Not applicable. As a physical device, there is no "training set" in the context of machine learning or AI.

9. How the Ground Truth for the Training Set Was Established

• Not applicable. See point 8.

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