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Single-use hand-switching electrosurgical accessory handpiece used in conjunction with an electrosurgical generator for delivery of RF electrosurgical current through an electrode for cutting and coagulation at the operative site.

This pencil has applications in general surgical procedures to provide a means of cutting and coagulation using electrosurgical current. The device consists of a cable for connection to the output of an electrosurgical generator unit, to carry high-frequency (HF) electrosurgical current to an electrode tip at the distal end of the handpiece is provided with various electrode types and cable lengths and acts as a hand-switching conduit in delivering the HF energy from the electrosurgical generator unit through an electrode to produce the therapeutic affect. Current is activated by the cut/coagulation switching element buttons on the handpiece. The devices will be distributed sterile for single-use applications.

The provided text describes a 510(k) premarket notification for a Disposable Electrosurgical Pencil, not a study evaluating acceptance criteria or device performance in the way typically expected for an AI/ML medical device. This document is a regulatory submission for a traditional medical device (electrosurgical pencil) and focuses on demonstrating substantial equivalence to a predicate device based on technological characteristics and compliance with existing standards.

Therefore, many of the requested categories (e.g., sample size for test set, number of experts, MRMC study, standalone performance, training set details) are not applicable to this type of device and submission. There isn't an "AI" component, a "ground truth" to establish, or a "performance" to measure in the context of an AI/ML algorithm.

However, I can extract information related to acceptance criteria and the study (or rather, the basis of the submission) that proves the device meets typical regulatory acceptance for this type of product.

Acceptance Criteria and Device Performance (Adapted for Electrosurgical Pencil)

Since this is a substantial equivalence submission for a traditional electrosurgical pencil, the "acceptance criteria" are primarily related to meeting established safety and performance standards and demonstrating that its technological characteristics and intended use are the same as a legally marketed predicate device. The "performance" is implicitly deemed acceptable if these standards are met and equivalence is shown.

Here's an adapted table:

Explanation of the "Study that proves the device meets the acceptance criteria":

The "study" in this context is the 510(k) Premarket Notification process itself. For traditional medical devices like this electrosurgical pencil, demonstrating "substantial equivalence" to a predicate device is the primary mechanism for market clearance. This involves:

• Comparison of technological characteristics: Showing that the new device has the same technological characteristics (e.g., materials, design, energy output, physical dimensions, sterilization method) as a predicate device, or that any differences do not raise new questions of safety and effectiveness.
• Compliance with consensus standards: Demonstrating that the device has been designed to meet recognized consensus standards for safety and performance (as listed above: ANSI/AAMI HF-18, IEC 60601-2-2, ISO 11137, ISO 10993). This compliance generally involves verification and validation testing performed by the manufacturer, which is summarized and attested to in the 510(k) submission, even if detailed test reports are not included in the provided summary.

Information Not Applicable/Not Present in the Provided Text for an AI/ML Context:

1. Sample size used for the test set and the data provenance: Not applicable. There is no "test set" of diagnostic images/signals for an AI algorithm. The "testing" involves engineering verification and validation against device specifications and regulatory standards.
2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. There is no diagnostic "ground truth" to be established for an electrosurgical pencil's performance other than its physical and electrical properties.
3. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable.
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: Not applicable. This device does not involve human "readers" or AI assistance in interpretation.
5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.
6. The type of ground truth used (expert consensus, pathology, outcomes data, etc): Not applicable. The "ground truth" for this device relates to its adherence to engineering specifications and safety standards.
7. The sample size for the training set: Not applicable. There is no AI model to train.
8. How the ground truth for the training set was established: Not applicable.

In summary: The provided documentation is for a conventional medical device seeking market clearance through substantial equivalence, not an AI/ML-powered device. Therefore, the detailed questions about AI model testing and validation methodologies are not relevant to this specific submission.

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