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The CONMED PlumeSafe® X5™ Smoke Management System is designed to remove and filter smoke and aerosols from a surgical site produced during electrosurgical and laser procedures.

The PlumeSafe® X5™ Smoke Management System is a portable, stand-alone, capital unit, that when paired with a reusable filter and disposable accessories makes up a Smoke Management System. The smoke unit is accompanied by a reusable filter and is available in two different configurations, a 22mm or 25mm size. Each filter is designed to capture components of surgical smoke and return clean air to the environment and can connect to different accessories which include pencils, adapters, fluid traps, and tube sets. Each filter is a seff-contained device that is completely enclosed to protect health care personnels from potential contamination during filter changes. Each filter is comprised of filtration (gross particulate pre-filter, Ultra-Low Penetration Air (ULPA), coconutbased carbon, impregnated alumina, and carbon dust capture media) that produce capture efficiency ratings equal to or better than 99.999% for particles ranging in size from 0.01μm to 0.2μm.

PlumeSafe® X5™ is comprised of a vacuum motor, aluminum, steel, and plastic components combined with sound reducing insulation. The vacuum motor is used to draw the surgical site, through an accessory, and into the PlumeSafe® X5™ filter. The PlumeSafe® X5™ Smoke Management System provides multiple modes (open, laparoscopic, and pencil) and settings to adjust the flow to the clinical need.

Here's a breakdown of the acceptance criteria and study information for the CONMED PlumeSafe® X5™ Smoke Management System, based on the provided FDA 510(k) summary:

1. Table of Acceptance Criteria and Reported Device Performance:

2. Sample size used for the test set and the data provenance:

• The document describes "benchtop testing" and "non-clinical performance testing." These are physical device tests, not tests on a clinical dataset.
• Therefore, there is no "test set" in the sense of a collection of patient data or images. The "samples" would be the physical devices, filters, and components themselves, tested under specific laboratory conditions.
• The provenance of data is not applicable in the context of clinical data, as this is solely benchtop testing.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

• This question is not applicable. "Ground truth" in the context of expert review typically refers to a clinical diagnosis or labeling of medical images/data. Since this is benchtop device testing, there is no "ground truth" established by clinical experts for a test set. The acceptance criteria are based on engineering specifications and international standards, and the "ground truth" is measured by laboratory equipment and procedures.

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

• This question is not applicable. Adjudication methods are used for resolving discrepancies in expert interpretations of clinical data. For benchtop testing, results are typically objective measurements against predefined thresholds, not subjective interpretations requiring adjudication.

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:

• No, a multi-reader multi-case (MRMC) comparative effectiveness study was not conducted. This device is a smoke management system, not an AI-powered diagnostic tool. The testing performed is related to the physical performance and safety of the device in filtering smoke and aerosols.

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

• This question is not applicable. The device is a physical smoke management system, not an algorithm or software that operates standalone for diagnostic or interpretive purposes. Its performance is measured independently of human interaction in terms of its ability to filter air, maintain flow, etc., but this is inherent to the device's function, not "standalone algorithm performance."

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

• For the benchtop tests, the "ground truth" is established by adherence to recognized international standards (e.g., ISO, IEC, ASTM) and engineering specifications. The performance metrics (e.g., efficiency, flow rates, sound levels, motor lifetime) are objectively measured using calibrated laboratory equipment. There is no clinical "ground truth" in the form of expert consensus, pathology, or outcomes data for this type of device testing.

8. The sample size for the training set:

• This question is not applicable. The device is a hardware product, not a machine learning model; therefore, there is no "training set" in the context of artificial intelligence.

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

• This question is not applicable, as there is no training set for this device.

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CONMED CleanSeal Vessel Sealers are intended to be used in open and mimimally invasive procedures for the ligation and division of tissue bundles, lymphatics, and vessels up to and including 6 mm vessels (arteries, veins, pulmonary arteries, pulmonary veins). The handpiece is indicated for use in gynecological and general surgical procedures, including urologic, thoracic, and vascular. These procedures include, but are not limited to, hysterectomies, colectomies, Nissen fundoplication, and adhesiolysis. CleanSeal vessel sealer has not been shown to be effective for ubal sterilization or tubal coagulation for sterilization procedures. Do not use CleanSeal vessel sealer for these procedures.

CleanSeal Advanced Bipolar Vessel Sealer Maryland is designed to be used, with a compatible MEP-1 electrosurqical generator, in open and minimally invasive procedures for the ligation and division of tissue bundles, lymphatics, and vessels up to and including 6 mm arteries and veins. They are sterile, single use bipolar vessel sealing hand pieces featuring double action non-stick coated jaws, three shaft length options, a one-hand controlled handle with latchable lever. The instrument creates a seal by application of radio frequency (RF) electrosurgical energy to vascular structures or tissue bundles interposed between the jaws.

The provided text describes a 510(k) premarket notification for a medical device called "CleanSeal Advanced Bipolar Vessel Sealer Maryland." This document is a regulatory submission to the FDA, demonstrating the device's substantial equivalence to previously cleared predicate devices.

However, the information provided does not contain any details about acceptance criteria, study design for a test set, sample sizes for training or test sets, number/qualifications of experts, adjudication methods, MRMC studies, standalone performance, or ground truth establishment relevant to AI/ML device performance.

The document primarily focuses on:

• Device Description and Intended Use: Explains what the device is, how it works, and its surgical applications for sealing and dividing tissue and vessels.
• Performance Testing: Mentions that the device has been tested according to FDA guidance for electrosurgical devices.
• Biocompatibility Testing: States that biocompatibility testing was conducted and met acceptance criteria.
• Chronic Animal Studies: Describes two chronic animal studies (porcine and canine models) comparing the performance of the CleanSeal Maryland with its predicate devices for effective vessel sealing. These are biological/physiological studies, not studies of an AI/ML algorithm's performance.
• Shelf Life Study: Indicates a shelf-life study was performed.
• Substantial Equivalence Argument: Compares the new device's features (Model numbers, intended use, polarity, dimensional design, rated voltage, shelf-life, sterilization method, and disposability) to its predicate and reference devices to argue for substantial equivalence.

Therefore, based solely on the provided text, it is not possible to describe the acceptance criteria and the study that proves the device meets those criteria in the context of an AI/ML device. The document refers to a physical electrosurgical device, and the "performance testing" and "chronic animal studies" relate to its mechanical and biological effectiveness, not an AI/ML algorithm's analytical performance on data.

If this device were an AI/ML device, the required information (acceptance criteria for AI metrics, test set details, ground truth, etc.) would be explicitly mentioned in sections describing its software performance and validation. Since those details are absent, it confirms that this is not an AI/ML device submission from which such information could be extracted.

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