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The Deltronix Precision and SEG are a high frequency electrosurgical generators intended for use with monopolar and bipolar accessories for cutting and coagulating tissue.

The electrosurgical generators of Precision and SEG lines are intended to cut and electrosurgical coagulation of living human tissues. This objective is achieved through the power supply at high frequency. The electrosurgical generator of the Precision line may coagulate by using both monopolar technique and bipolar technique.

This is an electrosurgical generator device, not an AI/ML device. Therefore, the questions related to AI/ML device performance are not applicable.

Here's the relevant information extracted from the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

The document primarily focuses on demonstrating substantial equivalence to predicate devices based on technological characteristics and performance, rather than defining explicit acceptance criteria or presenting a standalone performance study with specific metrics. The "Performance" section in Table 5.1 compares output frequencies, waveform, channels, power output, voltage output, and crest factor between the subject devices and predicate devices.

The "acceptance criteria" here implicitly refer to the demonstration of comparable performance within a range considered safe and effective for electrosurgical generators, as evidenced by comparison to predicate devices. The document states: "The documentation submitted in this premarket notification demonstrates that the subject devices have comparable features and performance and, therefore, are substantially equivalent to the identified predicate devices."

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

Not applicable, as this is demonstrating substantial equivalence for an electrosurgical generator, not an AI/ML device that requires a test set of data. The evaluation is based on technical specifications and comparison to existing cleared devices.

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, as this is an electrosurgical generator, not an AI/ML device relying on expert-established ground truth from a test set.

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

Not applicable.

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, as this is not an AI-assisted device.

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

Not applicable, as this is an electrosurgical generator, not an algorithm.

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

Not applicable. The "ground truth" for this type of device lies in adherence to established performance standards for electrosurgical generators and demonstrating equivalence to legally marketed predicate devices through engineering and functional comparisons.

8. The sample size for the training set:

Not applicable, as this is an electrosurgical generator, not an AI/ML device that undergoes training.

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

Not applicable.

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The smoke evacuation rocker switch pencil and telescoping smoker switch pencil are intended for general electrosurgical applications, including cutting and coagulation, and for removing smoke generated by electrosurgery when used in conjunction with an effective smoke evacuation system. The pencil enables the operator to remotely conduct an electrosurgical current from the output connector of an electrosurgical unit to the operative site for the desired surgical effect.

The Valleylab™ Smoke Evacuation Rocker Switch Pencil family consists of sterile, single-use, hand-held monopolar electrosurgical instruments designed for use with compatible Covidien generators that include monopolar capabilities to cut and coagulate through tissue. They have a standard three-prong monopolar plug. The devices have an integrated smoke capture capability and are included with a default adapter that can aid in the connection to a smoke evacuation system. The adapter can be removed or replaced as needed to fit a variety of smoke evacuation systems. The proposed device family will be provided gamma sterilized. The proposed devices do not contain software.

The pencil family consists of standard and telescoping pencil models and associated accessories. The standard model is designed with a fixed smoke nozzle and electrode length, with the option for use with extender accessories (Valleylab™ Smoke Evacuation Extension Tube) and longer electrodes to access deeper spaces while maintaining smoke evacuation capabilities. The telescoping model has an independently telescoping smoke nozzle and electrode, allowing for a customizable configuration.

The provided text describes a 510(k) premarket notification for electrosurgical devices, not an AI/ML device. Therefore, the questions related to AI/ML specific acceptance criteria, study design, and performance metrics cannot be answered from the given document.

The document focuses on demonstrating substantial equivalence to a predicate device through non-clinical performance data, primarily related to safety and effectiveness of electrosurgical cutting, coagulation, and smoke evacuation.

However, I can extract information relevant to general device evaluation as presented:

1. Table of Acceptance Criteria and Reported Device Performance

Since this is a substantial equivalence determination for a medical device (electrosurgical pencil) and not an AI/ML diagnostic tool, the acceptance criteria are not in terms of traditional metrics like sensitivity, specificity, or AUC. Instead, they relate to established medical device standards and functional performance in comparison to a predicate device.

The following questions are not applicable or cannot be answered from the provided text as it pertains to a traditional medical device submission, not an AI/ML device.

2. Sample size used for the test set and the data provenance: Not applicable for an AI/ML model. The "test set" here refers to physical testing of prototypes.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable for an AI/ML model. Ground truth in this context would be physical measurements or standardized test results.
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable for an AI/ML model.
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. This device is an electrosurgical tool, not an AI diagnostic assistant.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done: Not applicable. The device has no standalone algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): For the performance data mentioned (biocompatibility, electrical safety, mechanical/functional, thermal effect), the "ground truth" would be objective measurements against established engineering standards and physical properties, not clinical diagnostic ground truth.
8. The sample size for the training set: Not applicable. There is no AI/ML model training set.
9. How the ground truth for the training set was established: Not applicable. There is no AI/ML model training set.

Summary of the study/performance evaluation presented:

The submission aimed to demonstrate substantial equivalence of the Valleylab™ Smoke Evacuation Rocker Switch Pencil family to its predicate device (Valleylab™ Smoke Evacuation Pencil, K103375). This was achieved through a series of non-clinical performance tests:

• Biocompatibility testing according to ISO 10993-1.
• Electrical safety and EMC testing complying with relevant IEC 60601 standards.
• Mechanical and functional testing to confirm performance against design requirements.
• Ex-vivo Monopolar Thermal Effect testing comparing the proposed device's thermal performance to the predicate device across various tissue types, power settings, and modes, using different electrosurgical generators.
• Human Factors and Usability testing in compliance with IEC 62366 to ensure safe and correct use.

No pre-clinical or clinical studies relying on "assessment of performance data" for substantial equivalence were conducted, as stated in the document. The overall conclusion was that the device is as safe and effective as the predicate based on the non-clinical performance documentation.

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