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The SISS Inc. (d.b.a. MediSISS) Reprocessed electrosurgical instruments have applications in a variety of minimally invasive surgical procedures to manipulate and manage internal soft tissue by grasping, cutting, and/or to facilitate coagulation. transection, resection, mobilization, and dissections of tissue.

Reprocessed Electrosurgical Instruments mav consist of hand-manipulated devices with electrocautery capability and with or without rotation capability. The distal end of the Ethicon device consists of a scissor distal end configuration. The U.S Surgical device consists of a dissector distal end configuration. The devices are designed to be inserted through an appropriately sized trocar sleeve or cannula. The end effectors are operated by the handpiece handles may be designed to be suppressed and released to activate the instruments end-effector. The device's insulated shaft may be designed to (depending on the device model and type) be rotated (up to 360") either direction (using a knob on the handle.)

This document describes the validation and acceptance criteria for reprocessed electrosurgical instruments by SISS Inc. (d.b.a. MediSISS). This is NOT a study of an AI/ML device, but rather a submission for a 510(k) premarket notification for a medical device. Therefore, many of the requested categories related to AI/ML studies are not applicable.

Here's a breakdown of the requested information based on the provided document:

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

The document does not provide a table with specific quantitative acceptance criteria or detailed numerical performance metrics for individual reprocessed instruments. Instead, it relies on demonstrating substantial equivalence to legally marketed predicate devices and compliance with established standards.

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

The document mentions "representative samples of reprocessed electrosurgical instruments underwent bench testing." It does not specify the exact sample size for these tests. The provenance of the data is prospective, as it involves testing of the reprocessed devices themselves. The country of origin for the testing is not explicitly stated but can be inferred as the U.S. where the company is based and seeking FDA approval.

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)

This is not applicable to this type of device submission. The "ground truth" for reprocessed medical instruments is typically established through adherence to validated cleaning, sterilization, and functional performance protocols, and comparison to validated predicate devices, rather than expert consensus on individual "cases."

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

This is not applicable. Adjudication methods like "2+1" or "3+1" are characteristic of human evaluation of data, often in clinical trials or image interpretation studies, which are not described here. The evaluation of reprocessed instruments primarily involves engineering and microbiological testing.

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

This is not applicable. This submission is for a physical medical device (reprocessed electrosurgical instruments), not an AI/ML diagnostic or assistive tool. Therefore, MRMC studies are irrelevant.

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

This is not applicable. This is not an algorithm or software device.

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

The "ground truth" in this context is the established performance, safety, and effectiveness of the original, legally marketed predicate devices, as well as compliance with relevant international standards for medical device reprocessing (cleaning, sterilization, biocompatibility). It also includes the manufacturer's own validated internal functional and mechanical testing results. The goal is to demonstrate that the reprocessed devices meet these established benchmarks.

8. The sample size for the training set

This is not applicable. There is no "training set" in the context of reprocessed physical medical instruments as there's no AI/ML algorithm being developed or trained.

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

This is not applicable as there is no training set.

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The SISS Inc. (d.b.a. MediSISS) Reprocessed electrosurgical instruments have applications in a variety of minimally invasive surgical procedures to manipulate and manage internal soft tissue by grasping, cutting, and/or to facilitate coagulation, transection, resection, mobilization, and dissections of tissue.

Reprocessed Electrosurgical Instruments may consist of hand-manipulated devices with electrocautery capability and with or without rotation capability. The handpiece handles are connected to the distal end-effector by a narrow-diameter insulated barrel or shaft. The distal end of the device consists of a variety of distal end configurations including: dissectors (straight or curved), graspers, scissors (curved, hooked, or metzenbaum), shears, and cutting or dissecting forceps. The devices may be monopolar, bipolar, or tripolar. The devices are designed to be inserted through an appropriately sized trocar sleeve or cannula. If the instrument has a scissor or jaw end-effector these are opened and closed using the handles. The device's insulated shaft may be designed to (depending on the device model and type) be rotated (up to 360°) either direction (using a knob on the handle.) The jaws of some models may be rotated by manipulating controls on the handpiece. Grasper and clamp models may have manipulating jaws operated at the handpiece to lock and hold tissue.

The provided text describes a 510(k) premarket notification for reprocessed electrosurgical instruments. This type of submission relies on demonstrating substantial equivalence to a legally marketed predicate device, rather than extensive clinical efficacy studies with specific acceptance criteria as would be found for novel devices or AI/software as a medical device (SaMD).

Therefore, many of the requested categories for acceptance criteria and study details are not applicable (N/A) in this context, as the focus is on process validation and demonstrating that the reprocessed device performs identically to its original counterpart.

Here's the breakdown based on the provided text:

Acceptance Criteria and Device Performance

Study Details

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

   • Sample Size: The document mentions "Representative samples of reprocessed electrosurgical instruments underwent bench testing." However, a specific numerical sample size for the test set is not provided.
   • Data Provenance: The testing appears to be internal "bench testing" conducted by SISS Inc. (d.b.a. MediSISS) in the US, as part of their manufacturing and re-processing validation. It is prospective as it's part of a manufacturing validation process.

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

   • N/A. This type of study (demonstrating substantial equivalence for reprocessed medical devices) does not typically involve expert review for ground truth in the same way an AI/CADe system would. The ground truth here is derived from objective measurements against established specifications for electrosurgical instrument function, cleaning, and sterilization.

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

   • N/A. Adjudication methods are typically relevant for subjective assessments or discrepancy resolution in clinical trials or expert-labeled datasets. This premarket notification relies on objective bench testing and compliance with standards.

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:

   • N/A. This is a reprocessed medical device, not an AI/CADe system. No human reader studies or AI assistance are involved.

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

   • N/A. This is a reprocessed medical device, not an algorithm or AI system.

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

   • The ground truth is based on objective performance specifications and compliance with recognized standards (e.g., ISO for sterilization and biocompatibility) for electrosurgical instruments, along with visual and mechanical factory acceptance testing. The "truth" is that the reprocessed device functions identically and safely (e.g., cleaned, sterile, biocompatible) to the original predicate device.

7. The sample size for the training set:

   • N/A. This device does not involve machine learning or AI, so there is no "training set." The reprocessing "process validation" itself is akin to a training phase in a manufacturing context, ensuring the process consistently yields acceptable products.

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

   • N/A. As there is no AI training set, this is not applicable. The "ground truth" for the reprocessing process validation was established by adherence to industry standards and internal quality control specifications for device functionality, cleanliness, and sterility, verified through scientific methodologies like sterilization validation protocols.

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