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The Medline ReNewal Reprocessed ENDOPATH XCEL Bladeless Trocar with OPTWIEW Technology has applications in abdominal, thoracic and gynecologic minimally invasive surgical procedures to establish a path of entry for endoscopic instruments. The trocar may be used with or without visualization for primary and secondary insertions. The Medline ReNewal Reprocessed ENDOPATH XCEL Universal Trocar Stability Sleeve with OPTIVIEW Technology has applications in thoracic, gynecologic laparoscopy and other abdominal procedures to establish a path of entry for endoscopic instruments.

The Medline ReNewal Reprocessed ENDOPATH XCEL Trocar with OPTIVIEW Technology devices are sterile, single-patient use endoscopic devices used to create an access port to the inside of the body cavity to perform endoscopic surgery. The trocars accommodate instruments that are 5-mm in diameter. The trocars contain two seals, an outer integrated removable self-adjusting seal and an integrated seal. Together, these two seals minimize gas leakage when instruments are inserted or withdrawn through the trocar. A stopcock valve is compatible with standard luer lock fittings and provides attachment for gas insufflation. The trocars contain OPTIVIEW Technology that reduces the incidence of trocar-induced endoscope lens smudging during endoscope insertion. Endoscope smudging occurs when bodily fluids and debris smear across the endoscope lens during a laparoscopic procedure. Trocar-induced smudging occurs when these bodily fluids and debris are deposited within the trocar's seal system when an endoscope or instrument has been exchanged through the trocar.

This document describes a substantial equivalence determination for a reprocessed medical device, the Medline Renewal Reprocessed ENDOPATH XCEL Trocar with OPTIVIEW Technology. It does not contain information about the acceptance criteria or a study proving the device meets specific performance criteria as typically found in an AI/ML medical device submission.

Instead, this submission focuses on demonstrating that the reprocessed device is "substantially equivalent" to an already legally marketed predicate device (Ethicon ENDOPATH XCEL Trocar with OPTIVIEW Technology). The performance testing outlined is to show that the reprocessed device maintains the same functional characteristics as the predicate device after reprocessing.

Therefore, many of the requested categories for AI/ML device studies (like sample size for test/training sets, expert ground truth, MRMC studies, standalone performance, effect size) are not applicable to this type of traditional medical device submission.

Here's an attempt to extract relevant information given the context of a reprocessed traditional medical device:

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

The document does not explicitly present a table of acceptance criteria with specific numerical targets and results in the format typically seen for AI/ML performance. Instead, it lists various functional performance studies and concludes that the reprocessed device was "found to be substantially equivalent" to the predicate. The "acceptance criteria" for a reprocessed device are generally that its performance characteristics (functional, cleaning, biocompatibility, sterilization) meet or exceed those of the original device or established standards, ensuring safety and effectiveness are maintained post-reprocessing.

2. Sample sizes used for the test set and the data provenance

• Sample Size: Not explicitly stated in the provided text for each test. The document mentions "the proposed device" and "the predicate device" which implies comparative testing was conducted using a sufficient number of units to establish statistical equivalence for each functional and material characteristic.
• Data Provenance: The studies were conducted by Medline ReNewal as part of their 510(k) submission for a reprocessed device. This is prospective testing performed to support the regulatory submission. The country of origin of the data is implied to be the US, where Medline ReNewal is based and operates.

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

This is not applicable. For this type of traditional medical device, "ground truth" is established through engineering and scientific testing against defined specifications, industry standards, and comparison with the predicate device's known performance, rather than expert consensus on medical images or clinical outcomes.

4. Adjudication method for the test set

This is not applicable. Adjudication methods like 2+1 or 3+1 are used in clinical trials or reader studies where human interpretation of data is being evaluated. For device performance testing, results are typically objective measurements (e.g., leakage rate, residual chemical levels) compared against defined criteria.

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 concerns a traditional reprocessed surgical instrument, not an AI/ML device. Therefore, no MRMC study, AI assistance evaluation, or effect size related to human reader improvement is relevant.

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

This is not applicable. This submission is for a physical surgical device, not an algorithm.

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

For the functional and material tests:

• Engineering Specifications: Performance against predefined engineering and material specifications.
• Industry Standards: Compliance with relevant ISO, ASTM, or other industry standards (e.g., for biocompatibility, sterility).
• Predicate Device Performance: Direct comparison of measurements and characteristics to the performance of a new (un-reprocessed) predicate device. For example, a leakage test result on the reprocessed device would be compared to the leakage test result on the original device.

8. The sample size for the training set

This is not applicable. This is a traditional medical device, not an AI/ML device. There is no concept of a "training set" in this context.

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

This is not applicable as there is no training set for a traditional medical device.

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