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The reprocessed endoscopic trocars are designed to provide a pathway for entry of minimally invasive instruments to a body organ or cavity during general, abdominal, thoracic, gynecologic or other minimally invasive surgical procedures.

The Reprocessed Endoscopic Trocar is a sterile instrument consisting of a radiolucent sleeve and obturator in sizes ranging from 75 to 150 mm in length and 5 to 12 mm in diameter. Reprocessed Endoscopic Trocars are devices that provide a pathway for entry of minimally invasive instruments to a body organ or cavity during abdominal, thoracic or gynecologic surgical procedures.

The provided text describes the 510(k) summary for SterilMed, Inc.'s Reprocessed Endoscopic Trocar. However, it does not contain specific acceptance criteria or a detailed study description with performance metrics in the format requested.

The document primarily focuses on establishing substantial equivalence to predicate devices based on functional design, materials, indications for use, and manufacturing methods. It mentions "Functional and Safety Testing" and "Process validation testing" but does not elaborate on the specific acceptance criteria or the quantitative results of these tests.

Therefore, the following information is not available in the provided text:

• A table of acceptance criteria and reported device performance.
• Sample sizes used for test sets.
• Data provenance (country of origin, retrospective/prospective).
• Number and qualifications of experts for ground truth.
• Adjudication method for test set.
• Results of a multi-reader multi-case (MRMC) comparative effectiveness study.
• Results of a standalone (algorithm only) performance study.
• Type of ground truth used (expert consensus, pathology, outcomes data, etc.) for testing.
• Sample size for the training set.
• How ground truth for the training set was established.

Summary of available information:

1. Acceptance Criteria and Device Performance:

The document states: "Representative samples of reprocessed endoscopic trocars underwent bench testing to demonstrate appropriate functional performance. Process validation testing was performed to validate the cleaning and sterilization procedures as well as the device's packaging. In addition, the manufacturing process includes visual and functional testing of all products produced."

It concludes that the device is "substantially equivalent" to predicate devices based on "similarities in functional design, materials, indications for use and methods of construction."

No specific quantitative acceptance criteria or corresponding performance scores are provided in the text.

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

• Sample Size: Not specified. The document mentions "Representative samples," but does not give a number.
• Data Provenance: Not specified.

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

• Not applicable as this is a medical device, not an AI/imaging device requiring expert ground truth for classification. The testing focused on functional performance, cleaning, and sterilization validation.

4. Adjudication method 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. This is not an AI-assisted diagnostic device.

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

• Not applicable. This is not an AI algorithm.

7. The type of ground truth used:

• For "Functional and Safety Testing," the ground truth would be established scientific and engineering standards for device performance, cleanliness, and sterility. These are typically defined by regulatory standards (e.g., ISO, ASTM) and internal specifications. The document doesn't explicitly state the specific standards used.

8. The sample size for the training set:

• Not applicable. This device is reprocessed hardware, not an AI model requiring a training set.

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

• Not applicable.

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