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Medline ReNewal Reprocessed Endopath 5DCD and 5DCS 5-mm Diameter Endoscopic Instruments have application in a variety of minimally invasive procedures to facilitate grasping, mobilization, dissection of tissue.

Medline ReNewal Reprocessed Endopath 5DCD and 5DCS 5-mm Diameter Endoscopic Instruments (originally manufactured by Ethicon Endo-Surgery) are cleaned, refurbished, tested, inspected packaged, labeled, and sterilize for an additional clinical use.

The provided document describes the FDA 510(k) clearance for the Medline Renewal Reprocessed Endopath Endoscopic Instruments (K152313). The primary goal of this submission is to demonstrate substantial equivalence to a predicate device, not necessarily to establish novel performance criteria for a new AI device. Therefore, the information requested may not be fully available in the context of this specific regulatory document.

However, based on the provided text, I can extract the following information regarding the device's acceptance criteria and the study proving it meets these criteria:

This document describes the regulatory clearance of reprocessed surgical instruments, not an AI device. Therefore, many of the typical AI-specific questions (like effect size of AI assistance, standalone performance, ground truth for training sets, etc.) are not applicable here. The "acceptance criteria" here refer to demonstrating that the reprocessed devices perform equivalently to the original predicate devices and meet established safety and functional standards for surgical instruments.

Acceptance Criteria and Reported Device Performance

The acceptance criteria for these reprocessed devices are implicitly that they perform identically to the original, new Endopath Endoscopic Instruments manufactured by Ethicon Endo-Surgery, and maintain safety and sterility. The performance testing aims to confirm this equivalence.

Study Details (as inferable from the document):

Since this is a submission for reprocessed surgical instruments, not an AI device, the common terminology for AI studies doesn't directly apply. However, I can interpret the request in the context of this document:

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

   • The document does not explicitly state the sample size (e.g., number of reprocessed devices tested for each functional or safety test).
   • Provenance: Not specified in terms of country of origin for the data. The devices are reprocessed versions of Ethicon Endo-Surgery instruments, and the testing was performed by Medline ReNewal. It is a prospective evaluation in the sense that Medline performs these tests on their reprocessed devices to ensure quality and equivalence.

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

   • This concept is not directly applicable. "Ground truth" for these devices is typically established by comparing their performance to the known specifications and performance of original, new devices, and against recognized industry standards (e.g., ISO, ASTM, IEC). The testing itself provides the data, and expert interpretation occurs during the evaluation of these results against the predicate's performance and safety standards. There's no mention of a panel of experts for subjective assessment typical in AI evaluation.

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

   • Not applicable in the context of this type of device and testing. Performance data from laboratory tests (e.g., force measurements, electrical readings) are quantitative and do not require expert adjudication in the same way clinical image interpretation might. Visual inspections would be performed according to established criteria, not consensus.

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:

   • Not applicable. This is not an AI device or a diagnostic imaging study.

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

   • Not applicable. This is a physical surgical instrument, not an algorithm.

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

   • The "ground truth" here is the performance specifications and safety profile of the original, new predicate devices (Ethicon Endopath Endoscopic Instruments), coupled with established engineering, biological, and sterilization standards (e.g., IEC 60601 series for electrical safety, biocompatibility standards, sterilization validation standards). The reprocessed device's performance is compared against these benchmarks.

7. The sample size for the training set:

   • Not applicable. There is no machine learning "training set" for physical reprocessed instruments.

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

   • Not applicable, as there is no training set for an AI model.

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