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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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The ENDOPATH Endoscopic Instruments have application in a variety of minimally invasive procedures to facilitate grasping, mobilization, dissection and transection of tissue.

The ENDOPATH Endoscopic Instruments are sterile, single patient use instruments designed for use through appropriate ENDOPATH Surgical Trocars and FLEXIPATH® Flexible Surgical Trocars. The instruments have a rotating insulated shaft with a diameter of either 3mm, 5mm or 10mm. The rotation knob located on the handle rotates the shaft 360 degrees in either direction. The ring handles are compressed and released to activate the instrument jaws or scissor blades. Each of the curved scissors and dissectors has a monopolar cautery connector that extends from the top of the handle. The connector is used for electrosurgery when properly attached to a standard cautery cable and a proper generator.

The provided 510(k) summary for the ENDOPATH® Endoscopic Instruments describes a medical device and its substantial equivalence to a predicate device. However, it does not contain detailed acceptance criteria, a specific study with quantitative performance metrics, or information relevant to AI/ML or extensive clinical trials as implied by many of your requested categories.

This device is a surgical instrument from 1999, and the regulatory submission approach for such devices
is typically based on demonstrating substantial equivalence through design comparisons and pre-clinical bench testing, rather than the rigorous performance studies often associated with AI/ML-driven diagnostics where the requested details would be highly applicable.

Therefore, I cannot fulfill most of your request as the information is not present in the provided text. I will address what can be extracted or inferred.

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

The document does not explicitly state numerical acceptance criteria. Instead, it states:

• Acceptance Criteria (Implied): Acceptable performance equivalent to the Predicate Device in reliability and design.
• Reported Device Performance: "The studies demonstrated acceptable performance to the Predicate Device in reliability and design. The performance evaluated are ergonomics of the handle and rotating knob tissue trauma, grasping, dissecting, cauterizing ability and cutting ability. From the date generated, it can be concluded that the New Device performs equivalent to the Predicate Device."

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

This information is not provided. The performance evaluation refers to "pre-clinical data" and "studies" but gives no details on sample size, data provenance, or whether the studies were retrospective or prospective. Given the nature of a surgical instrument, these tests would likely be in-vitro or ex-vivo bench tests, possibly animal models, rather than human clinical trials for a 510(k) submission focused on substantial equivalence.

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 information is not provided. It's unlikely that "experts" in the sense of clinicians establishing ground truth for diagnostic accuracy (as would be relevant for AI) were involved in a way that would require detailed reporting for this type of device. The evaluations would more likely involve engineers or technicians assessing mechanical and functional performance.

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

This information is not provided. Adjudication methods are typically relevant for complex diagnostic interpretations, not for the functional testing of a surgical instrument.

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

No such study was done. This is a surgical instrument, not an AI-based diagnostic tool. "Human readers" and "AI assistance" are not applicable here.

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

Not applicable. This is not an AI/ML device.

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

The document states performance was evaluated on "ergonomics of the handle and rotating knob tissue trauma, grasping, dissecting, cauterizing ability and cutting ability." The "ground truth" would be objective measurements or qualitative assessments of these physical properties and functions against pre-defined engineering specifications or performance of the predicate device. It would not be expert consensus, pathology, or outcomes data in the context of diagnostic accuracy.

8. The sample size for the training set

Not applicable. This is not an AI/ML device, so there is no "training set."

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

Not applicable. There is no training set for this type of device.

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