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The Endius Bipolar Sheath is intended to be used to coagulate soft tissue during various spinal surgical procedures.

The Endius Bipolar Sheath is a stainless Steel tube covered with an insulation material that is intended to fit over an automated tissue removal blade. The device is intended to be connected to the Valley Lab's Force 2, FX, or EZ, generator by using the Bipolar Sheath Adapter that is intended to decrease the maximum voltage of the Valley Lab's Generator from 800 volts to 100 volts. This will ensure that the appropriate level of energy is transmitted to the Bipolar Sheath for the maximum performance.

Here's an analysis of the provided documents regarding the acceptance criteria and supporting study for the Endius Bipolar Sheath:

This submission (K012488) is a 510(k) Pre-Market Notification, which is a regulatory pathway for demonstrating that a new device is "substantially equivalent" to a legally marketed predicate device. For such submissions, the primary "study" is often a comparison to the predicate device based on design, materials, intended use, and performance characteristics (often bench testing results). A formal clinical trial with specific acceptance criteria in the way one might expect for a novel drug or a high-risk device requiring PMA is generally not presented in full here.

Based on the provided text, the core of the "study" is the demonstration of substantial equivalence to a predicate device.

Acceptance Criteria and Reported Device Performance

The acceptance criteria here are implicitly not different from the predicate device in terms of fundamental performance (e.g., ability to coagulate, electrical safety, material compatibility). The "performance" is demonstrated by showing that the device has similar design features, materials, and operating principles to the predicate.

Additional Information on the "Study" (Substantial Equivalence)

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

   • Test Set Sample Size: Not applicable in the context of a clinical performance study. For substantial equivalence, the "test set" is essentially the device itself and its specifications, which are compared against the predicate device's specifications. There is no mention of a particular number of units tested beyond what would be typical for design verification and validation (e.g., electrical tests, material tests), but a specific "sample size" for a comparative clinical test set is not provided or required for this type of submission.
   • Data Provenance: The data comes from the design and manufacturing specifications of the Endius Bipolar Sheath and the publicly available information/previous 510(k) submissions (K981041, K984018) for the predicate SLT Bipolar Sheath. This is retrospective in the sense that it relies on existing design information and previous predicate approvals, rather than new prospective clinical trials. The country of origin of the data is the USA (Endius, Inc. and Surgical Laser Technologies are US companies).

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

   • Not applicable. This is not a study that involves expert review or ground truth establishment from medical images or clinical outcomes in the way a diagnostic AI might. The "ground truth" for substantial equivalence is the predicate device's performance and safety, which has already been established and regulated by the FDA. The experts involved would be the engineers and regulatory affairs personnel who prepared the submission and the FDA reviewers who assessed it.

3. Adjudication method for the test set:

   • Not applicable. There is no test set in the sense of clinical cases requiring adjudication. The assessment is a regulatory review process by the FDA.

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 device is a surgical instrument (bipolar sheath), not an imaging or diagnostic AI device.

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

   • Not applicable. This is not an algorithm or AI device.

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

   • The "ground truth" for this 510(k) submission is the demonstrated safety and effectiveness of the legally marketed predicate device(s) as determined by the FDA. The new device must be shown to be as safe and effective as the predicate.

7. The sample size for the training set:

   • Not applicable. This is a medical device, not a machine learning algorithm that requires a "training set."

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

   • Not applicable. No training set is involved.

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