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For use as an adapter for the introduction of tools and/or irrigation fluid through the endoscope working channel.

The N.M. Beale Co., Inc. Scope Introducer consists of a one-piece metal construct with a luer fitting on one end and a tubular opening at the other end. The luer connector of the introducer can be connected to an irrigation source; the tubular end is inserted into the endoscope working channel to facilitate the introduction of accessories and/or irrigation. The Scope Introducer can be reused and is intended to be sterilized between uses.

The N.M. Beale Co., Inc. Scope Introducer, as described in the provided documents, is a simple medical device intended as an adapter for introducing tools or irrigation fluid through an endoscope working channel. The "performance testing" mentioned in Section 5 of the 510(k) summary (page 0) refers only to "cleaning and sterilization validations." This device is a Class II device and was cleared via the 510(k) pathway by demonstrating substantial equivalence to a predicate device.

Given the nature of this device and the information provided, it does not involve Artificial Intelligence (AI) or any complex algorithms that would necessitate the extensive study and performance evaluation metrics typically associated with AI-driven medical devices. Therefore, a table of acceptance criteria and reported device performance related to diagnostic accuracy, sensitivity, specificity, or other AI-specific metrics is not applicable here.

The questions regarding sample size for test sets, data provenance, expert ground truth establishment, adjudication methods, MRMC studies, standalone performance, type of ground truth, and training set details are all relevant to the evaluation of AI models. Since this device is not an AI product, these questions cannot be answered based on the provided documents.

In summary:

• 1. A table of acceptance criteria and the reported device performance: Not applicable for an AI device. The submission mentions "cleaning and sterilization validations" as performance testing, which would have their own acceptance criteria, but these are not specified in the provided text.
• 2. Sample sized used for the test set and the data provenance: Not applicable as it is not an AI device.
• 3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable as it is not an AI device.
• 4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable as it is not an AI device.
• 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 as it is not an AI device.
• 6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable as it is not an AI device.
• 7. The type of ground truth used (expert consensus, pathology, outcomes data, etc): Not applicable as it is not an AI device.
• 8. The sample size for the training set: Not applicable as it is not an AI device.
• 9. How the ground truth for the training set was established: Not applicable as it is not an AI device.

The study referenced is the 510(k) premarket notification process for medical device clearance, which, in this case, primarily focused on demonstrating substantial equivalence to a predicate device and included "cleaning and sterilization validations" for reusability.

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