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This device is intended for use in percutaneous nephrostomy, biliary und abscess drainage and other gastrointestinal and genitourinary procedures.

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The provided document is a 510(k) clearance letter from the FDA for a medical device: the Uresil® Guidewire. This type of document is generally a regulatory approval based on demonstrating "substantial equivalence" to a predicate device already on the market, rather than a de novo approval based on extensive clinical trials proving safety and effectiveness through well-defined acceptance criteria and study results.

Therefore, the information requested regarding acceptance criteria and study details (such as sample size, ground truth, expert qualifications, adjudication methods, MRMC studies, or standalone algorithm performance) is typically not found or relevant in a 510(k) clearance letter dated 1997 for a guidewire.

The 510(k) process focuses on comparing a new device to an existing predicate device, primarily to show that it is as safe and effective and raises no new questions of safety or effectiveness. It does not generally require the detailed performance studies or statistical analysis with specific acceptance criteria that would be expected for novel devices or AI/software as a medical device (SaMD) where such information would be central to demonstrating efficacy and safety.

However, I can extract the following information that is present:

• Device Name: Uresil® Guidewire
• Intended Use Statement: "This device is intended for use in percutaneous nephrostomy, biliary und abscess drainage and other gastrointestinal and genitourinary procedures."
• Regulatory Class: Class II
• Product Codes: 78 FGE, 78 EZB
• Date of Clearance: November 21, 1997

Therefore, I cannot provide the requested table and study details as they are not part of a standard 510(k) clearance documentation for a guidewire from 1997. The document explicitly states that the device is determined to be "substantially equivalent" to predicate devices marketed prior to May 28, 1976. This implies that its performance is expected to be similar to those existing devices, and detailed evidence of meeting specific numerical acceptance criteria (as for an AI algorithm) is not presented here.

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