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To facilitate the placement of devices during diagnostic or interventional procedures.

The TXM Hydrophilic Guidewire is a hydrophilic coated device which is constructed with a nitinol inner core which is covered with a polyurethane outer layer coated with a lubricious coating to minimize friction during use. The TXM Hydrophilic Guidewire outer diameter is 0.035" and is available in a variety of lengths ranging from 80 cm to 260 cm. The TXM Hydrophilic Guidewire is also constructed in stiff and standard shaft configuration with straight or angled distal tip. The device is supplied sterile and is intended for single use only.

This is a 510(k) premarket notification for a medical device (TXM Hydrophilic Guidewire), not for an AI/ML powered medical device. Therefore, the requested information regarding acceptance criteria and studies proving the device meets them in the context of AI/ML performance metrics (like sample size for test sets, data provenance, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance, and training set information) is not applicable here.

This document describes the substantial equivalence of the TXM Hydrophilic Guidewire to a predicate device (Hydrophilic Coated Guidewire, K133155). The acceptance criteria and "study" are in the context of demonstrating this substantial equivalence through bench testing, biocompatibility testing, and sterilization testing.

Here's an analysis of the provided text based on the nature of the device:

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't explicitly list numerical "acceptance criteria" for each test. Instead, it states that "The TXM Hydrophilic Guidewire met the predetermined acceptance criteria." and then reports "Pass" for each test, indicating conformity. The applicable standards or internal test methods implicitly define the acceptance criteria.

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

• Sample Size: The document does not specify the exact number of devices tested for each bench test or biocompatibility test. It only indicates that tests were performed on "non-aged devices (T=0) as well as on devices subject to 2 years of accelerated aging (T=2)." This implies at least two groups of samples for most tests.
• Data Provenance: Not applicable in the context of an AI/ML device. For physical device testing, the data is generated internally by the manufacturer (Texas Medical Technologies, Inc.) through their testing processes. There's no mention of country of origin for test data, as it's product performance data. The tests are prospective, as they are performed on newly manufactured devices for regulatory submission.

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):

Not applicable. For a physical medical device, "ground truth" is established by direct measurement and observation against engineering and biological standards, not by expert consensus in the way it is for AI/ML image interpretation. The "experts" would be the engineers, technicians, and biologists performing and interpreting the standardized tests, but their specific number and qualifications are not detailed in this type of submission.

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

Not applicable. Adjudication methods are relevant for human interpretation tasks, especially in AI/ML performance evaluation where human experts might disagree. For device bench testing, the results are objectively measured against predefined criteria.

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 this is a physical medical device, not an AI-powered diagnostic or interpretive tool. MRMC studies are used to evaluate AI performance with human readers.

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

Not applicable, as this is a physical medical device, not an AI algorithm.

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

For this device, the "ground truth" is defined by established engineering and biological standards (e.g., ISO, ASTM, FDA Guidance documents, USP). Deviations from these standards constitute a "failure." For example:

• Bench Testing: Mechanical properties (e.g., tensile strength, flexibility, lubricity) are measured directly and compared against predefined ranges or thresholds specified in the applicable standards.
• Biocompatibility Testing: Biological responses (e.g., cytotoxicity, irritation, sensitization) are assessed using standardized in-vitro and in-vivo assays, and the absence of unacceptable biological reactions indicates compliance.
• Sterilization Testing: Sterility Assurance Level (SAL) of 10^-6 is the standard ground truth for terminal sterilization.

8. The sample size for the training set:

Not applicable. This is a physical device, not an AI/ML algorithm that requires a "training set."

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

Not applicable. As there is no AI/ML algorithm, there is no "training set" or ground truth establishment for it. The design specifications of the device are based on engineering principles and regulatory requirements, not learned from data.

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