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The Double Flexible Tipped Wire Guides are used to facilitate the placement of devices during diagnostic and interventional procedures.

The Double Flexible Tipped Wire Guides are Class II devices according to 21 CFR §870.1330; product code DQX (Wire, Guide, Catheter). The Double Flexible Tipped Wire Guides have flexible distal and proximal ends. Double Flexible Tipped Wire Guides are used to facilitate the placement of devices during diagnostic and interventional procedures.

The Double Flexible Tipped Wire Guides, subject of this submission, have been modified from the predicate device, Double Flexible Tipped Wire Guides (K171912), to include an additional diameter of 0.015 inches to the uncoated configurations with lengths of 30, 40, and 60 centimeters. Additionally, the subject device has been modified from the predicate device to include coated configurations for the existing 0.021 and 0.025 inch diameter devices with lengths of 40, 50, and 60 centimeters.

The Double Flexible Tipped Wire Guides are manufactured using a stainless steel core wire, and stainless steel coils. Some configurations include an exterior PTFE coating on the coils.

The modification to the Double Flexible Tipped Wire Guides have been created to provide additional options for physicians in selecting the appropriate wire guide during diagnostic and interventional procedures.

The Double Flexible Tipped Wire Guides are packaged, sterile devices intended for single patient use and labeled with a five-year shelf life.

The provided text describes a 510(k) premarket notification for a medical device called "Double Flexible Tipped Wire Guides." The submission aims to demonstrate substantial equivalence to a predicate device.

However, the provided text does not contain the level of detail required to answer all parts of your request, specifically regarding acceptance criteria and study design for AI/machine learning models in a medical context. The document describes a traditional medical device (wire guides) and the testing conducted relates to the physical and mechanical properties of this device, not to an AI algorithm's performance.

Therefore, many of the requested items (e.g., sample size for test set, data provenance, number of experts, adjudication method, MRMC study, standalone performance, ground truth types, training set details) are not applicable to this document as it does not involve an AI/ML device.

Below, I will extract the information that is present and explicitly state when information is not available or not applicable based on the content.

Description of Acceptance Criteria and Study Proving Device Meets Criteria

The device in question is a physical medical device (Double Flexible Tipped Wire Guides), not an AI/ML algorithm. The performance testing revolves around the mechanical and material integrity of the wire guide, not an algorithm's ability to interpret data or images.

1. Table of Acceptance Criteria and Reported Device Performance

The document states that for each test, "The pre-determined acceptance criteria were met." However, it does not explicitly list the specific numerical or qualitative acceptance criteria themselves. It only reports that the device passed.

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size: Not specified in the provided text for any of the tests.
• Data Provenance: Not applicable in the context of data for an AI/ML model. The tests are laboratory/benchtop tests of physical device properties, not data collected from patients.

3. Number of Experts Used to Establish Ground Truth and Qualifications of Experts

• Not Applicable. This device is hardware, not an AI/ML system that requires expert-established ground truth from medical images or data. The "ground truth" here is the physical performance of the device against established engineering standards.

4. Adjudication Method for the Test Set

• Not Applicable. As this is not an AI/ML device, there's no need for adjudication of readings or interpretations. The tests likely followed defined protocols with objective measurements.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

• No. This type of study (MRMC) is relevant for assessing the impact of AI on human readers for diagnostic or interpretive tasks. Since this is a physical medical device, an MRMC study was not conducted and is not applicable.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

• Not Applicable. This is a physical device, not an algorithm.

7. The Type of Ground Truth Used

• Engineering Standards and Specifications: The "ground truth" for this device's performance is compliance with established international standards (e.g., BS EN ISO 11070:2014) and FDA guidance documents (e.g., FDA Coronary and Cerebrovascular Guidewire Guidance 1995). The tests aim to demonstrate that the device's physical properties meet these pre-defined engineering requirements. This is sometimes referred to as "benchtop testing" or "performance testing."

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. This is a physical device; there is no training set or associated ground truth for an algorithm.

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