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The Wingman Crossing Catheters (14/14C/18/3) are intended to be used in conjunction with steerable guidewires to access discrete regions of the peripheral vasculature. It may be used to facilitate placement and exchange of guidewires and other interventional devices, including facilitation of the intraluminal placement of diagnostic/ interventional devices beyond peripheral stenotic lesions (including chronic total occlusions [CTOs]) and provide a conduit for delivery of saline solutions or diagnostic/therapeutic agents.

The Wingman 14C Crossing Catheter is intended to be used in conjunction with steerable guidewires to access discrete regions of the coronary vasculature. It may be used to facilitate placement and exchange of guidewires and other interventional devices and provide a conduit for delivery of saline solutions or diagnostic/therapeutic agents.

The Wingman 14, 18, & 35 Crossing Catheter is contraindicated for use in the coronary and cerebral vasculature. The Wingman 14C Crossing Catheter is contraindicated for use in the cerebral vasculature.

The Wingman Crossing Catheter (14/18/35) is a device intended to provide additional support to a steerable guidewire when accessing discrete regions of the peripheral vasculature.
The Wingman Crossing Catheter (14C) is a device intended to provide additional support to a steerable guidewire when accessing discrete regions of the coronary vasculature and peripheral vasculature.

The device consists of a support catheter, with a concealed radiopaque beveled guide-tip, and activating handle. The through-lumen of the device can serve as a conduit for the delivery of diagnostic and therapeutic agents.

The provided text describes a 510(k) summary for the Wingman Crossing Catheters. The summary includes information about the device, its intended use, and a brief discussion of a clinical study conducted to demonstrate the safety and effectiveness of the device for crossing Chronic Total Occlusions (CTOs) in infrainguinal arteries.

Here's a breakdown of the requested information based on the provided text, focusing on the clinical study that proves the device meets the acceptance criteria:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Test Set Sample Size: 85 subjects with 86 CTO lesions.
• Data Provenance: The study was "non-randomized, prospective, multi-center, single-arm." It was conducted "both in the United States and outside the United States in Germany and Austria."

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications

The provided text does not specify the number of experts used to establish ground truth or their qualifications. The study focused on objective endpoints (successful CTO crossing, MAE rates) rather than subjective expert consensus on image interpretation.

4. Adjudication Method for the Test Set

The provided text does not specify an adjudication method. Given the objective nature of the primary effectiveness endpoint (successful crossing of the CTO) and the safety endpoint (occurrence of specific adverse events), a formal adjudication method by experts beyond clinical reporting might not have been implemented in the way it would for, say, image review.

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

The provided text indicates this was a "non-randomized, prospective, multi-center, single-arm study." It does not describe an MRMC comparative effectiveness study comparing human readers with and without AI assistance. The study evaluated the device's performance in crossing CTOs, not its impact on human reader performance.

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

The device is a physical medical device (catheter), not an AI algorithm. Therefore, the concept of "standalone (algorithm only)" performance is not applicable in this context. The study evaluates the catheter's ability to facilitate CTO crossing.

7. The Type of Ground Truth Used

The ground truth for the effectiveness endpoint was the objective observation of successful CTO crossing during the interventional procedure. For the safety endpoint, the ground truth was the occurrence of specific clinical events (MAE, perforation, embolization, or dissection) within 30 days, likely determined by clinical follow-up and medical records. This falls under outcomes data and clinical observation.

8. The Sample Size for the Training Set

The provided text describes a clinical study evaluating the device's performance. It does not mention a "training set" in the context of machine learning or AI models. This study is an evaluation of the device itself.

9. How the Ground Truth for the Training Set Was Established

As the device is a physical catheter and not an AI algorithm, the concept of a "training set" and its associated ground truth establishment is not applicable. The study evaluates the device's clinical performance.

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The speX Support Catheter is intended to be used in conjunction with steerable guidewires to access discreet regions of the peripheral vasculature. It may be used to facilitate placement and other interventional devices and provide a conduit for the delivery of saline solutions or diagnostic/therapeutic agents.

The speX Support Catheter is a device intended to provide additional support to a steerable guidewire when accessing discrete regions of the peripheral and/or coronary vasculature. The device consists of a support catheter body with a luer end. The through-lumen of the device can serve as a conduit for the delivery of diagnostic and therapeutic agents.

The provided document is a 510(k) summary for the speX Support Catheter, a medical device. It focuses on demonstrating substantial equivalence to a predicate device rather than presenting a study proving that an AI-driven device meets specific acceptance criteria.

As such, the information requested in the prompt, which is typically relevant for AI/ML medical devices, is largely absent from this document. The document describes a physical medical device (a support catheter), and the "performance data" refers to physical and mechanical tests of the catheter, not the performance of an algorithm.

Therefore, I cannot provide most of the requested information based on the provided text.

Here is what I can extract:

1. A table of acceptance criteria and the reported device performance:

Based on the document, specific numerical acceptance criteria and reported device performance are not explicitly detailed in a table format. The document states:

• "The modified speX Support Catheter met all specified criteria and did not raise new safety or performance questions."
• "Based on the performance testing the modified speX Support Catheter was found to be substantially equivalent to the predicate device."

The types of tests performed were:

• Simulated Use Testing
• Component/Assembly Integrity Testing
• Corrosion Resistance Testing
• Lubricity Testing

2. Sample sized used for the test set and the data provenance:

• This information is not available in the provided text, as the study involves physical device testing, not AI data analysis.

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

• This information is not applicable/not available, as the study pertains to physical device performance and not diagnostic or interpretive tasks requiring expert ground truth in the context of AI.

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

• This information is not applicable/not available for this type of physical device testing.

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:

• This information is not applicable. This document describes a physical medical device, not an AI system that assists human readers.

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

• This information is not applicable. This document describes a physical medical device, not an algorithm.

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

• This information is not applicable. For physical device testing, "ground truth" would typically refer to established engineering specifications, mechanical properties, and functional requirements, as opposed to medical diagnoses.

8. The sample size for the training set:

• This information is not applicable/not available as this is a physical medical device, not an AI model requiring a training set.

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

• This information is not applicable/not available as this is a physical medical device, not an AI model.

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