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Bard PTFE Coated Guide Wires are indicated for percutaneous entry of a guiding catheter into a vessel using standard percutaneous methods (Seldinger's Technique). Generally, Guide Wires which are 100cm or longer are indicated for use with vascular catheters and balloon dilatation catheters in angiographic or interventional procedures. The guide wire may be inserted through an [18g] needle, introducer, or catheter. A guide wire with an outer diameter of .018" or smaller may be used with open ended guide wires.

Guide wires which are shorter than 100cm are generally indicated for non-vascular use. Guide wires with an outer diameter of .018" or smaller may be inserted into the target organ through a [22g] needle or an open-ended guide wire (60cm or shorter). Larger guide wires may be inserted through larger gauge needles or an introducer for placement of dilators and/or drainage catheters.

The Bard PTFE (Teflon®) coated guide wires, subject of this 510(k), like their predicate device counterparts, are manufactured from stainless steel wire, tin/silver solder, and PTFE (Teflon®) coating, or Benzalkonium Heparin (BH) coating applied over the PTFE (Teflon®) coating. The guide wire construction consists of a safety wire, a core wire, and a wound spring for flexibility. The features that distinguish individual wires consist of the core type (fixed or moveable), a straight or "J" tip configuration, diameters, lengths, and coating types. Each guide wire is subsequently packaged, labeled, and sterilized.

The provided text describes a 510(k) summary for Bard PTFE (Teflon®) Coated Guide Wires, which aims to demonstrate substantial equivalence to predicate devices, rather than establishing acceptance criteria and conducting a study to prove performance against those criteria in the context of a new, significantly different device or an AI/ML product.

The submission focuses on a process change for the Teflon® coating due to environmental concerns regarding PFOA, not a new device design or a novel AI algorithm. Therefore, the information provided does not align with the typical structure for reporting acceptance criteria and a study proving device performance as envisioned for an AI/ML product.

However, I can extract the relevant "performance specifications" and the "testing performed" to address your request as best as possible within the context of this document.

Understanding the Context:
The "acceptance criteria" here are essentially that the modified guide wires maintain the same performance characteristics as the predicate devices, despite a change in the manufacturing process of the PTFE coating. The study's purpose is to demonstrate that this change in coating material does not adversely affect the safety, biocompatibility, and functional performance of the guide wires.

Here's the information structured to fit your requested format, with caveats where the document's content deviates from a typical AI/ML performance study:

1. Table of Acceptance Criteria and Reported Device Performance

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

The document does not specify a numerical sample size for the test set. It refers to "representative samples" for inhibition/enhancement testing, "representative products" for coating application, and "representative guide wire items" for functional performance testing.

• Sample Size: Not explicitly stated as a number; referred to as "representative samples/products/items."
• Data Provenance: Not explicitly stated (e.g., country of origin). The testing was conducted internally by Bard or outsourced to labs for specific tests (e.g., biocompatibility to ISO standards). It is retrospective in the sense that the new material's performance is being compared to the established performance of the predicate device.

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

This is not applicable in the context of this 510(k) submission. The "ground truth" for this submission is established through validated laboratory tests and engineering evaluations against existing performance specifications and standards (e.g., ISO, USP, FDA guidelines). There's no clinical "ground truth" established by human experts in the way an AI/ML study would require for diagnostic accuracy.

4. Adjudication Method for the Test Set

Not applicable. This is a scientific and engineering performance study, not a clinical trial requiring expert adjudication of results. Each test (e.g., biocompatibility, friction, durability) has its own pass/fail criteria based on standards and internal specifications.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

No. This type of study is relevant for diagnostic devices where human readers interpret results, often comparing AI-assisted vs. unassisted performance. This submission is for a physical medical device (guide wire) and its material change.

6. If a Standalone Study (algorithm only without human-in-the-loop performance) was done

Yes, in a conceptual sense. All the testing performed (biocompatibility, chemical analysis, mechanical testing) is "standalone" in that it evaluates the physical properties and safety of the device itself, without human interpretation as part of the performance metric for this type of device. There is no AI algorithm involved.

7. The Type of Ground Truth Used

The "ground truth" for this submission is based on:

• Established Standards: International Standard ISO 10993 for biocompatibility.
• Regulatory Guidelines: FDA-modified testing matrix (G95-1) for biocompatibility.
• Pharmacopeial Standards: USP Physiochemical analysis (replacement material meets USP 604 requirements).
• Internal Product Specifications: Performance specifications (e.g., for coefficient of friction, durability, stiffness, tensile, torque) that are the same as those for the predicate devices.
• Chemical Analysis: FTIR analysis.

8. The Sample Size for the Training Set

Not applicable. There is no training set as this is not an AI/ML product. The "development" of the new coating process was driven by supplier changes, and the "validation" involves ensuring the finished product performs equivalently.

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

Not applicable, as there is no training set for an AI/ML model. The "ground truth" for the device's performance characteristics (biocompatibility, mechanical properties) was established over time for the predicate devices through robust engineering, testing, and compliance with medical device regulations and standards. The purpose of this submission is to demonstrate that the new process for the coating maintains this existing ground truth.

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