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This Hi-Torque Guide Wire is intended to facilitate the placement of balloon dilatation catheters during percutaneous transluminal angioplasty (PTA) in arteries such as the femoral, popliteal, and infra-popliteal arteries. This guide wire may also be used with compatible stent devices during therapeutic procedures.

The guide wire may also be used to reach and cross a target lesion, provide a pathway within the vessel structure, facilitate the substitution of one diagnostic or interventional device for another, and to distinguish the vasculature.

The Abbott Vascular Hi-Torque (HT) Command 18 Guide Wire with hydrophilic coating is a guide wire with a maximum diameter of 0.0180" and is provided in 210 cm and 300 cm lengths.

The Abbott Vascular HT Command 18 Guide Wire consists of a 304V stainless steel proximal core and a nitinol distal core. The distal core is attached to the stainless steel proximal core using a dissimilar metal solid-state resistance weld. The core wire at the tip is flattened to provide optimize flexibility, steering, and tip shaping. There are four nitinol lengths of the HT Command 18 family, each having multiple tip load options. The HT Command 18 has a straight (shapeable) tip.

The distal portion of the wire is covered with a polyurethane jacket and a hydrophilic coating. The proximal section of the wire is coated with polytetrafluoroethylene (PTFE) and a single coat of a silicone-based hydrophobic coating. Brachial and femoral markers are located on the proximal segment of the 210 cm and 300 cm guide wires.HT Command 18 Guide Wire is offered in two (2) packaging configuration options: With Accessory Devices (Torque Device and Guide Wire Introducer) and Without Accessory Devices.

The provided document is a 510(k) summary for a medical device (Hi-Torque Command 18 Guide Wire). It describes the device, its intended use, and states that functional and dimensional testing was performed to demonstrate substantial equivalence to predicate devices. However, it does not contain the detailed study information typically associated with AI/ML device evaluations.

Therefore, many of the requested sections regarding acceptance criteria, study design, ground truth, and expert involvement are not applicable or cannot be extracted from this document, as this is a traditional medical device submission, not an AI/ML device submission.

Here's what can be extracted based on the provided text, with notes on what is not available:

1. Table of Acceptance Criteria and Reported Device Performance

The document lists various tests performed and states that the device "successfully met functional and dimensional acceptance criteria" and "met all acceptance criteria." However, it does not provide the specific numerical or qualitative acceptance criteria for each test, nor does it report the specific performance metrics (e.g., actual measured friction force, tensile strength values) for each test.

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

This information is not provided in the document. The testing described is for the physical and mechanical properties of a guide wire, not for an AI/ML algorithm that processes data.

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

Not applicable. This is a physical device, and its performance is evaluated against engineering specifications and predicate device equivalence, not against expert-established ground truth on a dataset.

4. Adjudication Method for the Test Set

Not applicable.

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. This document describes a physical medical device (guide wire), not an AI-enabled device.

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

Not applicable.

7. The Type of Ground Truth Used

The "ground truth" for this device's performance is based on engineering specifications, material properties, and comparison to a predicate device's established performance characteristics, as measured by standard laboratory tests. It's not based on expert consensus, pathology, or outcomes data in the context of an AI/ML algorithm.

8. The Sample Size for the Training Set

Not applicable, as this is not an AI/ML device.

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

Not applicable, as this is not an AI/ML device.

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