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The Chase Anastomosis Visualization Device is indicated for use during procedures wherein clearing of a wound or surgical site, for enhanced visibility, must be maintained by non-contact means.

The Chase Anastomosis Visualization Device consists of a malleable wand, a 0.2 micron filter, and a sterile fluid inlet line. The overall length of the wand is approximately 10.125 inches in length. The stainless steel wire is completely embedded within the wall along its length for the purpose of maintaining a user chosen shape. The distal tip is designed to provide a fan-shaped irreigation mist pattern. The remaining proximal length of the wand is the regulated gas inlet which consists of a 0.2 micron medical grade in-line bacterial filter made of a hydrophobic membrane and a 1/4 inch tubing connecter. A 1/4 inch PVC tube which connects the in-line filter to the regulated gas source. A fluid inlet line extends from a point near the proximal end of the malleable section of the wand and terminates in a female luer-lock adaptor for conneciton to a standard fluid administration set which provides for flow control and on-off capacity

The provided documentation describes the CHASE ANASTOMOSIS VISUALIZATION DEVICE, a Class II medical device. The submission is a 510(k) premarket notification, which establishes substantial equivalence to a predicate device rather than providing extensive de novo clinical study data. Therefore, the information typically requested for AI/ML device studies (such as MRMC studies, training/test set details, ground truth establishment for AI performance) is not applicable in this context.

The safety and effectiveness of this device are based on its substantial equivalence to an existing device (the RMI Surgical Site Visualization Wand) and functional testing demonstrating that it meets specific engineering and manufacturing performance criteria.

Here's a breakdown of the requested information based on the provided document:

1. Acceptance Criteria and Reported Device Performance

The document also states that "All functional characteristics of the Chase Medical Anastomosis Visualization Device are nondifferentiable as compared with the predicate." This implies that the performance of the Chase device is considered equivalent to the predicate device for all unlisted functional characteristics.

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

This information is not applicable as the document describes functional and engineering testing, not a clinical study with a "test set" in the context of AI/ML evaluation. The tests are for device integrity, material strength, and package durability.

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

This information is not applicable for this type of device submission. Ground truth, in the context of expert consensus for diagnostic accuracy, is not relevant to the described functional and sterilization validation.

4. Adjudication Method for the Test Set

This information is not applicable. No adjudication method for a clinical test set is described.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

An MRMC comparative effectiveness study was not performed and is not applicable for this type of device. This device is a mechanical tool for surgical site visualization, not an AI/ML diagnostic or assistive technology that would typically warrant such a study.

6. Standalone (Algorithm Only) Performance Study

A standalone performance study was not performed and is not applicable. The device is a physical, non-AI tool.

7. Type of Ground Truth Used

The "ground truth" for the tests performed are defined by engineering specifications and industry standards. For example, a leak-free device at 10 psi defines the target performance, and exceeding 10 lb. tensile strength is the target for tubing bond strength. For sterilization, the ground truth is a sterility assurance level (SAL) of 10^-6^ achieved through a validated sterilization cycle.

8. Sample Size for the Training Set

This information is not applicable as there is no "training set" in the context of AI/ML. The device's design is based on established engineering principles and materials, and its performance is validated through defined tests, not machine learning.

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

This information is not applicable for the reasons stated above.

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