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The CEREGLIDE 92 Intermediate Catheter is indicated for use in facilitating the insertion and guidance of appropriately sized interventional devices into a selected blood vessel in the neurovascular system.

The CEREGLIDE™ 92 Intermediate Catheter is a single lumen, variable stiffness catheter designed to be introduced over a steerable guidewire along with a microcatheter and/or compatible support device into the neuro vasculature. The catheter consists of a lubricious PTFE lined inner lumen to facilitate movement of the guidewires and other devices, variable pitch stainless steel and tungsten braid, and various durometer polymer jackets. These jackets provide distal flexibility and gradually transition to a stiffer proximal shaft to facilitate the advancement of the catheter in the anatomy. The outer surface of the catheter is hydrophilic coated in order to reduce friction during manipulation in the vessel. A radiopaque marker at the distal end of the catheter provides fluoroscopic visualization of the catheter tip. The proximal end of the catheter incorporates a standard Luer adapter to facilitate the attachment of accessories, a hub, and an ID band.

The CEREGLIDE™ 92 Intermediate Catheter is packaged with a Tuohy Borst hemostasis valve (RHV) with a side port and two slit introducer accessories. The RHV with side port is used for flushing and insertion of catheters. The slit introducers are designed to introduce the CEREGLIDE™ 92 Intermediate Catheter into the base catheter and protect the distal tip of the CEREGLIDE™ 92 Intermediate Catheter during insertion into the hemostasis valve of the base catheter.

The provided document is a 510(k) Premarket Notification from the FDA regarding the "CEREGLIDE 92 Intermediate Catheter." It details various performance tests conducted on the device to demonstrate its substantial equivalence to a legally marketed predicate device.

However, it's crucial to understand that this document does NOT describe the acceptance criteria and study proving device performance for an AI/ML-driven medical device.

Instead, this document pertains to a traditional, physical medical device (a catheter). The "performance testing" described are typical bench testing (physical and mechanical properties) and biocompatibility testing for hardware, not algorithmic performance.

Therefore, many of the specific questions asked in the prompt, such as "Sample sized used for the test set and the data provenance," "Number of experts used to establish the ground truth," "Adjudication method," "MRMC study," "Standalone performance," and "ground truth for the training set," are not applicable to the content of this document. These questions are relevant to the validation of AI/ML models in medical devices.

I will address the questions to the extent possible with the information provided, explicitly stating when information is not present or not applicable.

Acceptance Criteria and Device Performance for the CEREGLIDE 92 Intermediate Catheter

The CEREGLIDE 92 Intermediate Catheter is a physical medical device, not an AI/ML-driven one. Therefore, the "acceptance criteria" and "device performance" in this context refer to its physical, mechanical, and biological properties rather than algorithmic performance.

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

The document provides a summary of "Performance Testing - Bench" and "Biocompatibility Testing." For each test, the "Result" uniformly states "PASS: Samples met the established acceptance criteria" or simply "PASS." The specific numerical or quantitative acceptance criteria are generally not explicitly stated in the summary tables but are implied by the "PASS" result.

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

The document states: "All testing was conducted using sampling methods as required by internal design control procedures." However, the specific sample sizes for each test are not provided.

Data provenance: Given that these are bench tests for a physical device, the "data provenance" would refer to the testing conditions and lab environment, rather than patient data. The tests were conducted internally by the manufacturer. No country of origin for specific "data" (in the sense of patient data) is applicable. This was a non-clinical study involving bench testing and in-vitro/in-vivo animal tests for biocompatibility, not a clinical trial involving human patients or patient data.

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

Not applicable. This device is a physical catheter, not an AI/ML algorithm requiring expert ground truth for image interpretation or diagnosis. The "ground truth" for these tests refers to established engineering specifications, ISO standards, and biological safety limits.

4. Adjudication method for the test set

Not applicable. There is no "adjudication" in the sense of reconciling expert opinions on data. Adjudication methods like 2+1 or 3+1 are used for human-labeled datasets, typically for AI/ML models.

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. MRMC studies are performed to evaluate the diagnostic performance of AI-assisted human readers compared to human readers alone, typically in medical imaging or diagnostics. This document is about a physical interventional device, not a diagnostic AI tool.

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

For the bench testing and biocompatibility assessments, the "ground truth" is based on:

• Established engineering specifications and design requirements for the catheter's physical dimensions, mechanical properties (tensile strength, burst pressure, kink resistance, trackability, etc.).
• International standards (e.g., ISO 10555-1) for catheter performance.
• Regulatory guidance and standards for biocompatibility (e.g., ISO 10993-1, ISO 11135 for sterilization, EN ISO 10993-7 for EO residuals).
• Comparison to predicate device characteristics to demonstrate substantial equivalence.

8. The sample size for the training set

Not applicable. This is not an AI/ML device that requires a "training set."

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

Not applicable. As above, no training set for an AI/ML model.

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