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The KnoxFog Anti-fogging Device is a temporary anti-fog coating and therein inhibits fogging on optical lenses. It is a laparoscopic accessory intended to facilitate intraoperative defogging of laparoscope lenses, thereby maintaining visualization of the surgical site and closed body cavity.

KnoxFog™ is intended for use as an anti-fog solution applied to rigid endoscope lenses prior to insertion into the body to maintain optical clarity during endoscopic procedures.

KnoxFog™ is a semi-sol gel anti-fog coating designed to prevent condensation on endoscopic lenses during surgical procedures. The device is supplied as a sterile solution in single-use containers for application immediately prior to endoscopic procedures. When applied to the endoscope lens, KnoxFog™ forms a transparent hydrophilic coating that prevents fog formation by maintaining optical clarity in high-humidity environments. The product is terminally sterilized using gamma radiation to ensure safety for use in surgical environments.

The provided FDA 510(k) clearance letter for the KnoxFog Anti-fogging Device focuses on the device's technical specifications and substantial equivalence to a predicate device, VitreOx™. However, it does not contain information typically associated with studies proving a device meets acceptance criteria for an AI/ML medical device, which would involve aspects like expert ground truth, multi-reader studies, or large data sets.

The document describes bench testing for an anti-fogging solution, not an AI/ML algorithm. Therefore, many of the requested points regarding AI/ML device studies (e.g., ground truth establishment, training sets, MRMC studies, standalone performance) are not applicable to the information provided.

I can, however, extract the acceptance criteria and performance data for the anti-fogging device based on the provided text.

Acceptance Criteria and Device Performance (KnoxFog Anti-fogging Device)

Based on the provided document, the "acceptance criteria" appear to be implicitly defined by the comparative performance against the predicate device, VitreOx™, specifically in terms of time-to-fog. Other tests (transportation, accelerated aging, biocompatibility) are also performance indicators but without explicit numerical acceptance thresholds provided beyond general "stability," "shelf-life claims," and "biocompatible."

Here's the information that can be extracted:

1. Table of Acceptance Criteria and Reported Device Performance

Note on "Acceptance Criteria": The document doesn't explicitly state numerical acceptance criteria for "Transportation Stability," "Accelerated Aging," or "Biocompatibility." Instead, it states that the tests verified stability, confirmed shelf-life claims, and demonstrated biocompatibility in accordance with standards. The time-to-fog analysis is the most quantitative comparative criterion mentioned.

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

• Sample Size: Not explicitly stated for any of the tests (Time-to-Fog, Transportation, Accelerated Aging, Biocompatibility). The text just mentions "comparative testing" and "studies."
• Data Provenance: Not specified (e.g., country of origin). The studies appear to be bench testing performed by the manufacturer, UV ONE Hygienics, Inc. The document does not indicate if the data was retrospective or prospective in the medical context, as it's a materials science/engineering evaluation rather than a clinical study.

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

• Not Applicable. This device is an anti-fogging solution, not an AI/ML diagnostic or image interpretation device. The "ground truth" would be objective measurements of fogging, material stability, and biological reactions, not expert consensus on medical images.

4. Adjudication Method for the Test Set

• Not Applicable. As above, this is for assessment of an anti-fogging solution, not human interpretation of data requiring adjudication.

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

• No. An MRMC study is relevant for evaluating the impact of AI on human reader performance, typically in interpreting medical images. This device is a topical anti-fogging agent. The "Performance Data" section details bench testing comparing the device's technical performance (time-to-fog, stability) to a predicate, not how it affects human readers.

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

• Not Applicable. This is not an algorithm. The performance data presented (time-to-fog, stability, biocompatibility) are inherently "standalone" in the sense that they measure the physical properties of the device itself.

7. The Type of Ground Truth Used

• Objective Measurements/Material Science:
  • For "Time-to-Fog Analysis": The ground truth is the measurable time until fog formation on the endoscope lens under specific conditions.
  • For "Transportation Testing": The ground truth relates to the physical integrity and continued functionality of the product after simulated transport.
  • For "Accelerated Aging": The ground truth is the product's stability and efficacy over time, extrapolated from accelerated conditions.
  • For "Biocompatibility Testing": The ground truth is established through standardized in vitro and in vivo biological tests (e.g., cytotoxicity, irritation) according to ISO 10993 standards.

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 algorithm is involved.

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