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The Verde LED Surgical Light System, subjected in this submission is a variable pattern / intensity surgical light designed to provide illumination of the surgical field and patient during surgical and non-surgical procedures.

The proposed Verde LED Surgical Light System is the next generation variable pattern / intensity surgical light designed to provide visible illumination of the surgical field and the patient during surgical and non-surgical procedures.

The provided text describes a 510(k) submission for the Verde LED Surgical Lighting System. This is a medical device for providing illumination during surgical procedures, not an AI or diagnostic device that would typically involve acceptance criteria related to accuracy, sensitivity, or specificity. Therefore, many of the requested categories (e.g., sample size for test set, number of experts, MRMC studies, ground truth types) are not applicable to the information provided.

However, based on the available text, here's an analysis of what can be extracted regarding acceptance criteria and performance for this type of device:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size for Test Set: Not applicable in the context of this device (a surgical lighting system), as performance testing is typically done on the device itself, not on a dataset of patient cases.
• Data Provenance: Not applicable. Performance testing for this type of device involves engineering and electrical safety tests, not data from specific countries or retrospective/prospective studies in the sense of clinical trials for diagnostic devices.

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

• Not applicable. Ground truth, in the context of experts, usually pertains to diagnostic accuracy, which is not relevant for a surgical lighting system. The "ground truth" for safety standards is the standard itself (CEI/IEC 60601-1 and IEC 60601-2-41), not established by experts during testing of the device.

4. Adjudication method for the test set

• Not applicable. Adjudication methods (e.g., 2+1, 3+1) are used for resolving discrepancies in expert interpretations of data, particularly in diagnostic studies. This is not relevant to performance testing of a surgical light.

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. An MRMC study is relevant for diagnostic devices (especially those involving AI assistance for human readers). This device is a lighting system; it does not involve human "readers" or AI assistance in this context.

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

• Not applicable. This device is a physical product (a surgical light), not an algorithm or AI system.

7. The type of ground truth used

• Type of Ground Truth: The "ground truth" for this device's performance is compliance with established international safety and performance standards for medical electrical equipment, specifically CEI/IEC 60601-1 and IEC 60601-2-41. These are engineering and safety standards, not clinical outcomes, pathology reports, or expert consensus on diagnostic findings.

8. The sample size for the training set

• Not applicable. This device is not an AI model, so there is no "training set."

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

• Not applicable. As there is no training set for an AI model, this question is not relevant.

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