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A device intended to be used as a disposable barrier for a surgical lighting system and which allows a surgical team member to manually adjust the lighting system. This is a single-use device

The Surgical Light Handle Cover is a polycarbonate injection molded device shaped to fit a surgical light that has release buttons protruding from the surgical light handle. The Surgical Light Handle Cover has apertures located at the end of the device, proximal to the surgical light, which correspond to the release buttons on the surgical light handle. When the Surgical Light Handle Cover is attached to the light, the release buttons will interface with the apertures to secure the Surgical Light Handle Cover to the light handle.

The Surgical Light Handle Cover is hollow in the center, with transparent polycarbonate located near the distal end. The transparent end permits the use of a recording device, which may be mounted onto the surgical light. The transparent end allows light to pass through for the purpose of recording images, it does not provide image enhancement or magnification.

The provided text describes the acceptance criteria and the study results for the "Surgical Light Handle Cover" device (K133554).

The study did not involve AI assistance, human readers, or the establishment of ground truth by experts in the context of diagnostic accuracy. This device is a physical medical accessory, and its performance evaluation focuses on manufacturing, sterility, biocompatibility, and physical functionality rather than diagnostic capabilities.

Here's a breakdown of the requested information based on the provided text, with clarifications where the questions are not directly applicable to 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

The document does not specify exact sample sizes for each test listed in the "Performance Data Summary." For tests like "Simulated Distribution Test" (ASTM D4169), "Dye Migration Test" (ASTM F1929), "Seal Peel Test" (ASTM F88), "Sterility" (ISO 11135-1), "EO/ECH Residuals" (ISO 10993-7), "Cytotoxicity" (ISO Elution), and "Material Leachables" (USP Physical-Chemical Analysis), the sample sizes would typically be determined by the specific ASTM/ISO standards referenced, but they are not detailed in this summary.

For the functional requirements ("Product must be easily installed and removed" and "Product must not interfere with the functionality of surgical light"), the test method indicates empirical assessment on a surgical light, but no specific number of trials or devices tested is provided.

The data provenance is not explicitly stated in terms of country of origin or whether it was retrospective/prospective, but given that it's a 510(k) submission for a medical device manufacturer, the testing would have been conducted by or for Microtek Medical Inc., an Ecolab Company, likely in a controlled laboratory setting.

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

This question is not applicable to the evaluation of this device. The "ground truth" for this type of medical accessory is not established by clinical expert interpretation or diagnostic accuracy. Instead, it's based on objective engineering specifications, regulatory standards (ASTM, ISO), and functional performance against predefined criteria. For example:

• Sterility: Achieved if the Sterility Assurance Level (SAL) meets 10^-6 as per ISO 11135-1.
• Packaging: Pass/fail based on meeting the requirements of ASTM standards.
• Functionality: Pass/fail based on whether the device can be attached/detached and doesn't impede light movement or clarity.

No clinical experts or radiologists were involved in establishing "ground truth" for these performance metrics.

4. Adjudication method for the test set

This question is not applicable. Adjudication methods (e.g., 2+1, 3+1) are typically used in clinical studies involving interpretation of medical images or patient data where there might be inter-reader variability. For this device, the tests are objective: either a package seal passes ASTM F88 or it doesn't; either an item is sterile to the specified SAL or it isn't. Discrepancies would be resolved by re-testing or reviewing the test methodology rather than expert consensus on an interpretation.

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

No, an MRMC comparative effectiveness study was not done. This device is a physical surgical light handle cover, not an AI-powered diagnostic or assistive tool. Therefore, there is no AI component, no human reader performance to improve, and no effect size to report in this context.

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

No, a standalone (algorithm only) performance evaluation was not done. This device is a physical product and does not involve any algorithms or AI for standalone performance assessment.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

As discussed in point 3, the concept of "ground truth" as typically applied to diagnostic AI is not relevant here. The "ground truth" for this device's performance is defined by:

• Adherence to established international standards (e.g., ASTM, ISO) for material properties, sterility, and packaging integrity.
• Meeting predefined functional specifications (e.g., ease of installation, non-interference with light function).
• Compliance with biocompatibility requirements for medical devices.

8. The sample size for the training set

This question is not applicable. This device is not an AI algorithm, and therefore there is no "training set" in the machine learning sense. The device is manufactured based on a design and then tested against the criteria outlined above.

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

This question is not applicable. As there is no training set for an AI algorithm, there is no "ground truth" to establish for such a set.

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