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Labtician Lid Load Gold Eyelid Weight Implants, surgically implanted in the upper eyelid, work by gravity to restore a functional blink mechanism in the patient with lagophthalmos resulting from temporary or permanent facial paralysis, specifically the orbicularis oculi muscle. This paralysis may be the result of Bell's palsy or from surgical trauma to the facial nerve.

Functional defects which may be corrected or avoided with the use of Labtician lid Load Gold Eyelid Weight Implants include inadequate eyelid closure, corneal exposure, serious keratopathy such as ocular irritation, keratitis, corneal abrasion or ulceration. These conditions may result in decreased vision.

The Labtician Lid Load Gold Eyelid Weight Implants are spherically radiused strips of pure gold (99.99%), constructed in twelve sizes ranging from 0.6 grams to 2.8 grams in 0.2 gram increments. All product specifications are substantially equivalent to the predicate device, the Series 3000 Gold Evelid Implant, produced by MedDev Corporation, with the exception that Labtician Lid Load Gold Eyelid Weight Implants are supplied sterile, whereas the predicate device is supplied nonsterile and designed to be sterilized prior to surgery by the end user.

Labtician Lid Load Gold Evelid Weight Implants are constructed of pure gold (99.99%). The weights are designed in a rectangular shape with a spherical radius of curvature of 12.7 mm which conforms to the shape of the eye. All edges are smoothly rounded. Suture holes are placed in the implant to allow the surgeon to secure it to the tarsus or orbital septum.

The provided text describes a 510(k) premarket notification for the Labtician Lid Load™ Gold Eyelid Weight Implants and focuses on demonstrating substantial equivalence to a predicate device, rather than presenting a study to prove the device meets specific performance acceptance criteria.

Therefore, many of the requested categories for acceptance criteria and study details cannot be extracted from the provided text because such a study was not performed or detailed. The submission relies on demonstrating substantial equivalence to a legally marketed predicate device (Series 3000 Gold Eyelid Implants by MedDev Corporation) rather than new clinical performance data.

Here's a breakdown of what can and cannot be answered based on the provided text:

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

The document does not explicitly state quantitative "acceptance criteria" for device performance in the typical sense (e.g., a specific sensitivity or specificity). Instead, it establishes "substantial equivalence" based on qualitative characteristics.

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

Not applicable. No new test set or clinical study data was presented to demonstrate performance against acceptance criteria. The submission relies on substantial equivalence to the predicate device.

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

Not applicable. No new test set requiring expert ground truth was created.

4. Adjudication method for the test set

Not applicable. No new test set requiring adjudication was created.

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. This device is a physical implant, not an AI-assisted diagnostic tool.

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

Not applicable. This device is a physical implant, not a standalone algorithm.

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

The "ground truth" for the substantial equivalence claim is the established safety and effectiveness of the predicate device, the Series 3000 Gold Eyelid Implants. This is based on its pre-amendment status and long-standing use.

8. The sample size for the training set

Not applicable. There is no machine learning model or training set involved.

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

Not applicable. There is no machine learning model or training set involved.

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