Search Results

Benacel® Dental Dressing is intended for use as a wound dressing in extraction sites and the management of alveolar osteitis (dry socket) and may be used as a wound dressing for the temporary management of oral surgical wounds, such as operative, postoperative, donor sites, and traumatic injuries. Benacel® Dental Dressing may also be used as a wound dressing for the management and protection of oral lesions, including sores, ulcers, and injuries, such as cuts, lacerations and abrasions of the oral mucosa.

Benacel® Dental Dressing is an absorbable wound dressing made of oxidized regenerated cellulose material. Upon contact with moist oral mucosa, the material dissolves and transforms into a gelatinous material. By applying gentle pressure at this time, the material will adhere to the wound and form a barrier, protecting the wound from further irritation and pain. Benacel® Dental Dressing is sterile packaged and supplied in a variety of configurations and sizes.

The provided 510(k) summary for the Benacel® Dental Dressing does not contain detailed information about specific acceptance criteria or a comprehensive study report with quantitative results to "prove" the device meets acceptance criteria in the manner an AI/ML device would typically be evaluated. This document is for a traditional medical device (wound dressing), and its regulatory pathway focuses on substantial equivalence to predicate devices through in vitro and in vivo testing demonstrating similar performance, rather than complex statistical performance metrics.

Therefore, I cannot populate all the requested fields as they are designed for the evaluation of AI/ML-based medical devices. However, I will extract the relevant information that is present in the document.

Here's a breakdown based on the provided text, and where the requested information is not available for this type of device:

1. Table of acceptance criteria and the reported device performance:

The 510(k) summary states that "In vitro and in vivo tests demonstrate that Benacel® Dental Dressing performs substantially equivalent to predicate devices." This is a general statement rather than specific, quantitative performance against predefined acceptance criteria. The specific results of these tests are not detailed in the provided summary.

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

Not specified in the document. For in vitro and in vivo testing of a physical wound dressing, the "test set" would refer to the number of samples tested or animals/humans included in the in vivo study, and this detail is missing.

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

Not applicable or specified. For a physical wound dressing, ground truth is typically established through direct observation of physical properties, biocompatibility, and wound healing in controlled environments (in vitro) or animal/human subjects (in vivo). Expert consensus in the way it's used for AI/ML image interpretation is not relevant here.

4. Adjudication method for the test set:

Not applicable. Adjudication methods like 2+1 or 3+1 are used for evaluating human expert performance or resolving discrepancies in AI/ML outputs against ground truth. This is not a human-reader-based interpretation task.

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 wound dressing, not an AI/ML-based diagnostic or assistive tool for human readers.

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

Not applicable. This device is a physical wound dressing, not an algorithm.

7. The type of ground truth used:

Based on the mention of "in vitro and in vivo tests," the ground truth would likely be based on:

• Biocompatibility testing results: (e.g., cytotoxicity, sensitization, irritation)
• Physical performance characteristics: (e.g., absorption, adherence, dissolution time)
• Wound healing observations: In in vivo models (e.g., rate of healing, reduction in inflammation, pain management efficacy).
• Comparison to predicate device performance: The core of 510(k) substantial equivalence.

8. The sample size for the training set:

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

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

Not applicable.

Summary derived from the document:

The Benacel® Dental Dressing is intended for use as an absorbable wound dressing for extraction sites, alveolar osteitis, oral surgical wounds, and oral lesions. The claim for meeting acceptance criteria is through "substantial equivalence" to predicate devices (SaliCept®, "Sock It" oral pain gel, Hemcon®).

The study that proves the device meets the acceptance criteria is described as "in vitro and in vivo tests that demonstrate that Benacel® Dental Dressing performs substantially equivalent to predicate devices."

Key aspects provided by the document:

• Predicate Devices: SaliCept®, "Sock It" oral pain gel, Hemcon®
• Testing Types: In vitro and in vivo tests.
• Performance Claim: Substantially equivalent to predicate devices.

The document does not provide the granular detail requested for AI/ML device studies.

Ask a specific question about this device

Not Found

Not Found

I am sorry, but the provided text is a letter from the FDA regarding an administrative change to a previous substantial equivalence determination for a device called "Benacel®".

This letter does not contain any information about:

• Acceptance criteria for the device's performance.
• Any study that proves the device meets acceptance criteria.
• Details about sample sizes, data provenance, expert qualifications, ground truth, or study methodologies.

Therefore, I cannot fulfill your request to describe the acceptance criteria and the study that proves the device meets them based on the provided text.

Ask a specific question about this device