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The device is intended to be used by trained physicians during neurosurgical procedures to protect neural tissues from drying, abrasion, or contamination and to absorb fluids.

The device is indicated for use by trained physicians during neurosurgical procedures to protect neural tissues from drying, abrasion, or contamination and to absorb fluids:

The device is a non-adherent, strung, x-ray detectable surgical sponge that is sterile and disposable. The American Surgical Sponges (brand) product line is made from cotton, polyester, or rayon in various sizes and shapes and has been first marketed since 1985. The current cleared product line includes the Telfa® Sponges, which are cotton surgical sponges covered on both sides with polyethylene terephthalate. The Telfa® Sponges provide additional stiffness to the neurosurgical sponges. The new proposed addition to the product line includes neurosurgical sponges (cotton, polyester, or rayon) covered on one side with a thin single layer of polytetrafluoroethylene (PTFE) to enhance the material stiffness and non-adherence properties while maintaining flexibility of the sponge. The polytetrafluoroethylene (PTFE) layer will be provided in a choice of three thicknesses, 0.001", 0.003" or 0.005". The sponges range in size from 6mm × 76mm × 76mm.

The presented text describes a 510(k) summary for the American Surgical Company's Neurosurgical Sponges, specifically focusing on the addition of a polytetrafluoroethylene (PTFE) layer to the sponges. The document details the product description, intended use, indications for use, and a comparison to a predicate device to establish substantial equivalence.

However, this document does not contain information about acceptance criteria for device performance, nor does it describe a study that proves the device meets such criteria in the way typically expected for an AI/ML medical device.

Here's why and what information is present:

• Type of Device: The device described is a physical medical device (neurosurgical sponges), not a software or AI/ML algorithm. Therefore, the typical "acceptance criteria" and "performance study" inquiries relevant to AI/ML (like sensitivity, specificity, AUC, etc., and studies involving human reader performance or standalone algorithm performance) are not applicable in this context.
• Regulatory Pathway: This is a 510(k) submission, which focuses on demonstrating substantial equivalence to a legally marketed predicate device. The primary evidence presented is that the modified device has the "same indications for use and intended use," "same principle of operation," "same basic design," "equivalent materials," "same shelf life," and "packaged and sterilized using the same materials and processes."

Given this, I cannot fulfill most of your request as the information is not present in the provided text. I will address the points that can be inferred or directly stated from the document, acknowledging where information is missing due to the nature of the device and submission.

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

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Test Set Sample Size: Not applicable/not specified for the type of device. The biocompatibility tests would have involved specific animal models or in-vitro cell cultures, but these details are not provided. Peel testing would involve a sample of the sponges.
• Data Provenance: The biocompatibility studies were conducted in compliance with U.S. Food and Drug Administration Good Laboratory Practice (GLP) regulations, implying the testing was performed in the US or under US GLP standards. Details on retrospective/prospective are not applicable for material testing.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

• Not applicable. This device is a physical sponge, not an AI/ML algorithm requiring expert opinion for ground truth. Biocompatibility and mechanical testing do not involve expert consensus on medical images or diagnoses.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

• Not applicable. This refers to adjudication of ground truth for AI/ML performance studies, which is not relevant here.

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. This is a physical medical device, not an AI/ML algorithm. An MRMC study is not relevant.

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

• No. This is a physical medical device, not an AI/ML algorithm. A "standalone performance" study in the context of AI is not relevant.

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

• The "ground truth" for the biocompatibility testing would be the established biological responses to the materials (e.g., absence of cytotoxicity, irritation, sensitization) as defined by ISO 10993 standards.
• For the peel testing, the "ground truth" would be the measured force required to delaminate the layers.

8. The sample size for the training set

• Not applicable. There is no AI/ML algorithm involved, so there is no training set.

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

• Not applicable. There is no AI/ML algorithm involved, so there is no training set or ground truth for one.

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The device is a neurosurgical pad used during surgery to protect nervous tissue, absorb fluids, or stop bleeding.

The device is a non-adherent, strung, x-ray detectable surgical sponge that is sterile and disposable. The Delicot product line is made from lyocell, a manmade fiber derived from cellulose, better known under the brand name of Tencel - a type of rayon; it is supplied in various lengths and widths and has been marketed since 1990. The Delicot product line is one of three rayon-based sponges. The Delicot sponges are manufactured using Dupont Style 8623 consisting of 100% lyocell. Dupont has discontinued the manufacture of Style 8623. Dupont Style 8471 consisting of 58% polyester and 42% lyocell is our proposed replacement.

The provided text is a 510(k) summary for a medical device (Delicot Neurosurgical Sponge) seeking substantial equivalence to a predicate device. It does not describe a study proving the device meets specific acceptance criteria in the way a diagnostic AI device or a device with measurable performance metrics would. Instead, the submission focuses on demonstrating equivalence through material and process changes.

Therefore, many of the requested categories are not applicable to this type of submission.

Here's an analysis based on the provided text:

Description of Acceptance Criteria and Study to Prove Device Meets Criteria:

The core "acceptance criteria" in this 510(k) submission is to demonstrate substantial equivalence to a previously cleared predicate device. The study to prove this involves comparing the modified device (using a new material) to the predicate device across various aspects.

The specific "acceptance criteria" are implied by the points of comparison for substantial equivalence:

• Same indications for use and intended use.
• Same principle of operation.
• Same basic design.
• Equivalent materials.
• Same shelf life.
• Packaged and sterilized using the same materials and processes.

The study conducted to prove this focused on Biocompatibility Testing and Comparability Testing.

1. Table of Acceptance Criteria and Reported Device Performance:

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

• Sample Size: The document does not specify the sample size for the biocompatibility testing or the comparability testing.
• Data Provenance: Not explicitly stated, but typically, such testing is conducted in a laboratory setting, either internally or at a contract research organization. The biocompatibility testing was conducted "in compliance with U.S. Food and Drug Administration Good Laboratory Practice (GLP) regulations set forth in 21 CFR Part 58." This implies a systematic, controlled study. It is prospective for the device under review.

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

• Not applicable. This is not a study involving human interpretation of data where "ground truth" would be established by experts (e.g., radiologists reading images). Biocompatibility and comparability testing relies on objective laboratory assays and measurements.

4. Adjudication Method for the Test Set:

• Not applicable. There is no human interpretation or adjudication described for these materials and biocompatibility tests.

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 is a submission for a physical medical device (surgical sponge), not an AI/diagnostic software device.

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

• Not applicable. This is a physical medical device, not an algorithm.

7. The Type of Ground Truth Used:

• Biocompatibility: The "ground truth" is defined by established international standards (ISO-10993) and regulatory guidelines (FDA's Blue Book Guidance G95-1) for evaluating biological response and toxicity. The test results (e.g., cell viability in cytotoxicity assays) are compared against these predetermined thresholds for what constitutes a safe response.
• Comparability: The "ground truth" for evaluating the "equivalence" of the new material for mechanical or functional properties (which are not detailed in this summary but would be part of a comparability study) would be the performance characteristics of the predicate device. The new device's performance would need to fall within an acceptable range of the predicate's performance.

8. The Sample Size for the Training Set:

• Not applicable. This is not a machine learning or AI device that requires a training set.

9. How the Ground Truth for the Training Set was Established:

• Not applicable. This is not a machine learning or AI device.

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