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The Bodygard SFS Surgical Gown Level 3 is intended to be worn by operating room personnel during surgical procedure to protect both the surgical patient and the operating room personnel from transfer of microorganisms, body fluids, and particulate material.

Per ANSI/AAMI PB70:2012 Liquid barrier performance and classification of protective apparel and drapes intended for use in health care facilities, Bodygard SFS Surgical Gown Level 3 met the requirements for Level 3 classification.

The Bodygard SFS Surgical Gown Level 3 is a poly reinforced surgical gown, SMS Nonwoven/Film/SMS Nonwoven (SFS) that provides AAMI Level 3 liquid barrier protection in the critical zones (arms and chest) and non-critical zones of the gown. The Bodygard SFS Surgical Gown Level 3 is manufactured using ultrasonic bonding technique and are available in four different sizes (M, L, XL, and XXL).

Per ANSI/AAMI PB70:2012 Liquid barrier performance and classification of protective apparel and drapes intended for use in health care facilities. The Bodygard SFS Surgical Gown Level 3, meets the requirements for Level 3 classification, are disposable medical devices and provided in sterile.

The provided document is limited to a 510(k) summary for a surgical gown (Bodygard SFS Surgical Gown Level 3). It details non-clinical performance and substantial equivalence to a predicate device, but it does not contain information on clinical studies, AI algorithms, or human reader performance. Therefore, I cannot answer questions related to those topics.

Here's a breakdown of what can be extracted from the document regarding acceptance criteria and non-clinical studies:

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 the exact sample sizes used for each non-clinical test. The acceptance criteria for many tests mention "AQL 4%, RQL=20%", which refers to Acceptance Quality Limit and Rejection Quality Limit, indicating a statistically driven sampling plan, but the specific number of units tested is not provided.

The data provenance is from non-clinical laboratory tests conducted for the purpose of demonstrating device performance against established standards for surgical gowns. No details about country of origin of data are provided beyond the manufacturer and contact person being in Turkey and Virginia, respectively. All tests appear to be prospective as they were conducted specifically for this submission.

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. The product is a physical medical device (surgical gown), not an AI algorithm requiring expert ground truth for image or data interpretation. The "ground truth" for these tests are the objective measurements and pass/fail criteria of the specified ASTM, AATCC, ISO, and CFR standards.

4. Adjudication method for the test set

This question is not applicable. There is no expert review or adjudication process described for these non-clinical physical and chemical tests. The results are typically objectively measured against the specified acceptance criteria.

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

This question is not applicable. The document describes a physical medical device (surgical gown), not an AI-powered diagnostic or assistive technology. No MRMC study or AI component is mentioned.

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

This question is not applicable, as the device is a physical surgical gown and does not involve an algorithm.

7. The type of ground truth used

The "ground truth" for the non-clinical tests are the established international and national standards and test methods (e.g., AATCC, ASTM, ISO, CFR) for the performance and safety of surgical apparel. These standards define objective pass/fail criteria based on physical, chemical, and biological properties.

8. The sample size for the training set

This question is not applicable. The device is a physical product and does not involve an AI algorithm with a training set.

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

This question is not applicable, as there is no training set for a physical surgical gown.

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Myflon Surgical Mask Level 3 is intended to be worn to protect both the patient and healthcare personnel from transfer of microorganisms, body fluids and particulate material. This face mask is intended for use in infection control practices to reduce the potential exposure to blood and body fluids. This is a single use, disposable device provided non-sterile.

The Myflon Surgical Mask Level 3 is blue in color, composed of three-layers, a flat-pleated type mask, utilizing ear loops for wearing. The Myflon Surgical Mask Level 3 materials consist of an outer cover (polypropylene spunbond, blue), middle filtration layer (polypropylene, melt-blown, white), and inner cover comfort/support layer web (polypropylene spunbond, white). Each mask has stretchable elastic laminate (Spunbond/elastic film/spunbond bond) ear loops to secure the mask over the user's mouth and nose and includes a polyethylene/ polypropylene coated wire nosepiece to provide a firm fit over the face and nose. This face mask is a single use, disposable device, provided non-sterile. This device is not made with natural rubber latex.

The provided text is a 510(k) summary for a surgical mask (Myflon Surgical Mask Level 3). It details the device, its intended use, and substantial equivalence to a predicate device based on non-clinical testing. It does not describe an AI/ML-driven medical device, an algorithm's performance, or any human-in-the-loop studies. Therefore, I cannot extract the information required to answer your specific questions related to AI/ML device acceptance criteria and study details.

The document explicitly states: "No clinical tests were performed." and describes the product as a physical surgical mask, not a software or AI device.

Therefore, I am unable to provide the requested information regarding:

1. A table of acceptance criteria and reported device performance for an AI/ML device.
2. Sample size used for the test set and data provenance.
3. Number of experts and their qualifications for establishing ground truth.
4. Adjudication method for the test set.
5. MRMC comparative effectiveness study and effect size.
6. Standalone (algorithm-only) performance.
7. Type of ground truth used.
8. Sample size for the training set.
9. How ground truth for the training set was established.

The acceptance criteria and performance data provided in the document pertain to the physical properties of the surgical mask, such as barrier testing (fluid resistance, particle filtration, bacterial filtration), flammability, differential pressure, and biocompatibility.

Here is the table of acceptance criteria and reported device performance for the surgical mask (as provided in the document), which is the only relevant information from the text:

Acceptance Criteria and Reported Device Performance (Myflon Surgical Mask Level 3)

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