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Surgical Face Mask is intended for single use by operating room personnel and other general healthcare workers to protect both patients and healthcare workers against transfer of microorganisms, blood and body fluids, and particulate materials.

The proposed device is a three-layer, single-use, flat-pleated mask. The inner and outer layers of the mask are made of polypropylene non-woven fabric, and the middle layer is made of polypropylene melt-blown fabric. The ear loops, which are made of nylon and spandex, are held in place over the users' mouth and nose by two elastic ear loops welded to the mask. The nose clip is to allow the user to fit the facemask around their nose, which is made of polypropylene and iron wire.

The provided text is a 510(k) Summary for a Surgical Face Mask. It details the non-clinical tests performed to demonstrate the device meets acceptance criteria and is substantially equivalent to a predicate device.

Here's the information requested, based on the provided document:

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

The document references ASTM F2100-2019 Level 2 requirements as the acceptance criteria for several performance parameters.

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

The document does not specify the sample sizes used for each non-clinical test.
The data provenance is from Jiangxi Feilikang Medical Technology Co., Ltd. in China. These are non-clinical test results, implying a prospective nature of testing specifically for this submission.

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)

This section is not applicable as the document describes non-clinical performance testing of a physical medical device (surgical face mask), not an AI/software device that requires expert-established ground truth for image interpretation or diagnosis. The "ground truth" here is established by standardized laboratory testing methods.

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

This is not applicable as the document describes non-clinical performance testing of a physical medical device, not a study involving human readers or AI output adjudication.

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 is not applicable. The document explicitly states: "No clinical study is included in this submission." This submission relies on non-clinical performance testing to demonstrate substantial equivalence, not a clinical study involving human readers or AI assistance.

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

This is not applicable. The device is a physical surgical face mask, not an algorithm or AI.

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

The "ground truth" for the non-clinical tests is established by standardized laboratory test methods and international standards (e.g., ASTM, ISO). For example, bacterial filtration efficiency is measured using a biological aerosol of Staphylococcus aureus as per ASTM F2101-2019.

8. The sample size for the training set

This is not applicable. The product is a physical medical device (surgical face mask) undergoing non-clinical performance testing, not a machine learning model that requires a training set.

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

This is not applicable for the same reason as point 8.

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