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The United Sewing High Fluid Resistant Disposable Face Mask, United Sewing High Fluid Resistant Surgical Face Mask and United Sewing High Fluid Resistant Procedure Face Mask are intended to be worn to protect both the patient and healthcare personnel from transfer of microorganisms, body fluids, and particulate material. These face masks are intended for use in infection control practices to reduce potential exposure to blood and body fluids. These face masks are single-use, disposable devices, provided non-sterile.

The United Sewing High Fluid Resistant Disposable Face Mask is a single use, disposable, nonsterile face mask intended to cover the nose and mouth of the wearer. The subject device consists of 3 layers with the outer and inner layer made with polypropylene spunbound material and middle layer made with polypropylene melt blown material, The device has a bendable nosepiece made with Polyethylene coated single wire, and ear loops made from nylon and spandex material. This device will be provided over the counter under the trade names United Sewing High Fluid Resistant Disposable Face Mask, United Sewing High Fluid Resistant Surgical Face Mask and United Sewing High Fluid Resistant Procedure Face Mask for marketing purpose. This device is not made with natural rubber latex.

The FDA 510(k) summary for K202697 provides detailed acceptance criteria and the results of non-clinical studies for the United Sewing High Fluid Resistant Disposable Face Mask, Surgical Mask, and Procedure Mask.

1. Table of Acceptance Criteria and Reported Device Performance

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

For all performance tests (Fluid Resistance, BFE, Differential Pressure, Flammability, PFE):

• Sample Size: 32 samples were used for each test.
• Data Provenance: The document does not specify the country of origin for the data or whether it was retrospective or prospective. These are non-clinical laboratory tests, so the concepts of retrospective/prospective clinical data do not directly apply.

For Biocompatibility testing:

• The document implies that the tests were conducted using relevant samples of the device materials, but a specific sample size (e.g., number of test specimens or animals) for these tests is not explicitly stated.
• Data Provenance: Not specified, but these are also non-clinical laboratory tests.

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

• This documentation describes non-clinical performance testing of a medical mask. The "ground truth" for such tests is typically established by recognized international and national standards (e.g., ASTM, EN, ISO, CFR) and the execution of these tests by accredited laboratories.
• It does not involve human expert consensus for a "test set" in the way a clinical study or AI model validation would. The results are compared against predefined numerical acceptance criteria within the standards.

4. Adjudication Method for the Test Set

• Not applicable as this is non-clinical performance testing against established standards, not a diagnostic or classification task requiring expert adjudication of results. The results are quantitative measurements compared directly to numerical pass/fail criteria.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

• No, an MRMC comparative effectiveness study was not done. The document explicitly states: "No clinical study is included in this submission."

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

• This question is not applicable. The device described is a physical medical face mask, not an algorithm or AI software. Therefore, there is no "standalone" algorithm performance to report.

7. The Type of Ground Truth Used

• The "ground truth" for the device's performance is based on established national and international standards and analytical test methods (e.g., ASTM F1862M-17, EN 14683:2019, ASTM F2101-19, 16 CFR 1610, ASTM F2299, ISO 10993 series). The device's physical properties and performance characteristics are measured and compared against the specific pass/fail criteria defined in these standards.

8. The Sample Size for the Training Set

• This question is not applicable. This is a physical medical device, not a machine learning model, so there is no training set in the AI/ML context.

9. How the Ground Truth for the Training Set Was Established

• This question is not applicable, as there is no training set.

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