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The PM Excellence SEQUR 100 Surgical Face Masks (for single use only) are indicated as protective nose and mouth covering for healthcare workers and patients. These face masks are intended for use in infection control practices as well as any medical or surgical procedure or situations where there is a risk of exposure to microorganism, body fluid, and particulate materials.

PM Excellence SEQUR 100 Surgical Face Mask (light blue) for single use only, are pleated 3-ply masks that consist of the following materials: hydrophobic nonwoven PP (polypropylene) spunbond 35 gsm, 17.5cm, light blue (outer layer); nonwoven PP (poly propylene) spunbond 30gsm, 19.5cm, white (inner layer); and nonwoven PP (polypropylene) meltblown 30gsm, 17.5cm, white (middle filter layer). The PM Excellence SEQUR 100 Surgical Face Mask Light Blue also utilizes soft, latex-free elastic earloops and malleable wire nose piece.

This document describes the performance testing for the PM Excellence SEQUR 100 Surgical Face Mask. This is a medical device, and the testing outlined is to demonstrate substantial equivalence to a predicate device, as required for a 510(k) submission to the FDA. The "acceptance criteria" and "study that proves the device meets the acceptance criteria" in this context refer to the a set of standardized performance tests that surgical masks must pass, and the results of those tests for the new device.

Here's a breakdown of the requested information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

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

The document explicitly states sample sizes for some tests:

• Fluid Resistance (ASTM F1862): The acceptance criteria and reported performance refer to "32" samples (e.g., "31 out of 32 pass"). This indicates a sample size of 32 for this specific test.
• Other Tests: For Bacterial Filtration Efficiency, Particle Filtration Efficiency, Differential Pressure, and Flammability, specific sample sizes are not explicitly stated in the provided text, but it's implied that sufficient samples were tested to generate the reported percentages and values.

Data Provenance: The data is presumed to be prospective bench testing conducted specifically for this 510(k) submission to demonstrate the performance of the PM Excellence SEQUR 100 Surgical Face Mask. The tests were performed following recognized consensus standards (e.g., ASTM, EN, ISO). The country of origin for the data is not specified, but the submission is to the U.S. FDA.

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

This section is not applicable in this context. The "ground truth" for a surgical mask's performance is established by objective, standardized laboratory measurements and test procedures defined by recognized consensus standards (e.g., ASTM, ISO, EN). It does not involve human expert consensus or interpretation in the way, for example, a diagnostic AI would require radiologist consensus for image labeling.

4. Adjudication Method for the Test Set

This section is not applicable. As stated above, the performance of a surgical mask is determined by objective physical and chemical tests, not by human interpretation or adjudication.

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

No. A MRMC study is relevant for diagnostic AI or imaging systems where human readers interpret medical images. This document describes the physical and filtration performance of a surgical face mask, which is a personal protective equipment device. Such studies are not applicable or required for this type of device.

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

This is not applicable. This device is not an algorithm or AI system. It is a physical product (surgical face mask).

7. The Type of Ground Truth Used

The "ground truth" for this device's performance is based on objective measurements performed in a laboratory setting according to internationally recognized consensus standards (e.g., ASTM F1862 for fluid resistance, ASTM F2299 for particulate filtration, EN 14683 for differential pressure, 16 CFR 1610 for flammability, and ISO 10993 for biocompatibility). These standards define the test methods and the metrics for performance.

8. The Sample Size for the Training Set

This concept is not applicable. "Training set" refers to data used to train machine learning algorithms. This submission is for a physical medical device (surgical face mask), not an AI/ML algorithm.

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

This is not applicable as there is no training set for a physical device.

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