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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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The GreenCross Surgical Masks are indicated as a protective nose and mouth covering for health care workers and patients involved in medical and surgical procedures. The masks are indicated in any procedure or situations where there is a risk of microorganism, body fluid, and particulate aerosol transfer.

GreenCross surgical masks, Type: Earloop or Tie-on, are pleated 3-ply mask. Inner and outer layers are made of 100% spun-bond polypropylene. Middle player is made of 100% meltblown polypropylene filter media. Ear-loops are made of soft latex free elastic loops. All of the materials used in the construction of the GreenCross surgical masks are being used in currently marketed devices, except the nose piece used plastic wire instead of aluminum wire.

K123787: GreenCross Surgical Mask Acceptance Criteria and Performance Study Analysis

This submission describes the non-clinical performance testing of the GreenCross Surgical Mask to establish substantial equivalence to a predicate device (K101000).

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria for each test are implicitly set by achieving comparable performance to the predicate device, or by meeting the "relevant requirements in the test standards." The reported device performance is directly compared to the predicate device's performance.

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

The document does not explicitly state the specific sample sizes used for each individual non-clinical test (e.g., number of masks tested for BFE, PFE). For the Fluid Resistance test (ASTM F1862), the result "29 out of 32 pass" indicates a sample size of 32 masks for that particular test.

The data provenance is from non-clinical tests conducted by the manufacturer, Jingzhou Haixin Green Cross Medical Products Co., Ltd. The country of origin for the testing is not explicitly stated, but the manufacturer is based in Wuhan City, Hubei, P. R, China. These are prospective test results generated specifically for this submission.

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

This section is not applicable. The ground truth for this device is based on objective, standardized laboratory performance tests designed to measure physical properties and filtration capabilities. It does not involve human expert interpretation or subjective evaluation.

4. Adjudication Method for the Test Set

This section is not applicable. As the ground truth is established through standardized laboratory tests, there is no need for expert adjudication.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

An MRMC study was not performed. This submission is for a surgical mask, and its performance is evaluated through non-clinical bench testing, not by comparing human reader performance.

6. Standalone (Algorithm Only) Performance

This section is not applicable. As this is a physical medical device (surgical mask), there is no algorithm or AI involved.

7. Type of Ground Truth Used

The ground truth used for evaluating the GreenCross Surgical Mask is based on objective, standardized laboratory performance testing as outlined by international and national standards (e.g., ASTM F2101, ASTM F2299, ASTM F1862, MIL-M-36945C, 16CFR 1610, ISO 10993). These standards define specific methodologies and criteria for measuring the performance attributes of surgical masks.

8. Sample Size for the Training Set

This section is not applicable. This is a physical device, not an AI/ML algorithm, so there is no "training set."

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

This section is not applicable. There is no training set for a physical surgical mask.

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