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The Medical surgical mask is 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 the potential exposure to blood and body fluids. This is a single use, disposable device, provided non-sterile.

The Medical surgical mask is Flat Pleated type mask, utilizing Ear Loops way for wearing, and they all have Nose Piece design for fitting the face mask around the nose. The Medical surgical mask is manufactured with three layers. The outer layer is made of polypropylene (PP) non-woven fabric with blue color. The middle layer is filtration function and is made of polypropylene (PP) melt-blown non-woven fabric. The inner layer contact with face is made of polypropylene (PP) non-woven fabric with white color. The Medical surgical mask is single use, disposable device, provided non-sterile.

This document is a 510(k) premarket notification for a Medical Surgical Mask (K210380), aiming to demonstrate substantial equivalence to a predicate device (K160269).

The acceptance criteria for this device are based on performance standards outlined in ASTM F2100-19 for medical face masks. The study proving the device meets these criteria is a non-clinical performance test.

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

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

2. Sample size used for the test set and the data provenance

• Sample Size for Test Set:
  • For Fluid Resistance Performance (ASTM F1862M-17): The acceptance criteria state "29 out of 32 pass," indicating a sample size of 32 units tested.
  • For Particulate Filtration Efficiency (ASTM F2299), Bacterial Filtration Efficiency (ASTM F2101-19), Differential Pressure (EN 14683:2019 Annex C), and Flammability (16 CFR 1610): The exact sample size for these tests is not explicitly stated in the provided text. However, "Results (3 Lots)" implies that samples from three different production lots were tested, and all tests passed.
• Data Provenance: The document does not explicitly state the country of origin of the data or whether the tests were retrospective or prospective. Given that this is a 510(k) submission from "Shantou T&K Medical Equipment Factory Co.,Ltd" in China, it's highly probable the testing was conducted in China, and it would be prospective as it's for a new device submission.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

• This information is not applicable to this type of testing. The tests conducted are standardized physical and performance tests for medical masks, not subjective evaluations requiring expert consensus on ground truth (like image interpretation). The "ground truth" is established by the specifications of the ASTM and EN standards themselves.

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

• Adjudication methods like 2+1 or 3+1 are typically used in studies involving human interpretation (e.g., radiology reads). For these non-clinical performance tests, there is no adjudication method in the sense of reconciling different expert opinions. The pass/fail is determined by objective measurements compared against predefined 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

• No MRMC comparative effectiveness study was done. This device is a medical surgical mask, not an AI-powered diagnostic tool requiring human-in-the-loop assessment. 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

• No standalone algorithm performance was done. This is not an AI/algorithm-based device.

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

• The "ground truth" for these non-clinical tests is based on standardized test methodologies and pre-defined quantitative performance thresholds set by organizations like ASTM and EN. For example:
  • Fluid Resistance: Number of passed specimens at a specific pressure.
  • Filtration Efficiency: Measured percentage of particles/bacteria filtered.
  • Differential Pressure: Measured pressure difference across the mask material.
  • Flammability: Classification based on burn rate.

8. The sample size for the training set

• Not applicable. This device is a physical medical product (mask), not an AI model that requires a training set.

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

• Not applicable. As stated above, there is no training set for this device.

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