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The POSE™ Health Care Surgical Mask is intended to be worn by operating room personnel during surgical procedures to protect both the surgical patient and the operating room personnel from transfer of microorganisms, body fluids, and particulate material.

POSE™ Health Care Surgical Mask is composed of three-layers and is flat fold. The mask materials consist of an outer cover web (polypropylene spunbond, white), filter web (polypropylene melt-blown, white) and inner cover web (polypropylene thermal-bonded, white). Each mask contains ear loops to secure the mask to the user's face and mouth, as well as a fully enclosed, soft, bendable nose piece to fit over the nose. This device is not made from natural rubber latex.

The provided document is a 510(k) summary for the POSE™ Health Care Surgical Mask. It outlines the device's technical characteristics, performance data, and comparison to a predicate device to demonstrate substantial equivalence to a legally marketed device.

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

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

The study that proves the device meets the acceptance criteria is described as benchtop performance testing and biocompatibility testing.

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

• Sample Size for Benchtop Testing: For each of the benchtop performance tests (Fluid Resistance, Particulate Filtration Efficiency, Bacterial Filtration Efficiency, Differential Pressure, and Flammability), three non-sequential lots of 32 masks were tested, resulting in a total of 96 masks tested for each parameter.
• Data Provenance: The document does not specify the country of origin of the data or whether the studies were retrospective or prospective. It only states that the device was tested to conform to specific standards and guidance.

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 information is not applicable as the document describes performance testing for a surgical mask (a physical medical device) against established standards (e.g., ASTM, ISO), not a diagnostic or AI-driven device requiring expert interpretation of results to establish ground truth. The "ground truth" here is the objective measurement against the specified standard criteria.

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

This information is not applicable. Adjudication methods like 2+1 or 3+1 are typically used for studies involving human interpretation or subjective assessments, often in diagnostic imaging or clinical trials. The testing for the surgical mask involves objective laboratory measurements against predefined physical and biological 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

This information is not applicable. MRMC studies are used to evaluate the diagnostic performance of human readers, often with and without AI assistance, especially in radiology or pathology. The POSE™ Health Care Surgical Mask is a physical medical device, not an AI-driven diagnostic tool.

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

This information is not applicable. This question refers to the performance of an algorithm or AI independently. The POSE™ Health Care Surgical Mask is a physical medical device.

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

The "ground truth" for the performance criteria of the surgical mask is based on established industry standards and regulatory guidance. These standards (e.g., ASTM F1862, ASTM F2299, ASTM F2101, ISO 10993) define the objective measurements and thresholds for a surgical mask to be considered safe and effective for its intended use. For instance, fluid resistance is measured against a specific pressure (160mmHg), and filtration efficiency against a percentage (≥98%). Biocompatibility is assessed against the criteria of being non-cytotoxic, non-sensitizing, and non-irritating.

8. The sample size for the training set

This information is not applicable. Training sets are relevant for machine learning or AI models. The device in question is a physical surgical mask, and its performance is evaluated through benchtop and biocompatibility testing, not through training data for an algorithm.

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

This information is not applicable for the same reason as above (point 8).

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