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510(k) Data Aggregation
(204 days)
The 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 surgical mask is a three-layer, flat pleated facepiece composed of a spunbond outer layer, filter layer, and spunbond (skin-contacting) inner layer. The mask is held in place with an elastic headband, and the position of the mask on the face is maintained with a nose wire and elastic beneath the chin. It is supplied non-sterile and is a single-use disposable.
Here's a breakdown of the acceptance criteria and study proving the device meets them, based on the provided text.
This document describes the validation of a Surgical Mask, not an AI/software device. Therefore, many of the typical acceptance criteria and study components for AI-driven medical devices (like MRMC studies, ground truth establishment by experts, training/test set provenance, etc.) are not applicable here. The study focuses on physical and biological performance characteristics of the mask according to recognized standards.
Acceptance Criteria and Reported Device Performance
The acceptance criteria are primarily based on established ASTM and ISO standards for surgical masks.
1. Table of Acceptance Criteria and Reported Device Performance:
| Test Methodology | Purpose | Acceptance Criteria | Reported Device Performance |
|---|---|---|---|
| ASTM F1862:2017 - Fluid Resistance Performance | Evaluate the resistance of medical face masks to penetration by the impact of a small volume (~2 mL) of a high-velocity stream of synthetic blood. | Class 3 - pass at 160mmHg Class 2 - pass at 120mmHg Class 1- pass at 80mmHg | Pass |
| ASTM F2299:2017 - Particulate Filtration Efficiency | Evaluate filtration efficiency by comparing the particle count in the feed stream (upstream) to that in the filtrate (downstream) for the materials used in medical face masks. | >98% | Pass |
| ASTM F2101:2019 - Bacterial Filtration Efficiency | Evaluate the effectiveness of medical face mask materials in preventing the passage of aerosolized bacteria, expressed in the percentage of a known quantity that does not pass the medical face mask material at a given aerosol flow rate. | >98% | Pass |
| EN 14683:2019 - Differential Pressure | Evaluate the resistance to air flow and breathability of a medical face mask by measuring differential pressure through the materials of a mask. | < 6.0mmH2O/cm² | Pass |
| 16 CFR 1610 - Flammability | Evaluate the resistance of a mask to ignition when exposed to a flame. | Class 1 | Pass |
| ISO 10993-5:2009, Cytotoxicity | Evaluate the potential of a medical device to cause cytotoxic reactions in mammalian cell culture. | Under the conditions of the study, the predicate device extract was determined to be non-cytotoxic | Pass |
| ISO 10993-10: 2021, Irritation | Evaluate the potential of a medical device to cause skin irritation. | Under the conditions of the study, the predicate device non-polar and polar extracts were determined to be non- irritating. | Pass |
Study Details (Applicable vs. Not Applicable for a Surgical Mask K-Submission)
Given that this is a 510(k) submission for a surgical mask, the validation is focused on objective, measurable physical and material properties, rather than diagnostic performance in a clinical setting with human readers or AI algorithms.
2. Sample size used for the test set and the data provenance:
- Sample Size: The document does not specify the exact sample sizes (number of masks, or number of tests conducted per mask) for each test. These are typically defined by the specific ASTM/ISO standards referenced.
- Data Provenance: Not explicitly stated regarding country of origin. The studies are non-clinical testing conducted in accordance with FDA's "Guidance for Industry and FDA Staff Surgical Masks – Premarket Notification [510(k)] Submission." This implies laboratory testing of the product itself.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- Not Applicable. For a surgical mask, "ground truth" is established by the results of standardized physical, chemical, and biological tests, not by human expert interpretation of images or clinical data. No human experts are mentioned as establishing "ground truth" for these performance tests.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:
- Not Applicable. Adjudication methods are relevant for subjective interpretations (e.g., radiological reads, pathology slides). The tests for a surgical mask are objective and quantitative.
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:
- Not Applicable. This is a physical device, not an AI or software product. No human readers or AI assistance are involved in its primary function or performance evaluation.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
- Not Applicable. This is a physical device, not an AI algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
- Standardized Test Results: The "ground truth" for this device is the objective performance measured against predefined thresholds in recognized international standards (ASTM, ISO, EN, CFR) for fluid resistance, filtration efficiency, flammability, and biocompatibility.
8. The sample size for the training set:
- Not Applicable. This device does not involve machine learning; therefore, there is no "training set."
9. How the ground truth for the training set was established:
- Not Applicable. As there is no training set for an AI model, this is irrelevant.
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