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510(k) Data Aggregation
(113 days)
When properly worn, the surgical face masks are intent and healthcare workers from transfer of microorganisms, body fluids and particulate material. The face masks are intended for use in infection control practices to reduce the potential exposure to blood and body fluids. This device is disposable, non-sterile and for single use only.
Magnum is a surgical face mask identified by Regulation 21 CFR 878.4040 under FDA product code, FXX. This medical device is offered in a single color – blue.
The inner and outer layers are made of spun-bond polypropylene non-woven fabric, and the middle layer is made of melt blown filter media. The nose wire contained in the proposed device is in the layers of face mask to allow the user to fit the face mask around their nose, which is made of PVC coated aluminum wire.
The model 2200 is level 2 surgical face mask and the model 2300 is level 3 surgical face mask. Both these models are provided with ear loops to hold and fit the face mask in place over the user's mouth and nose. The ear loops are made of knitted elastic.
The model 1200 is level 2 surgical face mask and the model 1300 is level 3 surgical face mask. Both these models are provided with tie back to hold and fit the face mask in place over the user's mouth and nose. The tie back string is made of spun-bond polypropylene non-woven fabric.
The dimensions of the test item are: length- 172 ± 3 mm and width- 95 ± 3 mm.
The surgical masks are single-use, disposable devices, provided non-sterile.
The provided text describes the acceptance criteria and performance data for Magnum surgical masks in their 510(k) submission to the FDA. Here's a breakdown of the requested information:
1. A table of acceptance criteria and the reported device performance
The document provides two tables (Table 2 and what is labeled as "Table 2" but is actually a third table, both on page 9) summarizing the performance testing for different models (Level 3 models 1300 and 2300, and Level 2 models 1200 and 2200). I will combine these into a single table for clarity, indicating the specific level for the criteria.
| Test Performed | Acceptance Criteria (Level 3 Models) | Reported Performance (Model 1300) | Reported Performance (Model 2300) | Acceptance Criteria (Level 2 Models) | Reported Performance (Model 1200) | Reported Performance (Model 2200) | Overall Result |
|---|---|---|---|---|---|---|---|
| Fluid resistance (ASTM F1862/F1862M-17) | Pass at 160 mmHg | Pass at 160 mmHg | Pass at 160 mmHg | Pass at 120 mmHg | Pass at 120 mmHg | Pass at 120 mmHg | Pass |
| Particulate Filtration Efficiency (PFE) (ASTM F2299/F2299M-03(2017)) | ≥ 98% | > 98% | > 98% | ≥ 98% | > 98% | > 98% | Pass |
| Bacterial Filtration Efficiency (BFE) (ASTM F2101-19) | ≥ 98% | > 98% | > 98% | ≥ 98% | > 98% | > 98% | Pass |
| Differential pressure (ΔP) (EN 14683 Annex C: 2019) | < 6.0 mmH2O/cm² | < 3.0 mmH2O/cm² | < 3.0 mmH2O/cm² | < 6.0 mmH2O/cm² | < 3.0 mmH2O/cm² | < 3.0 mmH2O/cm² | Pass |
| Flammability (16 CFR 1610) | Class 1 | Class 1 | Class 1 | Class 1 | Class 1 | Class 1 | Pass |
Biocompatibility Acceptance Criteria and Performance:
| Test Performed | Standard | Acceptance Criteria/Expected Outcome | Reported Performance (Proposed Device) | Overall Result |
|---|---|---|---|---|
| In-vitro Cytotoxicity | ISO 10993-5:2009 | Non-cytotoxic | Non-cytotoxic | Pass |
| Skin Irritation | ISO 10993-23:2021 | Non-irritating | Non-irritating | Pass |
| Skin Sensitization | ISO 10993-10:2021 | Non-sensitizer | Non-sensitizing | Pass |
2. Sample size used for the test set and the data provenance
The document does not specify the exact sample sizes used for the non-clinical performance tests (fluid resistance, PFE, BFE, differential pressure, flammability) or the biocompatibility tests (cytotoxicity, skin irritation, skin sensitization). However, these are standard laboratory tests typically performed on a limited number of samples to demonstrate compliance with the specified ASTM, EN, ISO, and CFR standards.
The data provenance is described as "Non-Clinical Data" and "Performance Tests" performed on the "proposed device" (Magnum surgical masks). The tests were conducted according to established international and US standards. The document does not explicitly state the country of origin for the testing itself, but the manufacturer is based in India. This is retrospective testing performed on manufactured devices to demonstrate compliance.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
Not applicable. This submission is for a physical medical device (surgical masks) and relies on objective, standardized non-clinical performance and biocompatibility testing, not expert interpretation of data or images. Therefore, there is no concept of "ground truth" established by experts in the context of this device's testing.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
Not applicable. As noted above, the testing involves objective measurement against industry standards, not subjective interpretations requiring adjudication.
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 not an AI-assisted device. Magnum surgical masks are a physical product intended to protect against exposure to microorganisms, body fluids, and particulate material.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Not applicable. This is not an algorithm or AI device.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
For the performance and biocompatibility tests, the "ground truth" is defined by the established and published criteria within the referenced standards (e.g., ASTM F2100-19, ASTM F1862/F1862M-17, ISO 10993 series, etc.). These standards set objective thresholds for performance (e.g., >98% filtration efficiency, pass at 160 mmHg fluid resistance) and safety (e.g., non-cytotoxic, non-sensitizing). Compliance with these numerical or qualitative thresholds constitutes meeting the acceptance criteria.
8. The sample size for the training set
Not applicable. This is a physical product, not a machine learning model, so there is no training set.
9. How the ground truth for the training set was established
Not applicable. There is no training set for this device.
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