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510(k) Data Aggregation
(87 days)
The Altor Safety 4-Ply Surgical Mask is intended to be worn to protect both the patient and healthcare professional from transfer of microorganisms, body fluids, and particulate material. The Altor Safety 4-Ply Surgical Mask is intended for use in infection control practices to reduce the potential exposure to blood and body fluids. This is a single use, non- sterile, disposable device.
The Altor Safety 4-Ply Surgical Mask is a flat-pleated mask with ear loops and nose piece for fitting and securing the mask to the to the user's face. The mask outward facing layer is blue in color, using color master batch. The device is manufactured with 4 layers: 2-Outer Facing Layers: Spunbond nonwoven polypropylene (Blue), Middle Layer: Melt Blown nonwoven polypropylene (White) and Inner Layer: Spunbond nonwoven polypropylene (White). Other Materials used include the Ear loops which are made from Spandex / Nylon. The subject device is provided non-sterile and is a single use, disposable device.
This document is a 510(k) summary for a surgical mask (Altor Safety 4-Ply Surgical Mask, Model: 62232). It focuses on demonstrating substantial equivalence to a predicate device through non-clinical performance testing rather than a study involving human or AI performance. Therefore, many of the requested elements for a study proving a device meets acceptance criteria, particularly for AI/human reader performance, are not applicable to this document.
However, I can extract the acceptance criteria (pass criteria) and reported device performance for the physical and biological characteristics of the surgical mask, as detailed in the non-clinical performance testing section.
Here's a breakdown of the requested information based solely on the provided document:
1. A table of acceptance criteria and the reported device performance
| Test Method | Purpose | Acceptance Criteria (Pass Criteria) | Reported Device Performance (Results) |
|---|---|---|---|
| ASTM F2101-19 (Bacterial Filtration Efficiency - BFE) | Evaluate Bacterial filtration efficiency (%) | ≥98% | 3 lots tested with total 96 samples, 94/96 Passed at ≥98% /Pass (Note: Listed as 99.60% in Table 1) |
| EN 14683: 2019, Annex C (Differential Pressure - Delta-P) | Evaluate Differential pressure (Delta-P) | <6.0 mmH2O/cm² | 3 lots tested with total 96 samples, 92/96 Passed <6 mmH2O/cm² / Pass (Note: Listed as 3.5mmH2O/cm² in Table 1 for average of 3 lots with means of 4.2, 3.2, 3.1) |
| ASTM F2299-03 (Particulate Filtration Efficiency - PFE) | Evaluate Sub-micron particulate filtration efficiency at 0.1 micron, % (PFE) | ≥98% | 3 lots tested with total 96 samples, 96/96 Passed at ≥98% / Pass (Note: Listed as ≥99% in Table 1) |
| ASTM F1862M-17 (Resistance to Penetration by Synthetic Blood) | Evaluate Resistance to penetration by synthetic blood | Fluid resistant claimed at 160 mm Hg | 3 lots tested with total 96 samples, 95 of 96 test articles passed at 160mmHg /Pass |
| 16 CFR Part 1610 (Flammability) | Evaluate Flame spread | Class 1 | 3 lots tested with total 96 samples, 96/96 Passed ≥3 seconds burn Time- Class 1 / Pass |
| ISO 10993-5:2009 (Cytotoxicity) | Evaluate cytotoxicity | Non-cytotoxic | The proposed device extract was determined to be non-cytotoxic. |
| ISO 10993-10:2010 (Skin Irritation) | Evaluate irritation | Non-irritating | The proposed device non-polar and polar extracts were determined to be non-irritating. |
| ISO 10993-10:2010 (Skin Sensitization) | Evaluate skin sensitization | Non-sensitizing | The proposed device non-polar and polar extracts were determined to be non-sensitizing. |
2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
- Sample Size for Non-Clinical Testing: For most performance tests (BFE, Delta-P, PFE, Flammability, Fluid Resistance), 3 lots were tested, with generally 96 samples in total (e.g., 96 samples for BFE, PFE, Flammability; 95 of 96 passed for Fluid Resistance). The specific number of samples for biocompatibility tests (cytotoxicity, irritation, sensitization) is not explicitly stated, but the results indicate tests were conducted.
- Data Provenance: Not specified in the document. This is a 510(k) submission, and the tests would typically be performed by accredited labs, but the country of origin of the labs or the data generation is not mentioned. The data is presented as retrospective in the context of this submission, meaning the tests were already conducted when the submission was prepared.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
N/A. This document pertains to the physical and biological performance of a surgical mask, not an AI or diagnostic device requiring expert interpretation for ground truth. Ground truth for these tests is established by standardized test methods and laboratory measurements.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
N/A. As this is not a study involving human or AI interpretation, there is no adjudication method for establishing ground truth. The results are objective measurements from laboratory tests.
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
N/A. No MRMC study was conducted. This is a 510(k) submission for a physical medical device (surgical mask), not an AI-assisted diagnostic tool.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done
N/A. No standalone AI algorithm performance was evaluated.
7. The type of ground truth used (expert concensus, pathology, outcomes data, etc)
The "ground truth" for the acceptance criteria discussed in this document is based on established international and national standards for medical devices, specifically surgical masks (e.g., ASTM F2100, EN 14683, ISO 10993 series). The performance of the device is measured against these objective, quantitative criteria.
8. The sample size for the training set
N/A. There is no training set mentioned as this is not an AI/machine learning device.
9. How the ground truth for the training set was established
N/A. There is no training set and therefore no ground truth establishment for a training set.
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