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510(k) Data Aggregation
(91 days)
Medical Protective Masks are intended to be worn to protect both the patient and healthcare personnel from transfer of microorganisms, body fluids and particulate material. It is intended for use in infection control practices to reduce the potential exposure to blood and body fluids. This is a single use, disposable device(s), provided non sterile.
The mask materials include four layers, the inner and outer layers are made of spun-bond polypropylene, and the two middle layers are melt-blown polypropylene and non-woven polypropylene filters, respectively.
The ear straps are held in place over the users' mouth and nose by two elastic ear straps welded to the facemask. The elastic ear straps are not made with natural rubber latex. The nose piece on the layers of facemask is to allow the user to fit the facemask around their nose, which is made of PE (polyethylene) with dual-Galvanized wire. The mask is a single use, disposable device, provided non-sterile in white color.
The provided text is a 510(k) summary for Medical Protective Masks, a Class II medical device. It does not describe an AI medical device. Therefore, it is not possible to answer the questions about acceptance criteria and study proving device performance for an AI device.
The document focuses on non-clinical performance testing of the medical masks to demonstrate substantial equivalence to a predicate device, as required for 510(k) clearance by the FDA. The tests are for physical properties and biocompatibility of the mask, not for an AI algorithm's performance.
Here's an analysis of what is provided regarding acceptance criteria and performance, as it relates to the physical mask device, to clarify why it doesn't fit the AI-focused query:
1. Table of Acceptance Criteria and Reported Device Performance (for the physical mask):
| Items | Acceptance Criteria (Level 2, ASTM F2100-19) | Performance | Result |
|---|---|---|---|
| Bacterial filtration efficiency (BFE) (%) | ≥98 | 99.9% | Pass |
| Differential pressure (mmH2O/cm²) | <6.0 mmH2O/cm² | 3.6-4.2 mmH2O/cm² | Pass |
| Sub-micron particulate filtration efficiency at 0.1 micron, % (PFE) | ≥98 | 99.63~99.84% | Pass |
| Resistance to penetration by synthetic blood (Minimum pressure in mmHg for pass result) | 29 of 32 test articles passed at 120mmHg | Test 1-3: 32 of 32 test articles passed at 120mmHg; | Pass |
| Flame spread | Class 1 | Class 1, Non Flammable | Pass |
Biocompatibility Testing:
| Testing Items | Standards | Results |
|---|---|---|
| Cytotoxicity | ISO 10993-5:2009 | Pass (Non-Cytotoxic) |
| Irritation | ISO 10993-10:2010 | Pass (Non-Irritating) |
| Sensitization | ISO 10993-10:2010 | Pass (Non-Sensitizing) |
Remaining questions from the prompt cannot be answered from the provided text as they pertain to AI/software device evaluation, not physical medical devices:
- Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
- 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)
- Adjudication method (e.g. 2+1, 3+1, none) for the test set
- 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
- If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- The type of ground truth used (expert consensus, pathology, outcomes data, etc)
- The sample size for the training set
- How the ground truth for the training set was established
The document explicitly states: "No clinical study implemented for the Medical Protective Masks." (Section 8.0). This further emphasizes that the evaluation framework is for a physical product's performance against recognized standards, not an AI algorithm.
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