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510(k) Data Aggregation
(138 days)
The Disposable Medical Mask is 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. It is a single use, disposable device(s), provided non-sterile.
The Disposable Medical Mask is a blue, flat pleated type mask, which utilizes an Earloop to Wear. It has a nose piece design to fit the facemask around the nose. The Disposable Medical Masks are manufactured with three layers and the inner and outer layers are made of spun-bond polypropylene, and the middle layer is made of melt-blown polypropylene filter. The model of the proposed device, earloop, is held in place over the user's mouth and nose by two elastic ear loops welded to the facemask. The elastic ear loops are not made with natural rubber latex. The nose piece in the mask is in the facemask layers to allow the user to fit the facemask around their nose, made of malleable aluminum wire. The Disposable Medical Masks are sold non-sterile and are intended to be a single-use, disposable device. This product contains no components made from natural rubber latex.
This document is a 510(k) premarket notification for a medical device: a Disposable Medical Mask (K212826). The information provided focuses on demonstrating substantial equivalence to a predicate device, rather than proving the device meets a set of acceptance criteria through a clinical study that uses AI or human readers for diagnosis. Therefore, several aspects of your request (related to AI, human readers, ground truth establishment for a training set, the number of experts, and adjudication methods for a test set) are not applicable to the content provided.
However, I can extract the acceptance criteria and performance data for the physical properties and biocompatibility of the medical mask, as these are the "device performance" aspects evaluated in this submission for regulatory clearance.
Here's a breakdown of the requested information based on the provided document:
1. A table of acceptance criteria and the reported device performance
The document presents performance criteria for the Disposable Medical Mask based on established ASTM and EN standards for medical face masks.
| Test / Performance Metric | Standard(s) | Acceptance Criteria (for Level 2 Mask) | Reported Device Performance | Pass/Fail |
|---|---|---|---|---|
| Bacterial Filtration Efficiency (BFE, %) | ASTM F2101 | ≥ 98% | Average 99.79% | Pass |
| Particulate Filtration Efficiency (PFE, at 0.1µm, %) | ASTM F2299 | ≥ 98% | Average 99.13% | Pass |
| Differential Pressure (Delta P, mm H2O/cm²) | ASTM F2100-19, EN 14683:2019, Annex C | < 6.0 mm H2O/cm² | 4.4 mm H2O/cm² | Pass |
| Resistance to penetration by synthetic blood (minimum pressure in mmHg for pass result) | ASTM F1862/F1862M-17 | 29 out of 32 pass at 120 mmHg | 31 of 32 pass at 120 mmHg | Pass |
| Flame Spread | 16 CFR 1610 | Class 1 Non-Flammable | Class 1 Non-Flammable | Pass |
| In Vitro Cytotoxicity | ISO10993-5: 2009 | Non-cytotoxic | Non-cytotoxic | Pass |
| Skin Sensitization | ISO10993-10: 2010 | Non-sensitizing | Non-sensitizing | Pass |
| Skin Irritation | ISO10993-10 | Non-irritating | Non-irritating | Pass |
2. Sample sized used for the test set and the data provenance
- Sample Size for Test Set: The document indicates specific sample sizes for certain tests, e.g., "31 out of 32 pass" for fluid resistance. This implies a sample size of 32 masks for that particular test. Other tests, such as BFE, PFE, and Differential Pressure, typically involve multiple measurements across a sample of materials/masks, but specific sample numbers (like 'n=X') are not explicitly stated for each test beyond the fluid resistance.
- Data Provenance: The tests are conducted for the purpose of a US FDA 510(k) submission. The manufacturer is Jiangsu Nanfang Medical Co., Ltd. from Jiangsu Province, China. The testing itself is non-clinical, involving laboratory assessments of physical and biological properties. The document does not specify whether the data was retrospective or prospective in the sense of a clinical trial; these are manufacturing and materials tests conducted on samples of the device.
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 is not applicable. The "ground truth" for a medical mask in this context refers to its physical and biocompatibility properties as measured by standardized laboratory methods (e.g., how much fluid it resists, its filtration efficiency). These are objective measurements, not subjective interpretations by human experts like radiologists.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
This is not applicable. As the ground truth is established through objective laboratory testing rather than human interpretation, there's no need for an adjudication process involving multiple readers.
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 is not applicable. This submission is for a disposable medical mask, a physical barrier device, and does not involve AI assistance, image interpretation, or human reader studies.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
This is not applicable. There is no algorithm or AI involved in this device.
7. The type of ground truth used (expert concensus, pathology, outcomes data, etc)
The "ground truth" for the device's performance is established through measurements against recognized international consensus standards and test methods. For example:
- Performance: ASTM F2101 for BFE, ASTM F2299 for PFE, ASTM F1862/F1862M-17 for fluid resistance, EN 14683:2019 for differential pressure, and 16 CFR 1610 for flammability.
- Biocompatibility: ISO 10993 series (ISO10993-5 for cytotoxicity, ISO10993-10 for sensitization and irritation).
These standards define the methodology for determining if the device's material properties meet specified safety and performance benchmarks.
8. The sample size for the training set
This is not applicable. The device is a physical product (medical mask) and does not involve AI or machine learning models that require a "training set" of data.
9. How the ground truth for the training set was established
This is not applicable for the same reason as point 8.
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