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510(k) Data Aggregation
(296 days)
The GD Disposable Medical Face 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(s), provided non-sterile.
The GD Disposable Medical Face Mask is a single use multi-layer Level 2 surgical mask. It houses a meltblown polypropylene filter between an outer and inner layer of spunbond polypropylene that covers the nose and mouth of the end user and held in place by a pliable nose piece and ear loops. Contact duration is less than 24 hours.
The provided document is a 510(k) summary for a medical device: the GD Disposable Medical Face Mask. It outlines the device's characteristics, intended use, and performance data to demonstrate substantial equivalence to a legally marketed predicate device.
However, the request asks for information related to Acceptance Criteria and a study proving a software-based or AI-enabled medical device meets these criteria. The document provided is for a physical medical device (a face mask) and its performance is evaluated through physical and material tests, not AI model performance metrics.
Therefore, many aspects of your request, such as "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", "Adjudication method", "MRMC comparative effectiveness study", "Standalone (i.e. algorithm only without human-in-the-loop performance)", and "Training set", are not applicable to this type of device and its regulatory submission.
I will, however, extract the acceptance criteria and reported device performance from the document as they pertain to a physical face mask, which is the closest match to your request for "Acceptance Criteria and the study that proves the device meets the acceptance criteria."
Acceptance Criteria and Device Performance for GD Disposable Medical Face Mask
The document details performance testing for the GD Disposable Medical Face Mask to demonstrate its substantial equivalence to a predicate device (K160269 Surgical Face Masks). The "Summary of Performance Data" section provides the "Acceptance Criteria" and the "Results" (reported device performance).
1. Table of Acceptance Criteria and the Reported Device Performance:
Name of the Test / Methodology | Purpose | Acceptance Criteria | Results |
---|---|---|---|
ISO 10993-5: 2009 Biological Evaluation Of Medical Devices -- Part 5: Tests For In Vitro Cytotoxicity | Safety Testing | Non-Cytotoxic | Pass |
ISO 10993-10: 2010 Biological Evaluation Of Medical Devices - Part 10: Tests For Irritation And Skin Sensitization | Safety Testing | Non-Irritating and Non-Sensitizing | Pass |
ASTM F1862-17, Standard Test Method For Resistance Of Medical Face Masks To Penetration By Synthetic Blood (Horizontal Projection Of Fixed Volume At A Known Velocity) | Barrier Testing | Pass at 120mm Hg | Pass |
ASTM F2101-19, Standard Test Method For Evaluating The Bacterial Filtration Efficiency (BFE) Of Medical Face Mask Materials, Using A Biological Aerosol Of Staphylococcus Aureus; | Barrier Testing | ≥98% | Pass |
ASTM F2299-03, Stand test method for determining the initial efficiency of materials used in medical face masks to penetration by particulates using latex spheres; | Barrier Testing | ≥98% | Pass |
EN 14683: European standard for face masks (This row seems to describe a test for breathability based on the predicate comparison, although the value is not explicitly stated in the "Summary of Performance Data" table. The predicate comparison table lists "GD Level 2 Mask" as "Pass at 99.4%" for particle filtration, but here it states EN 14683 as "Physical Testing" with "99.9% (Predicate: Pass at >98% - Similar) |
- Flammability Class (16 CFR 1610): GD Level 2 Mask: Class I (Same as predicate)
2. Sample sized used for the test set and the data provenance:
- The document does not specify the exact sample sizes used for each of the physical and biological tests conducted (e.g., how many masks were tested for fluid resistance or BFE).
- Data provenance: The testing was performed for Jiangsu Guangda Medical Material Group Co., Ltd. located in Jiangsu Province, China. The document does not specify whether the data is retrospective or prospective, but given it's for a 510(k) submission, it would be data generated for the submission to demonstrate compliance.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- This is Not Applicable. The "ground truth" for this medical device is established through standardized laboratory testing protocols (e.g., ASTM, ISO standards) for physical and biological properties, not through expert consensus on medical images or clinical outcomes.
4. Adjudication method for the test set:
- This is Not Applicable. Adjudication methods like 2+1 or 3+1 refer to agreement among human readers for image interpretation, which is not relevant for testing a physical face mask. The results of the tests (e.g., "Pass," "Non-Cytotoxic," percentages) are direct measurements against predefined criteria.
5. If a multi reader multi case (MRMC) comparative effectiveness study was done:
- This is Not Applicable. An MRMC study is for evaluating the performance of diagnostic tools (often imaging-based AI) with and without human assistance. This document is for a physical non-diagnostic device.
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 component in this medical face mask.
7. The type of ground truth used:
- The "ground truth" for this device is based on objective, standardized measurements and laboratory test results against established industry and regulatory standards (e.g., ASTM F1862 for fluid resistance, ASTM F2101 for BFE, ISO 10993 for biocompatibility). There is no "expert consensus" or "pathology" in the sense of clinical diagnoses for this product type.
8. The sample size for the training set:
- This is Not Applicable. There is no "training set" as this is a physical product, not an AI model.
9. How the ground truth for the training set was established:
- This is Not Applicable. See point 8.
In summary, the provided document is a regulatory submission for a physical medical device (face mask). Its "acceptance criteria" and "study proving it meets criteria" are based on performance against established engineering and biocompatibility standards, not on AI/software performance metrics or human reader studies.
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