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510(k) Data Aggregation
(38 days)
Powder free vinyl patient examination glove is a disposable device intended for medical purposes that is worn on the examiner's hand or finger to prevent contamination between patient and examiner.
powder free vinyl patient examination gloves, Clear(non-colored) that meets all of the requirements of ASTM standard D 5250-0004
Here's an analysis of the provided text regarding the acceptance criteria and the study that proves the device meets those criteria:
The provided document is a 510(k) Premarket Notification summary for "Powder Free Vinyl Patient Examination Gloves, Clear (non-colored)". It describes the device and its compliance with relevant standards rather than a study for an AI/ML powered device. Therefore, many of the requested fields for AI/ML device studies are not applicable.
Here's the breakdown based on the provided text:
Acceptance Criteria and Device Performance
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Dimension (ASTM D 5250-00e4) | Meets |
| Physical Properties (ASTM D 5250-00e4) | Meets |
| Freedom from pinholes (21 CFR 800.20) | Meets |
| Powder Residual (ASTM D 5250-00e4 and D6124-01) | < 2mg/glove |
| Biocompatibility: Primary Skin Irritation (rabbits) | Passes (Not a Primary Skin Irritation) |
| Biocompatibility: Dermal sensitization (guinea pig) | Passes (Not a Dermal sensitization) |
Study Details (as applicable for a non-AI/ML device)
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Sample size used for the test set and the data provenance:
- Sample Size: Not explicitly stated for each test. For "Powder Residual", a quantity is measured per glove, implying testing on multiple gloves, but the sample size isn't given. For "Freedom from pinholes", it refers to 21 CFR 800.20, which likely specifies an AQL (Acceptable Quality Limit) sampling plan, but the specific sample size used is not provided. For biocompatibility, animal models were used (rabbits for skin irritation, guinea pigs for sensitization), but the number of animals is not specified.
- Data Provenance: Not explicitly stated, but the tests performed are standard industrial tests for medical devices. The manufacturer is WUXI SHENZHOU PLASTIC PRODUCTS CO.,LTD in P.R.CHINA.
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Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- Not applicable. These are physical and biological material property tests based on standardized methods, not expert interpretation of data.
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Adjudication method (e.g. 2+1, 3+1, none) for the test set:
- Not applicable. Results are quantitative measurements or direct observations against a standard (e.g., "Passes," "Meets," or a specific numerical threshold like "<2mg/glove").
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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/ML device.
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If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
- Not applicable. This is not an AI/ML device.
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The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
- Ground Truth: For physical properties (Dimension, Physical Properties, Freedom from pinholes, Powder Residual), the "ground truth" is defined by the technical specifications and thresholds set in the referenced ASTM standards (D5250-00e4, D6124-01) and regulatory requirements (21 CFR 800.20).
- For Biocompatibility, the "ground truth" is based on the biological response observed in animal models (rabbits for primary skin irritation, guinea pigs for dermal sensitization) according to the test protocols, confirming the absence of significant irritation or sensitization. The reference ISO10993-10 also points to standardized biological evaluation methods.
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The sample size for the training set:
- Not applicable. This is not an AI/ML device, and thus there is no training set in the context of machine learning. The device is manufactured and tested according to established quality control procedures.
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How the ground truth for the training set was established:
- Not applicable. As this is not an AI/ML device, there is no "training set ground truth." The ground truth for device performance is based on adherence to pre-defined industry standards and regulatory requirements.
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