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510(k) Data Aggregation
(44 days)
This glove Is disposable and is intended for medioal purposes that is worn on the examiner's hand to prevent contamination between patient and examiner.
Smart Glove Latex Patternt Examination Gloves Powderfree, 50 mogm or less water extractable protein.
Here's a breakdown of the requested information, based on the provided document:
Observation: The provided document is a 510(k) clearance letter for an examination glove, not a document describing a medical device that utilizes an algorithm or AI. Therefore, most of the requested information regarding acceptance criteria, study data, expert involvement, and AI performance metrics is not applicable.
However, I can extract information related to the device and its intended use, which are analogous to reporting some "acceptance criteria" through regulatory compliance.
1. Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criteria (Regulatory Compliance) | Reported Device Performance |
|---|---|
| Device Type: Examination Glove | Smart Glove Latex Patternt Examination Gloves Powderfree |
| Protein Content Labeling Claim: | 50 µg/gm or less water extractable protein |
| Intended Use: | Disposable; for medical purposes; worn on examiner's hand to prevent contamination between patient and examiner. |
| Regulatory Class: I | Met regulatory class I requirements |
| Compliance with GMP regulation (21 CFR Part 820): | Assumed; compliance verified through periodic GMP inspections. |
| Substantial Equivalence: | Determined by FDA to be substantially equivalent to devices marketed prior to May 28, 1976. |
The following sections are Not Applicable (N/A) to this document, as it pertains to a medical device (examination glove) without an algorithmic or AI component.
2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
- N/A. This information is not relevant for the regulatory clearance of a physical examination glove. Studies for such devices typically involve mechanical properties, biocompatibility, and chemical analyses, not performance against a test set of data.
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)
- N/A. Ground truth establishment by experts is not applicable for this type of device.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
- N/A. Adjudication is not applicable as there is no test set in the context of an algorithm's output.
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. This device does not involve human readers or AI assistance.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- N/A. This device is not an algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
- N/A. Ground truth, in the context of AI or diagnostic performance, is not applicable here. The "truth" for this device would be its physical and chemical properties and its ability to meet its intended use.
T8. The sample size for the training set
- N/A. Training sets are for machine learning models, which are not involved here.
9. How the ground truth for the training set was established
- N/A. There is no training set or AI model for which to establish ground truth. Data for glove testing would typically come from lab-based material characterization and sterility testing, if applicable.
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