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510(k) Data Aggregation
(213 days)
A patient examination glove is a disposable device intended for medical purpose that is worn on the examiner's hand or fingers to prevent contamination between patient and examiner.
Powder Free Polychloroprene Light Weight Examination Gloves-Green, Blue and Pink
This document is a 510(k) premarket notification letter from the FDA regarding "Powder Free Polychloroprene Light Weight Examination Gloves - Green, Blue and Pink." It primarily focuses on the regulatory approval and substantial equivalence to legally marketed predicate devices, not on a study with acceptance criteria for a device's performance in a diagnostic or clinical setting.
Therefore, the provided document does not contain the information requested regarding acceptance criteria and a study to prove a device meets those criteria. Specifically, it lacks:
- A table of acceptance criteria and reported device performance.
- Sample sizes for test sets, data provenance, and expert qualifications for ground truth.
- Adjudication methods.
- Information on MRMC comparative effectiveness studies.
- Information on standalone algorithm performance.
- Details on the type of ground truth used (beyond implying mechanical and material properties typical for examination gloves).
- Sample size for the training set.
- How ground truth for the training set was established.
This document is a regulatory approval letter based on "substantial equivalence" to existing devices, which typically relies on demonstrating that the new device has the same intended use and technological characteristics as a predicate, or if there are differences, that those differences do not raise new questions of safety and effectiveness. The performance criteria for examination gloves would typically involve standards for tensile strength, elongation, barrier integrity (e.g., freedom from holes), and biocompatibility, which are usually tested against established industry or regulatory standards rather than through clinical studies with expert-adjudicated ground truth as might be seen for AI/ML diagnostic devices.
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