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A patient examination glove is a disposable device intended for medical purposes that is worn upon the examiners' hands or fingers to prevent contamination between patients and examiners

Classified by FDA's General and Plastic Surgery Device panel as Class I, 21 CFR 880.6250, Powder-Free Vinyl Patient Examination Gloves, 80 LZA, and meets all requirements of ASTM standard D-6139 and ASTM D-5250.

The provided text describes the 510(k) submission for Anhui Intco Medical Products Co. Ltd.'s Powder-Free Vinyl Patient Examination Gloves, Yellow Color (K191092). This submission focuses on demonstrating substantial equivalence to a predicate device, rather than proving the performance of an AI-powered medical device through a clinical study.

Therefore, most of the requested information regarding AI device acceptance criteria and study details (such as MRMC studies, standalone algorithm performance, AI training/test set ground truth, and expert qualifications for ground truth establishment) is not applicable to this document.

However, I can extract information related to the performance characteristics that were tested for these medical gloves to demonstrate substantial equivalence.

Here's the information that is applicable based on the provided document:

1. Table of acceptance criteria and the reported device performance:

The document compares the subject device (K191092) to a predicate device (K022091) across various physical and biocompatibility characteristics. The "acceptance criteria" here are essentially the performance levels of the predicate device or established standards (like ASTM).

2. Sample size used for the test set and the data provenance:

• Pinhole Test: The sample size mentioned is "125 pieces gloves" for each test (subject and predicate).
• Residual Powder: Not explicitly stated, but implies a sampling based on ASTM D6124-06.
• Physical and Dimensions Testing: "Inspection level S-2, AQL 2.5."
• 1000 ml Water Fill Test: "samplings of AQL 2.5 inspection level G-1."
• Data Provenance: The testing was conducted by Anhui Intco Medical Products Co. Ltd. (China) or their contracted labs. The data is retrospective, as it's part of a 510(k) submission showing compliance with standards.

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):

Not applicable. This is not a study involving human experts establishing ground truth for image interpretation or diagnosis. It involves standardized laboratory testing of physical and chemical properties of a medical device (gloves).

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

Not applicable. Adjudication methods are relevant for subjective assessments, typically in clinical readings or evaluations. The tests performed on the gloves are objective, standards-based measurements.

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:

Not applicable. This is not an AI-powered device.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

Not applicable. This is not an AI-powered device.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc):

The "ground truth" here is defined by the established ASTM (American Society for Testing and Materials) standards for patient examination gloves and the reported performance of the legally marketed predicate device. For example, for pinholes, the ground truth is "AQL 2.5 is met," meaning a certain acceptable quality level for defects based on statistical sampling. For biocompatibility, the ground truth is "not an irritant/sensitizer/cytotoxic" based on specific ISO or other standard test methods applied to animal models or cell cultures.

8. The sample size for the training set:

Not applicable. This is not an AI-powered device that requires a training set.

9. How the ground truth for the training set was established:

Not applicable. This is not an AI-powered device that requires a training set.

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