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Their intended use is to prevent an interchange of body fluids via the hands of the wearer and the person (patient) being examined. Specifically, they are designed to prevent blood or other body fluids from the hands of the wearer from being transferred to the examinee. Also they are designed to prevent body fluids from the examinee from being transferred to the wearer via the wearer's hands.

Oak Carolina examination gloves are made from poly vinyl chloride (vinyl). They are to be marketed under the trade name Sensi-tex.

The provided text describes a medical device, specifically Oak Carolina Examination Gloves, and outlines its specifications and some testing results. However, it does not describe an AI/ML powered device or a study involving such a device, and therefore the specific questions you've asked about acceptance criteria and a study proving an AI device meets them are largely not applicable.

The document focuses on the physical properties and basic performance of examination gloves as per FDA requirements in 1996 for a 510(k) submission.

Here's an attempt to answer your questions based on the provided text, flagging where the information is not present or not applicable to an AI device:

1. A table of acceptance criteria and the reported device performance

Regarding AI-specific acceptance criteria (Sensitivity, Specificity, AUC, etc.): Not applicable. This document is for a medical glove, not an AI device.

2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective)

• Sample Size for Test Set: The document mentions physical requirements tested "before and after accelerated aging" and "when tested in accordance with ASTM D5151-92" and "Biocompatibility studies." However, specific sample sizes for these tests are not provided.
• Data Provenance: The document is dated April 26, 1996, and relates to a submission to the FDA in the USA. The manufacturer is "Oak Carolina Inc. 100 Roe Road Travelers Rest, S.C. 29690" in the USA. The data would therefore be assumed to be from tests performed in the USA by the manufacturer. It is a report on testing, so it can be considered a retrospective summary of completed tests.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

• Not applicable. This pertains to a physical product's performance against pre-defined engineering and safety standards, not an AI model's diagnostic accuracy where expert ground truth is typically used. The "ground truth" here is the pass/fail result of physical and chemical tests against established standards (e.g., ASTM standards).

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

• Not applicable. This concept typically applies to discrepancies in expert annotations for AI model ground truth. The tests described are objective measurements (e.g., width, length, tensile strength, water leak) against a standard, not subjective interpretations requiring adjudication.

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 document describes a physical medical device (examination gloves), not an AI algorithm designed to assist human readers.

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

• Not applicable. This document describes a physical medical device (examination gloves), not an AI algorithm.

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

• The "ground truth" for the glove's performance is based on objective measurements against established industry standards (e.g., ASTM D5250, ASTM D5151-92) and biocompatibility testing. This is not based on expert consensus, pathology, or outcomes data in the context of diagnostic accuracy.

8. The sample size for the training set

• Not applicable. This document describes a physical medical device (examination gloves), not an AI algorithm that undergoes training.

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

• Not applicable. This document describes a physical medical device (examination gloves), not an AI algorithm.

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