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A 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.

Classified by FDA's General and Plastic Surgery Device panel as Class 1, 21 CFR 880.6250, Powder-Free Vinyl Patient Examination Glove, 80LYZ, and meets all requirements of ASTM Standard D5250-00E4.

The provided text describes a 510(k) submission for "Shanghai Antares Industries Inc. Disposable Powder Free Vinyl Synthetic Exam Gloves, With Vitamin Complex, Nopal and Lanolin (Blue Color)". Medical gloves are Class I devices and generally demonstrate substantial equivalence through performance testing against recognized standards.

Here's an analysis of the acceptance criteria and the study that proves the device meets them:

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

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

• Physical and Dimensions Testing: Inspection level S-2, AQL 4.0. The specific sample size is not explicitly stated but is implicitly defined by the ASTM D5250-00E4 standard and the AQL.
• Watertight Integrity: Inspection level I, AQL 2.5. The specific sample size is not explicitly stated but is implicitly defined by the ASTM D-5151-99 standard and the AQL.
• Powder-Free Claim: Not explicitly stated, but the test (ASTM D6124-01) is conducted at "finished inspection".
• Primary Skin Irritation and Skin Sensitization: Sample size for these biocompatibility tests is not explicitly mentioned.

The data provenance is prospective manufacturing testing of the Shanghai Antares Industries Inc. gloves. The country of origin of the data is implicitly China, where the manufacturer (Shanghai Antares Industries Inc.) is located.

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

This type of device (patient examination gloves) does not typically involve human expert interpretation for establishing ground truth in the same way an imaging AI algorithm would. The "ground truth" is established by the objective measurement against the specified ASTM standards and FDA test methods. Therefore, the concept of "number of experts" or their "qualifications" for ground truth establishment is not applicable here.

4. Adjudication method for the test set

Not applicable. The tests are objective measurements against established standards, 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 is a medical device (examination gloves), not an AI algorithm for diagnosis or interpretation that would typically require an MRMC study comparing human performance with and without AI.

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

Not applicable. This is a physical medical device.

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

The ground truth for this device is based on objective performance standards and test methodologies established by ASTM (American Society for Testing and Materials) and FDA. For example:

• Physical properties (dimensions, tensile strength) are objectively measured against limits defined in ASTM D5250-00E4.
• Watertight integrity (pinhole) is objectively measured against the criteria in ASTM D-5151-99.
• Powder content is objectively measured against the limit of 2 mg per glove using ASTM D6124-01.
• Biocompatibility (skin irritation and sensitization) results are based on standardized biological testing protocols.

8. The sample size for the training set

Not applicable. This is a physical medical device, not a machine learning model, so there is no "training set" in the computational sense. The "training" would be analogous to the manufacturing process adhering to quality controls.

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

Not applicable. As explained above, there is no "training set" for a physical device in the context of an AI algorithm. The manufacturing process is designed to produce gloves that inherently meet the established performance standards.

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