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A powder-free patient examination glove is a disposable device made of natural rubber latex material that may bear a trace amount of glove powder and is intended to be worn on the hand or finger(s) for medical purposes to provide a barrier against potentially infectious materials and other contaminants.

A non-sterile, disposable, patient examination glove made of natural rubber latex, powder-free, with or without polymer coating.

The provided document describes the 510(k) summary for the Palm-Pro and Palm-Pro Premium Powder-Free Latex Examination Gloves. These gloves are Class I devices and their acceptance criteria and performance are outlined in relation to established ASTM standards and FDA regulations.

Here's a breakdown of the requested information based on the document:

1. Table of Acceptance Criteria and Reported Device Performance

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

The document does not specify the exact sample sizes used for each of the non-clinical tests (Dimensions, Physical Properties, Freedom from pinholes, Powder-Free, Protein level, Biocompatibility).

Regarding data provenance, the document states: "The performance test data of the non-clinical tests that support a determination of substantial equivalence is the same as mentioned immediately above." This implies that the tests were conducted by the manufacturer, Dipped Products (Thailand) Limited (located in Sri Lanka and Thailand), to demonstrate compliance with the specified ASTM standards and FDA regulations. The nature of these tests (e.g., in-house testing) generally leans towards prospective data collection for product qualification.

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

This section is not applicable as the device is a Class I medical device (patient examination gloves). The evaluation relies on meeting established engineering and material science standards (ASTM) and regulatory requirements (FDA 21 CFR 800.20), rather than expert interpretation of medical images or diagnostic data. Therefore, there's no "ground truth" derived from medical experts in the context of diagnostic performance.

4. Adjudication method for the test set

This section is not applicable for the same reasons as point 3. Adjudication methods are typically used in studies involving expert interpretation of data where discrepancies need to be resolved. For device performance against engineering standards, the results are typically quantitative measurements against defined thresholds.

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

This section is not applicable. The device is a physical product (gloves) and does not involve AI or human readers for diagnostic interpretation. Therefore, an MRMC study is not relevant.

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

This section is not applicable. The device is a physical product and does not involve an algorithm.

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

The "ground truth" for this device is the defined specifications and thresholds within the ASTM standards and FDA regulations. For example:

• Dimensions: Measured values compared against the ranges specified in ASTM D 3578-01a.
• Physical Properties: Tensile strength, elongation, etc., measured and compared against ASTM D 3578-01a.
• Freedom from pinholes: Testing according to ASTM D-3578-01a and FDA 21 CFR 800.20.
• Powder-Free level: Gravimetric measurement of powder content compared against the < 2mg/glove threshold according to ASTM D 6124-01.
• Protein level: Measured protein content according to ASTM D-5172-95 compared against the < 50μg/g threshold.
• Biocompatibility: Results of standardized primary skin irritation and dermal sensitization tests.

8. The sample size for the training set

This section is not applicable. This is a physical product and does not involve a "training set" in the context of machine learning or AI.

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

This section is not applicable for the same reasons as point 8.

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