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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.

It is the powder-free variation of the class I latex patient examination gloves made by on-line polymer-coating and mild on-line chlorination process modifies the surface characteristics and causes it to remain tackfree without the use of any dusting or donning powder.

Based on the provided document, the device in question is Powder Free Nitrile Examination Gloves, Blue (colored). This document is a 510(k) Summary for a medical device which typically focuses on demonstrating substantial equivalence to a legally marketed predicate device rather than presenting a clinical study proving device performance against specific acceptance criteria in the context of an AI-powered diagnostic device.

Therefore, many of the requested elements for an AI device (like human reader improvement with AI assistance, standalone performance, training set details, expert qualifications for ground truth) are not applicable to this type of device and submission.

However, I can extract the acceptance criteria and performance data for the physical and biological characteristics of the gloves as presented in the "Summary of the Technological Characteristic" section.

Here's the breakdown:

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

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

The document does not specify the exact sample sizes used for each test (e.g., how many gloves were tested for length, tensile strength, or water leaks). It simply states that the subject device "Meet[s]" or "Passes" the criteria. The provenance of the data is not explicitly stated beyond being presented in a submission from Careglove Global Sdn Bhd, Malaysia, implying the testing was conducted to support their device. It's standard for these types of tests to be prospective, laboratory-based evaluations.

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

Not applicable. This device is a physical product (examination gloves), not an AI-powered diagnostic tool requiring expert interpretation for "ground truth". The performance criteria are physical and chemical measurements or biological response assessments, not based on expert consensus.

4. Adjudication method for the test set:

Not applicable for the same reasons as #3. Quality control of physical properties does not typically involve expert 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 not an AI device.

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

Not applicable. This is not an AI device. The "standalone performance" is the inherent physical and chemical properties of the glove itself.

7. The type of ground truth used:

The "ground truth" for the physical and chemical properties of the gloves is established by standardized laboratory testing methods (e.g., likely conforming to ASTM standards like D6310, as mentioned in the document). For biocompatibility, the ground truth is established by the biological response observed in appropriate in vivo or in vitro models as per standard biocompatibility testing protocols.

8. The sample size for the training set:

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

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

Not applicable. This is not an AI device.

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A patient examination glove is a disposable device intended for medical purposes that is worn on the examiner's hand to prevent contamination between patient and examiner. These gloves were tested for use with chemotherapy drugs per ASTM D6978-05 (Reapproved 2013) Standard Practice for Assessment of Medical Gloves to Permeation by Chemotherapy Drugs.

Sterile Powder Free Nitrile Examination Gloves, Blue Colored. Tested For Use with Chemotherapy Drugs, with Non-Pyrogenic Labeling Claim

This document is a 510(k) premarket notification from the FDA regarding "Sterile Powder Free Nitrile Examination Gloves, Blue Colored. Tested For Use with Chemotherapy Drugs, with Non-Pyrogenic Labeling Claim."

The document does not describe the acceptance criteria and a study for an AI-powered device. Instead, it outlines the performance of medical gloves against chemotherapy drug permeation. Therefore, most of the requested information regarding AI device studies cannot be extracted.

However, I can provide the acceptance criteria and reported device performance related to chemotherapy drug permeation for the gloves as presented in the document.

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

For the specific context of these gloves and chemotherapy drug permeation, the "acceptance criteria" appear to be implied by the minimum breakthrough detection times. The device's performance is the reported breakthrough time for each drug.

Note: The phrase "minimum breakthrough detection time" in the table heading implies these are the observed times. The standard ASTM D6978-05 would define the methodology and potential performance requirements, but the document itself doesn't explicitly state a pass/fail threshold for these times. However, the subsequent note highlights drugs with "extremely low permeation times of less than 60 minutes," suggesting a 60-minute threshold might be implicitly relevant for practical use considerations.

The document does not provide information for the following points as they are typically relevant for AI/software-as-a-medical-device (SaMD) studies, not for the physical examination gloves described:

2. Sample size used for the test set and the data provenance
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
4. Adjudication method
5. If a multi reader multi case (MRMC) comparative effectiveness study was done
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
8. The sample size for the training set
9. How the ground truth for the training set was established

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