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A patient examination glove is a disposable device intended for medical purposes that is worn upon the examiner's hands to prevent contamination between patient and examiner.

The subject device is powder free vinyl examination gloves, adding 1%-3% nitrile to improve the tensile strength and ultimate elongation. The subject device is blue color. lt can be available in four specifications: S,M,L and XL. The subject device is non-sterile.

This document is a 510(k) Premarket Notification for NBR Synthetic Examination Gloves, indicating that it is a Class I medical device (non-powdered patient examination glove). The purpose of the submission is to demonstrate substantial equivalence to a legally marketed predicate device, rather than to prove de novo a device's safety and effectiveness through extensive clinical trials for new technologies.

As such, the "acceptance criteria" and "study that proves the device meets the acceptance criteria" in this context refer to the non-clinical performance testing and biocompatibility assessments performed to demonstrate that the new device meets established standards for patient examination gloves and is substantially equivalent to a predicate device. There is no AI or diagnostic component to this device, so many of the common questions related to AI/ML device studies (e.g., ground truth, MRMC studies, training sizes) are not applicable.

Here's an analysis based on the provided document:

Acceptance Criteria and Reported Device Performance

The acceptance criteria are derived from recognized standards for medical gloves (e.g., ASTM, ISO). The reported device performance indicates compliance with these standards.

Table of Acceptance Criteria and Reported Device Performance:

Study Information (as requested, with noted applicability)

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

   • Test Set Sample Size: For the watertightness test (ASTM D5151), a sample size of 125 gloves was tested (0/125 indicates no holes found). Other physical and chemical tests would have their own sample sizes as per the respective ASTM/ISO standards, which are not explicitly detailed but are inherent to the "Pass" results.
   • Data Provenance: The document does not specify the country of origin for the non-clinical testing data, but the submitter is based in China. The testing would be retrospective, as it involves laboratory tests on manufactured samples.

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

   • This question is not applicable as the device is a patient examination glove and the evaluation relies on direct physical/chemical testing against established industry standards (ASTM, ISO), not on expert subjective interpretation or "ground truth" derived from human experts in a clinical context.

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

   • Not applicable. This relates to clinical or reading studies where multiple readers interpret data. The tests performed are objective, laboratory-based measurements.

4. 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 device is a physical glove, not an AI-powered diagnostic or assistive tool.

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

   • Not applicable. This does not relate to an algorithm.

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

   • The "ground truth" for this device's performance is defined by the objective, quantitative specifications and performance requirements outlined in the referenced international (ISO) and national (ASTM) standards for patient examination gloves. For example, "watertightness" is determined by a specific test procedure in ASTM D5151, not by expert consensus or pathology.

7. The sample size for the training set:

   • Not applicable. This device does not involve machine learning or AI, and therefore no "training set" in that sense. The training/development of the manufacturing process would be internal to the company, but not part of a regulatory "training set" evaluation.

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

   • Not applicable. As above, there is no AI/ML training set.

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