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This glove is intended to be worn by operating room personnel to protect a surgical wound from contamination. In addition, these gloves were tested for use with chemotherapy drugs in accordance with ASTM D6978-05(Reapproved 2019).

Sterile Polyisoprene Powder Free Surgical Glove, tested for Use with Chemotherapy Drugs is a disposable singleuse, sterile, Cream-colored and powder-free surgical glove made from synthetic polyisoprene latex.

This document describes the premarket notification (510(k)) for a medical device – "Sterile Polyisoprene Powder Free Surgical Glove, Tested for Use with Chemotherapy Drugs." This device is a Class I, reserved product, meaning it's subject to general controls but does not require extensive clinical data for approval if it demonstrates substantial equivalence to a legally marketed predicate device.

The provided text focuses on the device's technical specifications and non-clinical testing to demonstrate substantial equivalence to a predicate device, not on proving an AI algorithm's performance in a diagnostic context. Therefore, many of the requested elements for describing an AI acceptance criteria study (e.g., sample size for test set, data provenance, expert ground truth, MRMC study, effect size, standalone performance, training set details) are not applicable to this submission.

The "acceptance criteria" here refer to the product's physical, chemical, and performance standards as determined by established industry and regulatory test methods, not diagnostic performance metrics of an AI.

Here's an interpretation of the "acceptance criteria" and "study" based on the provided document:

Acceptance Criteria and Reported Device Performance

The device's performance is demonstrated through adherence to various ASTM and ISO standards. The acceptance criteria are the minimum or maximum values specified by these standards, and the reported device performance indicates whether the tested product met these thresholds.

Study Proving Device Meets Acceptance Criteria

The "study" refers to a series of non-clinical tests conducted according to recognized international and industry standards.

1. Sample Size Used for the Test Set and Data Provenance:

   • Sample Size: Not explicitly stated for each specific test, but the standards (e.g., ASTM D3577, ASTM D5151) would dictate the minimum sample sizes required for statistically valid testing (e.g., AQL levels for freedom from holes).
   • Data Provenance: The tests were performed to verify that the subject device meets the acceptance criteria. The location of the testing laboratories is not specified, but the manufacturing company is based in China. The data would be considered prospective as it was generated specifically for this 510(k) submission to demonstrate compliance.

2. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications:

   • Not Applicable. This is a physical product testing scenario, not an AI diagnostic study. "Ground truth" is established by the standardized test methods themselves and the precise measurement of physical properties (e.g., length, thickness, tensile strength) or chemical properties (e.g., breakdown time, residual powder). The "experts" are the technicians and scientists performing these standardized tests in accredited laboratories. Their qualifications would involve training and expertise in material science, chemistry, and quality control relative to medical device testing.

3. Adjudication Method for the Test Set:

   • Not Applicable. As this is not an AI diagnostic study, there is no human "adjudication" in the sense of reconciling expert opinions. The test results are typically quantitative measurements, and compliance is determined by whether these measurements fall within the specified acceptance criteria. Any discrepancies in test results would be handled through laboratory quality control procedures and repeat testing.

4. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done:

   • No. This type of study is relevant for diagnostic AI algorithms where human readers interpret medical images or data. It is not applicable to the testing of surgical gloves.

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

   • Not Applicable. This product is a physical medical device, not an AI algorithm.

6. The Type of Ground Truth Used:

   • Standardized Test Results and Established Benchmarks: The "ground truth" for the performance claims are the outcomes of tests conducted in accordance with well-established ASTM and ISO standards (e.g., ASTM D3577-19 for physical properties, ASTM D6978-05 for chemotherapy drug permeation, ISO 10993 series for biocompatibility). These standards define the methodologies and the "correct" or "acceptable" results for the device's characteristics.

7. The Sample Size for the Training Set:

   • Not Applicable. There is no "training set" in the context of a physical product's performance validation as described here. This is not an AI/machine learning development.

8. How the Ground Truth for the Training Set Was Established:

   • Not Applicable. (See point 7)

In summary, the provided document details a non-clinical performance evaluation of a medical device against established industry standards and regulatory requirements, not a study of an AI algorithm's diagnostic performance. The "acceptance criteria" are the thresholds defined by these standards, and the "study" is the battery of tests conducted to demonstrate compliance.

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