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The Medical Surgical Gowns is intended to be worn by operating room personnel during surgical procedure to protect both the surgical patient and the operating room personnel from transfer of microorganisms, body fluids, and particulate material.

Per ANSI/AAMI PB70:2012 Liquid barrier performance and classification of protective apparel and drapes intended for use in health care facilities, the Medical Surgical Gowns met the requirements for Level 3 classification.

The proposed device is a poly-reinforced surgical gown, the critical zone is front chest and sleeves. The critical zone is reinforced with PP/PE composite laminated material and the reinforced layer is attached with the gown by ultrasonic welding. The proposed device is available in five different sizes, include S-160, M-165, L-70, XL-175, XXL-180, and XXXL-185. Per ANSI/AAMI PB70:2012 Liquid barrier performance and classification of protective apparel and drapes intended for use in health care facilities, the proposed devices can meet the requirements for Level 3 classification. The proposed devices are disposable medical devices and provided in sterile.

This document is a 510(k) Pre-market Notification for a medical device, specifically Medical Surgical Gowns. The information provided does not describe an AI medical device or a study involving human readers.

Therefore, most of the requested points are not applicable. I can only extract information related to the performance of the Medical Surgical Gowns based on the provided text.

Here's a summary of the information that is available:

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

The acceptance criteria are generally based on the ANSI/AAMI PB70:2012 Level 3 classification for liquid barrier performance, along with specific physical and biological properties.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

The document does not specify the sample sizes used for the non-clinical tests. Non-clinical tests were conducted to verify design specifications and similarity to the predicate device. The provenance of the data is not explicitly stated beyond the manufacturer being in Beijing, China.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

Not applicable. This is for a physical medical device (surgical gown), not an AI diagnostic tool. "Ground truth" in this context would refer to the validated results of the physical and biological tests, not expert consensus on medical images.

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

Not applicable. This is for a physical medical device.

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 for a physical medical device, not an AI system.

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

Not applicable. This is for a physical medical device.

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

The "ground truth" for the device's performance is established through adherence to recognized international and national standards for physical properties, barrier performance, and biocompatibility, such as ANSI/AAMI PB70:2012, ASTM standards, ISO standards, and CFR regulations. These standards define the acceptable limits for the device's characteristics.

8. The sample size for the training set

Not applicable. This is for a physical medical device, not an AI system that requires a training set.

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

Not applicable.

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