Surgical gown are devices that are intended to be worn by operating room personnel during surgical procedures to protect both the surgical patient and the operating room personnel from transfer of microorganisms, body fluids, and particulate material.

Device Description

The surgical gown is intended to be worn by operating room personnel during surgical procedures to protect both the surgical patient and the operating room personnel from transfer of microorganisms, body fluids, and particulate material. It is made of soft, air permeable SMS non-woven fabric. The Jianerkang Surgical Gown is made of a laminate with adhesive taped seams and have a hook and loop closure at the back of the neck and a waist tie feature to secure the gown to the body of the user. The sleeves of the gown have knit cuffs sewn onto the end of the sleeve at the user's wrists to keep the sleeves in place on the wearer. The entire gown including the gown sleeves are made of the same material and utilize the same manufacturing processes.

AI/ML Overview

The provided text is a 510(k) summary for a medical device called "Surgical Gown." It details the product, its intended use, and its comparison to a predicate device to demonstrate substantial equivalence for FDA clearance.

However, the questions you've asked are typically relevant to the performance evaluation of AI/ML-enabled medical devices, specifically regarding their accuracy and how they improve human performance. The document describes a traditional medical device (a surgical gown) and focuses on its physical properties, material performance, and biocompatibility, not on AI/ML algorithm performance.

Therefore, I cannot provide answers to your specific questions based on the provided text, as it does not contain information about:

Acceptance criteria for an AI/ML algorithm's performance
Study data for an AI/ML algorithm
Sample sizes for test or training sets for AI/ML
Ground truth establishment by experts for AI/ML
MRMC studies for AI/ML
Standalone AI algorithm performance

The document states that "Performance testing was conducted on the Surgical Gown. All of the tested parameters met the predefined acceptance criteria," and then lists those criteria in a table for properties like water resistance, tearing strength, tensile strength, and seam strength. This is a physical product, not a diagnostic or prognostic AI/ML device.

To answer your request, if this were an AI/ML device, the structure of the answer below demonstrates what would be needed, but the actual values and details cannot be extracted from the provided text.

Assuming the Request Pertains to a Hypothetical AI/ML-enabled Medical Device based on the Questions Provided:

Given the nature of the provided document, which describes a surgical gown (a physical medical device), it does not contain the kind of information requested regarding acceptance criteria and studies for an AI/ML-enabled software device. The acceptance criteria and performance studies described in the document relate to the physical properties and barrier performance of the gown itself, not to an algorithm's diagnostic or analytical capabilities.

Therefore, for the type of device described in the document, none of the following information is applicable or available:

A table of acceptance criteria and reported device performance for an AI/ML algorithm
Sample sizes used for AI/ML test sets or training sets
Data provenance for AI/ML
Number of experts used to establish ground truth for AI/ML
Adjudication method for AI/ML
MRMC comparative effectiveness study results for AI/ML
Standalone AI algorithm performance
Type of ground truth used for AI/ML (e.g., expert consensus, pathology, outcomes data)
How ground truth for AI/ML training was established

However, if we were to reinterpret your request as an example of what such a description would entail for an AI/ML device, even though not present in this document, here's a hypothetical structure that addresses your points:

Hypothetical Description for an AI/ML Medical Device (Not Applicable to the Provided Document)

This section describes the hypothetical acceptance criteria and the study conducted to prove the AI-enabled device meets these criteria, as if the "Surgical Gown" were an AI/ML diagnostic tool.

1. Table of Acceptance Criteria and Reported Device Performance (Hypothetical AI/ML Device)

Metric	Acceptance Criteria	Reported Device Performance
Primary Endpoints:
Sensitivity (for Condition X)	≥ 90% (lower 95% CI > 85%)	92.5% (95% CI: 90.1% - 94.4%)
Specificity (for Condition X)	≥ 80% (lower 95% CI > 75%)	83.2% (95% CI: 80.5% - 85.7%)
Secondary Endpoints:
Area Under ROC Curve (AUC)	≥ 0.90	0.93
Positive Predictive Value (PPV)	≥ 75%	78.1%
Negative Predictive Value (NPV)	≥ 95%	96.3%
Human Reader Performance Gain (MRMC)	Mean sensitivity improvement ≥ 5% with AI assistance	Mean sensitivity improvement of 7.2%
Time-to-diagnosis	Reduction of 20%	25% reduction in mean diagnostic reading time

2. Sample Sizes and Data Provenance (Hypothetical AI/ML Device)

Test Set Sample Size: N = 1,000 cases (e.g., medical images, patient records).
Data Provenance: Retrospective and prospective data collected from multiple sites across the United States, Europe (e.g., Germany, UK), and Asia (e.g., Japan, South Korea). Data was collected over a period of 5 years (2018-2023).

3. Number of Experts and Qualifications for Ground Truth (Hypothetical AI/ML Device)

Number of Experts: A panel of 5 board-certified medical specialists (e.g., Radiologists, Pathologists) with varying levels of experience.
Qualifications:
- 3 Senior Experts: Each with >10 years of experience in the relevant subspecialty (e.g., thoracic radiology, dermatopathology).
- 2 Junior Experts: Each with 3-5 years of experience in the relevant subspecialty.
- All experts were blinded to the device's output during ground truth establishment.

4. Adjudication Method for the Test Set (Hypothetical AI/ML Device)

Method: A "3+1" consensus method was used.
- Each case was independently reviewed by three out of the five experts.
- If at least two out of the three experts agreed on a label, that was considered the preliminary ground truth.
- In cases of disagreement (i.e., no two out of three experts agreed, or a 1-1-1 split), a fourth senior expert (the "plus 1") was brought in to review the case and resolve the discrepancy, establishing the final ground truth.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study (Hypothetical AI/ML Device)

Was an MRMC study done? Yes.
Effect Size of Human Reader Improvement: The MRMC study demonstrated a statistically significant improvement in human reader performance when assisted by the AI device.
- Effect Size: Human readers improved their mean sensitivity by 7.2% (absolute change) and mean specificity by 4.5% (absolute change) when using the AI assistance compared to reading without AI assistance.
- This translated to a statistically significant increase in AUC for human readers with AI assistance (e.g., AUC increased from 0.85 to 0.91, p < 0.001).

6. Standalone Performance (i.e., algorithm only without human-in-the-loop) (Hypothetical AI/ML Device)

Was standalone performance done? Yes.
Performance: The standalone algorithm achieved a sensitivity of 92.5%, specificity of 83.2%, and an AUC of 0.93 on the independent test set. These metrics met the predefined acceptance criteria for standalone performance.

7. Type of Ground Truth Used (Hypothetical AI/ML Device)

Type: Expert consensus (as detailed in point 3 and 4) was the primary method for establishing ground truth.
For certain conditions, (e.g., malignancy), confirmation was sought from pathology reports or long-term clinical outcomes data where available, serving as the gold standard or confirmatory reference. All ground truth labels were meticulously documented and linked to the source.

8. Sample Size for the Training Set (Hypothetical AI/ML Device)

Sample Size: N = 10,000 cases (e.g., medical images). This large dataset allowed for robust model training and generalization.

9. How Ground Truth for the Training Set Was Established (Hypothetical AI/ML Device)

Ground truth for the training set was established through a combination of methods:
- Automated Labeling: For a large portion of the data, ground truth was derived from structured clinical reports, electronic health records (EHR), and existing pathology results. Natural Language Processing (NLP) models were used to extract relevant information and assign preliminary labels.
- Expert Review (Subset): A statistically significant subset (e.g., 20%) of the automatically labeled training data, particularly complex or uncertain cases, underwent manual review by experienced clinicians (e.g., 2 specialists per case) to validate and correct labels. Discrepancies were resolved through a consensus meeting.
- Active Learning: An active learning strategy was employed to prioritize cases for expert review that the model found most challenging or ambiguous, ensuring that expert annotation effort was focused on maximizing model learning.

Summary

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July 7, 2021

Jiangsu Province Jianerkang Medical Dressing Co., Ltd Tang Hongfang Quality System Director No.1 Jianerkang Road, Zhixi Industry Concentration Area, Zhixi Town Changzhou, Jiangsu 213251 China

Re: K210215

Trade/Device Name: Surgical Gowns Regulation Number: 21 CFR 878.4040 Regulation Name: Surgical Apparel Regulatory Class: Class II Product Code: FYA Dated: June 20, 2021 Received: June 24, 2021

Dear Tang Hongfang:

We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database located at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.

If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.

Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal

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statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting of medical device-related adverse events) (21 CFR 803) for devices or postmarketing safety reporting (21 CFR 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reporting-

combination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.

Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.

For comprehensive regulatory information about medical devices and radiation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medicaldevices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-device-advice-comprehensive-regulatoryassistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).

Sincerely,

Ryan Ortega, PhD Acting Assistant Director DHT4B: Division of Infection Control and Plastic Surgery Devices OHT4: Office of Surgical and Infection Control Devices Office of Product Evaluation and Quality Center for Devices and Radiological Health

Enclosure

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Indications for Use

510(k) Number (if known) K210215

Device Name Surgical Gown

Indications for Use (Describe)

Prescription Use (Part 21 CFR 801 Subpart D)

X Over-The-Counter Use (21 CFR 801 Subpart C)

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Image /page/3/Picture/0 description: The image shows a logo with two distinct elements. The first element is a green leaf-like shape, and the second is a blue, curved shape resembling a wave or a stylized letter 'C'. Below these shapes, the word "JIANERKANG" is written in capital letters. The logo appears to be designed to convey a sense of nature and fluidity.

510(k) Summary

K210215

In accordance with 21 CFR 807.92 the following summary of information is provided:

1. SUBMITTER

Jiangsu Province Jianerkang Medical Dressing Co., Ltd No.1 Jianerkang Road, Zhixi Industry Concentration Area, Zhixi Town,213251 Jintan Changzhou City, PEOPLE'S REPUBLIC OF CHINA Phone: +86-519-82444628 Fax: +86-519-82444750 Primary Contact Person: Hongfang Tang

Quality System Director

Jiangsu Province Jianerkang Medical Dressing Co., Ltd Tel: (+86)-519-8244 4628 Fax: (+86) -519-8244 4745

June 20 , 2021 Date prepared:

DEVICE

Device Name:	Surgical Gown
Common name:	Gown, Surgical
Classification Names:	Surgical apparel
Model:
Regulation number	21 CFR 878.4040
Regulation Class:	2
Product Code:	FYA

1. PREDICATE DEVICE
  K141467, Surgical gown XuChang ZhengDe Environstar Medical Products Co., Ltd This predicate has not been subject to a design-related recall.

DEVICE DESCRIPTION 4.

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Image /page/4/Picture/0 description: The image shows a logo with a green leaf-like shape on the top left and a blue wave-like shape on the bottom right. The green and blue shapes are intertwined, creating a sense of harmony and balance. Below the shapes, the word "JIANERKANG" is written in blue, indicating the name of the organization or brand associated with the logo. The logo appears to be designed to convey a message of nature, health, or environmental consciousness.

The device description of the Jianerkang Surgical Gowns is in accordance with the Guidance on Premarket Notification [510(k)] Submissions for Surgical Gowns and Surgical Drapes, issued on August 1, 1993 and Guidance for Industry and FDA Staff: Premarket Notification Requirements Concerning Gowns Intended for Use in Healthcare Settings, issued on December 9, 2015.

The Jianerkang Surgical Gown is made of a laminate with adhesive taped seams and have a hook and loop closure at the back of the neck and a waist tie feature to secure the gown to the body of the user. The sleeves of the gown have knit cuffs sewn onto the end of the sleeve at the user's wrists to keep the sleeves in place on the wearer. The entire gown including the gown sleeves are made of the same material and utilize the same manufacturing processes.

5.

ம் INDICATIONS FOR USE

Specification	Predicate Device	Proposed	Conclusion
K number	K141467	K210215	-
Manufacturer	XuChang ZhengDe Environstar MedicalProducts Co., Ltd	Jiangsu Province Jianerkang MedicalDressing Co., Ltd	-
Indication forUse	Surgical gown are devices that areintended to be worn by operating roompersonnel during surgical procedures toprotect both the surgical patient and theoperating room personnel from transferof microorganisms, body fluids, andparticulate material.	Surgical gown are devices that areintended to be worn by operating roompersonnel during surgical procedures toprotect both the surgical patient and theoperating room personnel from transferof microorganisms, body fluids, andparticulate material.	same
Material	SMS	SMS	same
Weight persquare (g)	45	45	same
Durability	Disposable	Disposable	same
Size	M-S, M, L, XL, XXL	M-S, M, L, XL, XXL	same
Color	Blue	Blue	same
Style	Reinforced and non reinforced	non reinforced	similar
Specification	Predicate Device	Proposed	Conclusion
Hydrostaticpressure:AATCC 127	>50 cm	>50 cm	same
Impactpenetration:AATCC 42	<1	<1	same
Biocompatibility	under the conditions of the study, notan irritant; (ISO 10993-10:2010)	under the conditions of the study, notan irritant; (ISO 10993-10:2010)	same
	under conditions of the study, not asensitizer; (ISO 10993-10:2010)	under conditions of the study, not asensitizer; (ISO 10993-10:2010)	same
	Under the conditions of the study thedevice is non-cytotoxic. (ISO 10993-5:2009)	Under the conditions of the study thedevice is non-cytotoxic. (ISO 10993-5:2009)	same
Tensilestrength:ASTM D 5034	Length(Ibf): 17.7Width(Ibf): 25.7	Length(Ibf): 17.1Width(Ibf): 26.8	Similar
Tearingstrength:ASTM D 5733	Length yarns torn(lbf): 4.7Width yarns torn(lbf): 9.8	Length yarns torn(lbf): 3.0Width yarns torn(lbf): 5.1	Similar-, thedifference doesnot impact theproduct's safetyand performance
Seamstrength:ASTM D 1683	Armhole seam (Ibf) 17.6(F.B.)Shoulder seam (Ibf) 9.5(F.B.)	Armhole seam (Ibf) 19.4(F.B.)Shoulder seam (Ibf) 13.4(F.B.)	Similar
Flammability:16 CFR Part1610	Class 1	Class 1	same
Sterilizationmethod	EO	EO	same
Resistance toblood andliguidpenetration	Level 3 per AAMI PB70	Level 3 per AAMI PB70	same

6. COMPARISON OF TECHNOLOGICAL CHARACTERISTICS WITH THE PREDICATE DEVICE

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Image /page/5/Picture/0 description: The image shows a logo with a green leaf-like shape on the left and a blue wave-like shape on the right. The green shape is larger and partially overlaps the blue shape. Below the shapes, the text "JIANERKANG" is written in a sans-serif font. The logo appears to represent a combination of nature and water, possibly suggesting a focus on health or environmental sustainability.

7. Summary of non-clinical performance tests

The following performance data were provided in support of the substantial

equivalence determination.

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Image /page/6/Picture/0 description: The image shows a logo with two distinct elements. On the left, there is a green leaf-like shape, and on the right, there is a blue wave-like shape. Below these elements, the text "JIANERKANG" is written in a simple, sans-serif font.

Biocompatibility testing

The biocompatibility evaluation for the Surgical Gown was conducted in accordance with the International Standard ISO 10993-1:2018, "Biological evaluation of medical devices -Part 1: Evaluation and testing within a risk management process" as recognized by FDA. The biocompatible testing included the following tests:

Cytotoxicity - (ISO 10993-5: 2009)
Sensitization - (ISO 10993-10:2010)
Skin Irritation - (ISO 10993-10:2010)

Performance testing

Performance testing was conducted on the Surgical Gown. All of the tested parameters met the predefined acceptance criteria.

Standards	Purpose	Acceptance Criteria	Results
AATCC 42	Spray Impact	Water Resistance	PASS
AATCC 127	Hydrostatic Pressure	Water Resistance	PASS
ANSI/AAMI PB70:2012AAMI Level 3	Liquid Barrier Performance	Water Resistance	PASS
ASTM D 5733	Standard Test Method for TearingStrength of Nonwoven Fabrics by theTrapezoid Procedure	Tearing Strength	PASS
ASTM D5034 –2017	Grab Tensile, Peak Stretch, and PeakEnergy - Nonwovens	Tensile Strength	PASS
ASTM 1683-17 (2018)	Standard Test Method for Failure inSewn Seams of Woven Apparel Fabrics	Seam Strength	PASS

8. CONCLUSION

The conclusion drawn from the nonclinical tests demonstrates that the subject device in 510(K) submission K210215, Jiangsu Province Jianerkang Medical Dressing Co., Ltd Surgical Gown is as safe, as effective, and performs as well as or better than the legally marketed predicate device cleared under K141467.

Regulation Number and Section

§ 878.4040 Surgical apparel.

(a)
Identification. Surgical apparel are devices that are intended to be worn by operating room personnel during surgical procedures to protect both the surgical patient and the operating room personnel from transfer of microorganisms, body fluids, and particulate material. Examples include surgical caps, hoods, masks, gowns, operating room shoes and shoe covers, and isolation masks and gowns. Surgical suits and dresses, commonly known as scrub suits, are excluded.(b)
Classification. (1) Class II (special controls) for surgical gowns and surgical masks. A surgical N95 respirator or N95 filtering facepiece respirator is not exempt if it is intended to prevent specific diseases or infections, or it is labeled or otherwise represented as filtering surgical smoke or plumes, filtering specific amounts of viruses or bacteria, reducing the amount of and/or killing viruses, bacteria, or fungi, or affecting allergenicity, or it contains coating technologies unrelated to filtration (e.g., to reduce and or kill microorganisms). Surgical N95 respirators and N95 filtering facepiece respirators are exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to § 878.9, and the following conditions for exemption:(i) The user contacting components of the device must be demonstrated to be biocompatible.
(ii) Analysis and nonclinical testing must:
(A) Characterize flammability and be demonstrated to be appropriate for the intended environment of use; and
(B) Demonstrate the ability of the device to resist penetration by fluids, such as blood and body fluids, at a velocity consistent with the intended use of the device.
(iii) NIOSH approved under its regulation.
(2) Class I (general controls) for surgical apparel other than surgical gowns and surgical masks. The class I device is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to § 878.9.