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ComPel Surgical Drapes are intended to cover patients or working surfaces during surgical procedures. ComPel Surgical Drapes and Covers are made of synthetic materials intended to be used as protective other of Dargious such as to isolate a site of surgical incision from microbial and other contamination.

ComPel Surgical Drapes will function as a surgical drape when processed according to instructions. Com of Dargical Drapes are reusable through 75 wash, dry and sterilization cycles. They are manufactured and distributed as non-sterile surgical drapes that are intended to be sterilized and processed by health care facilities and/or contract sterilization/laundry companies.

All base fabrics used in the construction of ComPel Surgical Drapes are made from 100% polyester, knitted or woven into fabric and then dyed. WrapPel and ComPel fabrics are fluorocarbon treated, XTR fabric is silicone coated, COMBOsafe fabric is laminated with a urethane film and Zorwik is treated to be hydrophilic. ComPel Surgical Drapes will function as a surgical drape when processed according to instructions through 75 complete wash, dry and sterilization cycles. These products will be manufactured and distributed as non-sterile surgical drapes that are intended to be sterilized and processed by health care facilities and/or contract sterilization/laundry companies.

The provided text describes a 510(k) summary for "ComPel Surgical Drapes and Covers," a non-sterile, reusable surgical drape. The document outlines various performance tests and does not focus on a standalone algorithm or a multi-reader multi-case (MRMC) comparative effectiveness study. Therefore, sections related to AI performance, sample sizes for test and training sets, expert qualifications, and adjudication methods are not applicable to this document.

Here's an analysis of the provided information, focusing on the acceptance criteria and supporting studies where applicable:

1. Table of Acceptance Criteria and Reported Device Performance:

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

• Sample Size for Test Set: The document does not specify the exact sample sizes used for each individual test. It merely states that the tests were "successfully completed."
• Data Provenance: Not explicitly stated, but the tests refer to established international and national standards (e.g., AATCC, ASTM, ISO, CFR) which imply laboratory testing rather than data from human subjects or retrospective studies from specific countries.

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

• This information is not applicable. The device's performance is measured against established scientific and engineering standards and test methods, not against expert consensus on medical images or diagnoses.

4. Adjudication method for the test set:

• This information is not applicable. Adjudication typically refers to resolving discrepancies in expert interpretations in medical studies, which is not relevant for physical and chemical performance testing of a medical device like a surgical drape.

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:

• This information is not applicable. This document describes a physical medical device (surgical drape), not an AI-powered diagnostic or assistive tool.

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

• This information is not applicable. This document describes a physical medical device, not an algorithm.

7. The type of ground truth used:

• The ground truth in this context is defined by the established performance specifications and limits within the referenced national and international standards (e.g., specific hydrostatic pressures for barrier performance, acceptable lint levels, non-toxic classifications, strength thresholds, and functional integrity after a certain number of processing cycles).

8. The sample size for the training set:

• This information is not applicable. There is no machine learning or AI component described that would require a training set.

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

• This information is not applicable. There is no machine learning or AI component described.

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