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Plain and chromic gut surgical sutures USP are indicated for use in general soft tissue approximation and/or ligation, including use in ophthalmic procedures, but not for use in cardiovascular and neurological procedures.

Plain and chromic gut surgical sutures USP manufactured by R.K. Medical, L.L.C. are equivalent to plain and chromic gut surgical sutures manufactured by Davis & Geck. These sutures are absorbable, sterile surgical sutures composed of purified connective tissue (mostly collagen) derived from either the serosal layer of beef (bovine) or the submucosal fibrous layer of sheep (ovine) intestines. The plain and chromic gut sutures are packaged in packing fluid composed of isopropanol, water, and triethanolamine. R.K. Medical plain and chromic gut surgical sutures are sterilized by gamma irradiation.

This document is a 510(k) summary for R.K. Medical's plain and chromic gut absorbable surgical sutures from 1996. It describes the device, its intended use, and claims equivalence to a predicate device.

However, the provided text does not contain the information requested in your prompt regarding acceptance criteria and a study proving device meets the criteria in the context of an AI/ML device.

Here's why and what's missing:

• Device Type: The device described is absorbable surgical sutures, which are a traditional medical device, not an AI/ML powered device.
• Study Type: The "study" mentioned is a comparison of physical properties (suture diameter, length, knot pull tensile strength, needle attachment strength) to USP XXIII specifications and a predicate device (Davis & Geck sutures). This is a standard engineering/materials testing study, not a clinical or AI performance study.
• Missing Information: Consequently, none of the requested fields related to AI/ML device validation (e.g., sample size for test set, data provenance, expert ground truth, adjudication, MRMC studies, standalone performance, training set details) are present or applicable to this document.

Therefore, I cannot fulfill your request to create the table and answer the questions based on the provided text, as the text describes a conventional medical device, not an AI/ML device, and doesn't contain the relevant performance study information you're asking for.

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