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510(k) Data Aggregation
(319 days)
PGA RESORBA, PGA RESOQUICK, GLYCOLON
GLYCOLON® is indicated for use in general soft tissue approximation and/or ligation, but not for use in cardiovascular or neurological tissues, microsurgery or ophthalmic surgery.
PGA RESORBA® is indicated for use in general soft tissue approximation and/or ligation, including use in ophthalmic surgery, but not in cardiovascular surgery or neural tissue.
PGA resoquick™ is indicated for use in general soft tissue approximation, including ophthalmic (e.g. conjunctiva) procedures, but not in cardiovascular or neurological procedures.
The subject devices are synthetic absorbable surgical sutures.
PGA Resorba: Primary material Polyglycolic acid (PGA), Material presentation Multifilament, braided, Dyed or undyed Undyed and dyed D&C violet No.2, Coated or uncoated Coated Polycaprolactone + calcium stearate, Suture material is a sterile, flexible, thread offered in a variety of lengths, reels, range of diameters, with or without needles attached.
PGA resoquick: Primary material Polyglycolic acid (PGA), Material presentation Multifilament, braided, Dyed or undyed Undyed, Coated or uncoated Coated Polycaprolactone + calcium stearate, Suture material is a sterile, flexible, thread offered in a variety of lengths, reels, range of diameters, with or without needles attached.
Glycolon: Primary material Copolymer glycolide and E-caprolactone (PGA/CL), Material presentation Monofilament, Dyed or undyed Undyed and dyed D&C violet No.2, Coated or uncoated Uncoated, Suture material is a sterile, flexible, thread offered in a variety of lengths, reels, range of diameters, with or without needles attached.
This document is a 510(k) premarket notification for surgical sutures, not an AI/ML device. Therefore, the requested information (acceptance criteria, study details, sample sizes, ground truth establishment, expert qualifications, adjudication methods, MRMC studies, standalone performance, and training set details) related to an AI/ML study is not applicable and cannot be extracted from the provided text.
The document discusses the substantial equivalence of three absorbable surgical sutures (PGA RESORBA, PGA RESOQUICK, GLYCOLON) to legally marketed predicate devices, focusing on their material, design, and performance characteristics in comparison to USP requirements.
Here's the relevant information that can be extracted, formatted as a table for "acceptance criteria" and "reported device performance," which in this context refers to meeting USP standards for surgical sutures.
1. Table of Acceptance Criteria and Reported Device Performance
Acceptance Criteria (USP Requirements for Synthetic Absorbable Sutures) | Reported Device Performance | Comments |
---|---|---|
Diameter | Meets USP requirements | (PGA RESORBA, PGA RESOQUICK). GLYCOLON® has minor variations in diameter from USP, but considered substantially equivalent. |
Tensile strength | Meets USP requirements | (PGA RESORBA, PGA RESOQUICK, GLYCOLON®) |
Needle attachment | Meets USP requirements | (PGA RESORBA, PGA RESOQUICK, GLYCOLON®) |
Resorption profiles (in-vitro and in-vivo) | Evaluated and provided | Resorption data in-vitro and in-vivo for PGA RESORBA, GLYCOLON. In-vivo only for PGA RESOQUICK. Not explicitly stated as "meets USP," but implies satisfactory evaluation. |
Biocompatibility (ISO 10993-1) | Supported by leveraging data from suppliers | Materials have established history of use for the same intended use. |
The following information is not applicable as the document is a 510(k) submission for surgical sutures and does not describe an AI/ML device or its associated studies:
- Sample sizes used for the test set and the data provenance.
- Number of experts used to establish the ground truth for the test set and their qualifications.
- Adjudication method for the test set.
- If a multi-reader multi-case (MRMC) comparative effectiveness study was done, or its effect size.
- If a standalone (algorithm only) performance study was done.
- The type of ground truth used (expert consensus, pathology, outcomes data, etc.).
- The sample size for the training set.
- How the ground truth for the training set was established.
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