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510(k) Data Aggregation
(59 days)
The VariAx 2 System is indicated for adult and pediatric patients, where the implant would not cross open growth plates, for the treatment of normal or osteopenic bone for the following conditions or procedures:
- · Fracture fixation, including single, segmental, and comminuted fractures
- · Revision, including nonunion and malunion
- · Intra- and extra-articular fractures
- · Compression fracture
- · Displaced fracture
- · Reconstruction
- · Replantation
- · Arthrodesis
- · Osteotomy
VariAx 2 is a system used for internal fixation applications and is composed of sterile and nonsterile screws, washers, and instruments. In addition to independent use, screws of this system are also used with compatible, internal fixation plating systems. These devices are made of titanium alloy, with Type III anodization, and are available in a variety of sizes and diameters, as well as locking and non-locking types.
This submission builds on K140769 by simplifying and clarifying the indications statement, and by expanding the treatment population to include pediatric patients.
I am sorry, but the provided text from the FDA 510(k) K173135 for the "VariAx 2 System" does not contain any information about acceptance criteria, device performance data (from a study), or details about a study design (like sample size, ground truth establishment, expert qualifications, etc.) for an AI/algorithm-based medical device.
This FDA submission is for a bone fixation system (screws, plates, washers), which is a physical medical device, not a software or AI-based device. The document explicitly states:
- "No new devices were introduced with this submission. No mechanical testing was presented."
- "Clinical testing was not a requirement of this submission."
Therefore, I cannot fulfill your request to describe the acceptance criteria and the study that proves the device meets them, as the provided text pertains to a hardware medical device and does not detail performance studies in the way you are asking about (which are typical for AI/ML or diagnostic devices).
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