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510(k) Data Aggregation
(29 days)
The HEALIX Compression Screw (HCS) System is indicated for Bone Fractures, Osteotomies, Arthrodeses, Osteochondritis, and Tendon Reattachment. It is intended for, but not limited to, Hand Surgery, Orthopedic Surgery, and Podiatric Surgery but is not intended for attachment or fixation to the posterior elements (pedicles) of the spine.
The Healix Compression Screw (HCS) System consists of cannulated, solid titanium allov. headless, headed screws and specialized instrumentation. This submission expands the Healix offering and includes longer screws ranging from 31 to 130mm in length for the 2.0 to 7.5mm diameters.
The provided text is a 510(k) summary for the Nvision Biomedical Technologies' Healix Compression Screw System. This document focuses on demonstrating substantial equivalence to predicate devices, primarily through engineering analysis. It does not contain information about acceptance criteria or a study proving that a device meets those criteria in the context of AI/ML or diagnostic performance.
Instead, this document is a regulatory submission for a physical medical device (bone fixation screws) and relies on mechanical performance characteristics and a comparison to existing predicate devices.
Therefore, I cannot extract the requested information (items 1-9) as it pertains to AI/ML device performance from the provided text. The document clearly states:
- "No FDA performance standards have been established for the Healix Compression Screw System."
- "The following was performed to demonstrate safety per methods of the previous submission: . Engineering analysis comparison of mechanical performance characteristics"
- "The results of the engineering analysis indicate that the Healix Compression Screw System is substantially equivalent to the predicate devices."
This indicates the evaluation was based on engineering analysis and comparison against physical predicate devices, not on a study proving a device meets acceptance criteria related to diagnostic performance, human-in-the-loop improvements, or ground truth establishment for AI/ML.
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