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510(k) Data Aggregation
(83 days)
ORTHOPEDIATRICS PLATING SYSTEM
The OrthoPediatrics Plating System is intended for use in the treatment of pelvic, small and long bone fractures.
The OrthoPediatrics Pediatric Plating system is a system of bone plates and screws to provide the pediatric and general orthopedic surgeon with necessary devices to achieve optimal bone fixation when treating fractures, osteotomies, mal-unions, and mal-alignments.
- Materials: The devices are manufactured from 316L stainless steel, which . meet ASTM F138 and F139, and ISO-5832 standards.
- Eunction: The system functions to provide immediate stability and . temporary fixation during the natural healing process.
The system includes cortical and cannulated screws, and specialty plates. The specialty plates will include three distinct shapes and each shape will be offered in multiple sizes to accommodate the individual requirements of the patient anatomy to aid the surgeon in achieving optimal fixation. The three specialty plates' shapes resemble the letters H and I, and the infinity symbol (similar to the number 8, lying on its side).
The provided text is related to a 510(k) premarket notification for a medical device (OrthoPediatrics Plating System). It primarily focuses on demonstrating substantial equivalence to predicate devices based on design, materials, and indications for use.
Crucially, it does not contain any information about acceptance criteria, device performance studies, sample sizes, ground truth establishment, expert adjudication, or comparative effectiveness studies (MRMC or standalone AI performance tests). These types of studies and their results are typically required for AI/ML-driven devices to demonstrate their clinical validity and utility.
Therefore, I cannot populate the requested table and answer the study-related questions based on the provided text.
The document is a standard 510(k) clearance letter for a traditional medical device (bone plates and screws), where substantial equivalence is typically established through comparisons of material properties, design specifications, and intended use with already marketed devices, rather than through performance metrics of an AI algorithm.
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