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510(k) Data Aggregation
(69 days)
PERIARTICULAR LOCKING PLATES AND SCREWS, MODEL 2358 SERIES
The Periarticular Locking Plate System is indicated for temporary internal fixation and stabilization of osteotomies and fractures, including:
- Comminuted fractures .
- . Supracondylar fractures
- Intra-articular and extra-articular condylar fractures .
- . Fractures in osteopenic bone
- . Nonunions
- Malunions . .
The Zimmer Periarticular Locking Plate System is a plate and screw system intended for internal fracture fixation. The low-profile periarticular locking plate is anatomically contoured and has threaded holes which accept locking screws to create a stable, fixed angle construct.
The provided document is a 510(k) Premarket Notification for the Zimmer® Periarticular Locking Plate System. This type of submission is for medical devices and focuses on demonstrating substantial equivalence to a predicate device, rather than proving efficacy through clinical or AI-specific performance studies with acceptance criteria, sample sizes, or ground truth as you've requested for an AI/algorithm-based device.
Therefore, the document does not contain the information requested regarding acceptance criteria, device performance tables, sample sizes for test/training sets, data provenance, expert ground truth establishment, adjudication methods, MRMC studies, or standalone algorithm performance.
The "Performance Data" section explicitly states: "The results of non-clinical analysis demonstrate that the device is safe and effective." This refers to mechanical testing or other non-clinical evaluations typical for an orthopedic implant, not to a performance study for an AI-enabled device.
To directly answer your questions based only on the provided text, the response would be:
This document is a 510(k) Premarket Notification for a traditional medical device (bone plate and screw system), not an AI/algorithm-enabled device. As such, it does not contain the information requested regarding acceptance criteria for an algorithm, study design elements for an AI performance evaluation (such as sample sizes for test/training sets, data provenance, expert qualifications, adjudication methods, MRMC studies, or standalone algorithm performance), or how ground truth was established for such a study. The document states that "non-clinical analysis demonstrate that the device is safe and effective," referring to engineering or mechanical testing, not an algorithmic performance study.
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