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510(k) Data Aggregation
(266 days)
· Noninflammatory degenerative joint disease including osteoarthritis and avascular necrosis.
· Rheumatoid arthritis.
· Correction of functional deformity.
· Treatment of non-union. femoral neck fracture, and trochanteric fractures of the proximal femur with head involvement. unmanageable by other techniques.
· Revision procedures where other treatment or devices have failed.
Porous acetabular shells and femoral stems are indicated for uncemented biological fixation. Non-coated or polyethylene components may be used with mating components that are indicated for either cemented use.
The G7 Acetabular System is a modular system, designed to provide numerous options for surgeons and patients in one compatible system. It is modular in design including multiple variants of acetabular shells: a titanium alloy (ASTM F136) shell with an apical hole and plug, the outer surface of the shell is coated with Biomet's Porous Plasma Spray (PPS®) (ASTM F1580) or produced by additive manufacturing using titanium alloy powder as OsseoTi® (ASTM F2924), available in solid shell, limited hole, and multi-hole designs as well as PPS Finned limited hole shells. The other main component is an acetabular liner manufactured from UHMWPE polyethylene, offered in both highly crosslinked polyethylene (HXPE) and Vitamin-E Highly Crosslinked polyethylene (VEHXPE), available in Neutral, High Wall, Neutral +5mm, or 10 Degree Face Changing designs.
The provided text describes a 510(k) premarket notification for the Zimmer, Inc. G7 Acetabular System, specifically focusing on the introduction of new acetabular liners.
Based on the document, there is no acceptance criteria or study that proves a device (in the context of an AI/ML medical device) meets acceptance criteria, an MRMC comparative effectiveness study, or standalone algorithm performance data.
The document pertains to a hip prosthesis which is a physical implant, not an AI/ML medical device. The "performance data" mentioned refers to non-clinical mechanical testing and engineering analysis for the physical implant, demonstrating that modifications to the physical device do not adversely affect its safety and efficacy.
Therefore, I cannot extract the requested information regarding AI/ML device acceptance criteria and performance from this document. The questions posed are relevant to AI/ML or diagnostic devices, but this document describes a physical orthopedic implant.
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