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510(k) Data Aggregation
(26 days)
REFLECTION MODIFIED ACETABULAR SHELLS
Total hip components are indicated for individuals undergoing primary and revision surgery where other treatments or devices have failed in rehabilitating hips damaged as a result of trauma, inflammatory joint disease such as rheumatoid arthritis, or noninflammatory degenerative joint disease (NIDJD) or any of its composite diagnoses such as osteoarthritis; avascular necrosis; traumatic arthritis; slipped capital epiphysis; fused hip; fracture of the pelvis; diastrophic variant; old, remote osteomyelitis with an extended drainage-free period; nonunion; femoral neck fracture and trochanteric fractures of the proximal femur with heads involvement that are unmanageable using other techniques; femoral osteotomy, or Girdlestone resection; fracture dislocation of the hip; and correction of deformity. The Reflection Modified Acetabular Shells are designed for uncemented applications and are single use only.
The Reflection Modified Acetabular Shells are titanium acetabular components with peripheral fixation holes in the spline of the device. The shells are coated with a -45/+60 porous titanium bead coating. The shells are also offered in a hydroxyapatite coating applied to the porous surface of the implant. The components are designed for use with existing UHMWPE acetabular liners of the Reflection Hip System.
The provided document does not describe acceptance criteria for an AI/ML device nor a study proving it meets such criteria.
Instead, it's a 510(k) Premarket Notification summary for a traditional medical device, specifically the "Reflection Modified Acetabular Shells" (a hip implant component), dated August 28, 2002.
The key information from the document pertains to substantial equivalence to currently marketed devices, not to an AI/ML device's performance against specific acceptance criteria. The "Mechanical and Clinical Data" section broadly states that a review of mechanical test data indicated the device's equivalence and ability to withstand in vivo loading. This is not a detailed study of an AI/ML algorithm.
Therefore, I cannot extract the requested information regarding acceptance criteria and a study for an AI/ML device from this document.
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