(86 days)
The Stryker Spine Oasys Bone Screw is intended to stabilize the spine as an aid to fusion through bilateral immobilization of the facet joints. The screws are inserted posteriorly through the superior side of the facet, across the facet joint, and into the pedicle. The Stryker Spine Oasys Bone Screw is indicated for bilateral fixation, with or without bone graft, at single or multiple levels, from C2 to T3. The Stryker Spine Oasys Bone Screw is indicated for treating any or all of the following:
- Trauma, including fractures and/or dislocations
- Spondylolisthesis
- Spondylolysis
- Pseudoarthrosis or failed previous fusions which are symptomatic or which may cause secondary instability or deformity
- Degenerative disc disease (DDD) as defined by neck and back pain of discogenic origin with degeneration of the disc confirmed by history and radiographic studies
- Degenerative disease of the facets with instability
The Stryker Spine Oasys Bone Screw is available in 3.5 and 4.0 mm diameters and a variety of lengths in order to accommodate patient anatomy. The components are fabricated from titanium alloy. The implants will be provided non-sterile.
The provided text is a 510(k) Premarket Notification for the Stryker Spine Oasys Bone Screw. This document does not describe a software or AI/ML device that would have acceptance criteria and a study design as typically associated with such technologies (e.g., diagnostic accuracy, performance metrics like sensitivity/specificity). Instead, it's for a physical medical device (bone screw).
Therefore, I cannot extract the requested information regarding acceptance criteria and study particulars in the context of an AI/ML device. The document states:
- Substantial Equivalence: "Equivalency of this device is based on similarities in intended use, materials, and design to other currently marketed transfacetpedicular screws. Mechanical testing demonstrated comparable mechanical properties to the predicate device."
This indicates that the "study" for this device involved mechanical testing to show its performance was comparable to existing predicate devices, rather than a clinical study with human readers or AI algorithms.
To answer your specific points, based on the provided text, here’s how they relate to this physical device:
- A table of acceptance criteria and the reported device performance: This document does not provide a table of acceptance criteria or specific performance metrics in the format you'd expect for an AI/ML device. The "performance" is stated as "comparable mechanical properties to the predicate device."
- Sample sized used for the test set and the data provenance: Not applicable. There's no "test set" in the context of diagnostic accuracy. The testing was mechanical.
- Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth for diagnostic accuracy is not relevant to mechanical testing of a bone screw.
- Adjudication method for the test set: Not applicable.
- If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance: Not applicable. This is not an AI-assisted device.
- If a standalone (i.e. algorithm only without human-in-the loop performance) was done: Not applicable. This is not an algorithm.
- The type of ground truth used: For a physical device like a bone screw, "ground truth" would relate to material properties, strength, fatigue life, etc., established through engineering standards and laboratory testing, not medical expert consensus or pathology in the diagnostic sense.
- The sample size for the training set: Not applicable. There is no training set for a bone screw in the AI/ML context.
- How the ground truth for the training set was established: Not applicable.
In summary, the provided document pertains to a physical medical device (bone screw) and its clearance based on substantial equivalence, primarily supported by mechanical testing, not a clinical performance study with AI/ML components or human review of diagnostic images. Therefore, the requested information elements are not applicable to this submission.
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