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The CENTINEL SPINE PCT SYSTEM is intended to provide immobilization of spinal segments as an adjunct to fusion for the following acute and chronic instabilities of the cervical spine (C1 to C7) and the thoracic spine from T1-T3: traumatic spinal fractures and/or traumatic dislocations; instability or deformity; failed previous fusions (e.g., pseudarthrosis); tumors involving the cervical spine; and degenerative disease, including intractable radiculopathy and/or myelopathy, neck and/or arm pain of discogenic origin as confirmed by radiographic studies, and degenerative disease of the facets with instability. The CENTINEL SPINE PCT SYSTEM is also intended to restore the integrity of the spinal column even in the absence of fusion for a limited time period in patients with advanced stage tumors involving the cervical spine in whom life expectancy is of insufficient duration to permit achievement of fusion.

The Centinel Spine PCT System consists of a variety of shapes and sizes of rods, hooks, polyaxial screws, and connecting components (e.g., variable and fixed cross connectors). The hooks and polyaxial screws are intended to be attached to the posterior elements of the cervical and/or upper thoracic spine and serve as bone anchors. The rods are longitudinally secured to the bone anchors with the set screw. The various connecting components serve to both secure the construct and provide additional construct configuration options. All implants are manufactured from titanium alloy, Ti6A14V (ASTM F136 or ISO 5832-3)

This document is a 510(k) summary for the Centinel Spine PCT System, a device intended for spinal immobilization and stabilization. It primarily focuses on demonstrating substantial equivalence to predicate devices rather than presenting a study of the device's performance against specific clinical acceptance criteria in terms of AI/algorithm efficacy. As such, many of the requested categories related to AI performance, ground truth, and expert evaluation are not directly applicable or available in this document.

However, I can extract information related to the device's mechanical performance testing:

1. A table of acceptance criteria and the reported device performance:

2. Sample size used for the test set and the data provenance:

• Test Set Sample Size: Not explicitly stated within this document. The testing refers to "performance testing" and indicates that "published literature" was also used, but does not detail the number of constructs or specimens tested for each mechanical test.
• Data Provenance: The document does not specify the country of origin of the data. The tests are described as "Performance Testing" conducted according to modified versions of ASTM standards (ASTM F1717 and ASTM F1798), implying laboratory-based mechanical testing rather than clinical data from human subjects. It would be considered an in-vitro study.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

This information is not applicable. The "ground truth" here is mechanical performance measured against engineering standards, not clinical diagnoses or outcomes requiring expert interpretation.

4. Adjudication method for the test set:

Not applicable. Mechanical tests for physical devices typically involve direct measurement against specified engineering limits, not human adjudication.

5. 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 device is a spinal implant, not an AI diagnostic tool that assists human readers.

6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:

Not applicable. This is a physical medical device, not an algorithm.

7. The type of ground truth used:

The ground truth used for performance assessment was based on mechanical engineering standards and the performance of predicate devices. Specifically, the "acceptance criteria were defined by predicate device performance."

8. The sample size for the training set:

Not applicable. This is not an AI/machine learning device that would have a training set.

9. How the ground truth for the training set was established:

Not applicable.

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