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510(k) Data Aggregation
(28 days)
CapSure**®** PS System
The CapSure® PS System is a non-cervical spinal fixation system intended for posterior pedicle screw fixation (T1-S2/ilium) in skeletally mature patients. The CapSure® PS System is indicated for degenerative spondylolisthesis with objective evidence of neurologic impairment, fracture, dislocation, scoliosis, spinal tumor, and failed previous fusion (pseudoarthrosis).
The CapSure® PS System is also indicated for pedicle screw fixation in skeletally mature patients with severe spondylolisthesis (Grades 3 and 4) at the L5-S1 vertebral joint, having fusions with autogenous bone graft, with the device fixed or attached to the lumbar and sacral spine (levels of pedicle screw fixation are L3-S2/ilium), and for whom the device is intended to be removed after solid fusion is attained.
The CapSure® PS System consists of a selection of non-sterile, single-use, titanium alloy screw and connector components and titanium alloy and cobaltchrome rod components that are assembled to create a rigid spinal construct. The components of the CapSure® PS System are attached to the non-cervical spine of skeletally mature patients to stabilize the spine during fusion of vertebral bodies and are intended to be removed after spinal fusion is achieved.
This 510(k) premarket notification describes a medical device, the CapSure® PS System, which is a spinal fixation system. The document concerns the addition of new components (4.75 mm diameter cobalt-chrome straight rods and dual-diameter titanium rods) to a previously cleared system.
Therefore, the study described is a performance test to demonstrate that these new components do not degrade the overall device performance and are substantially equivalent to the predicate device. This is not a study involving human or image data with AI systems.
Based on the provided information, I can answer the relevant questions about the device's performance testing:
1. Table of Acceptance Criteria and Reported Device Performance
Acceptance Criteria (Standard) | Reported Device Performance |
---|---|
In accordance with ASTM F1717 | "The results of this testing show that the modified implants do not represent a new worst case for the system and are therefore substantially equivalent to the predicate device." |
2. Sample size used for the test set and the data provenance:
- Sample Size: The document does not specify the exact number of samples tested but refers to "worst-case samples of the modified implants."
- Data Provenance: Not applicable as this is a physical device performance test rather than a data-driven study. The testing was performed by Spine Wave, Inc.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
Not applicable. The ground truth (device performance and safety) for this type of mechanical testing is established by adherence to a recognized international standard (ASTM F1717) and engineering analysis, not by expert consensus on clinical data.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:
Not applicable. Adjudication methods are typically associated with human decision-making or image interpretation, not physical device testing.
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 is a mechanical device performance study, not a study evaluating human reader performance with or without AI assistance.
6. If a standalone (i.e. algorithm only, without human-in-the-loop performance) was done:
Not applicable. This is a mechanical device performance study, not an algorithm performance study.
7. The type of ground truth used:
The ground truth used is conformance to the ASTM F1717 standard for dynamic axial compression bend testing and the determination that the modified implants "do not represent a new worst-case for the system."
8. The sample size for the training set:
Not applicable. There is no training set mentioned or implied as this is a physical device performance test, not a machine learning model.
9. How the ground truth for the training set was established:
Not applicable. There is no training set.
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