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510(k) Data Aggregation
(24 days)
The Blackstone Pedicle Screw System is intended for posterior, non-cervical pedicle fixation. Pedicle screw fixation is limited to skeletally mature patients and is intended to be used as an adjunct to fusion using autograft or allograft. The device is indicated for all of the following indications regardless of the intended use:
- degenerative disc disease (defined as discogenic back pain with degeneration of the disc confirmed by history and radiographic studies)
- spondylolisthesis.
- trauma (i.e., fracture or dislocation).
- spinal stenosis.
- deformities or curvatures (i.e., scoliosis, kyphosis, and/or lordosis),
- tumor,
- pseudoarthrosis, and
- failed previous fusion
The Blackstone Pedicle Screw System components are used with certain components of the Blackstone SFS system, including rods, rod connectors and cross-connectors.
The Blackstone Pedicle Screw System 4.0 mm Diameter Screws consists of an assortment of multiaxial and monoaxial pedicle screws.
The provided text describes a 510(k) premarket notification for a modification to the Blackstone Pedicle Screw System, specifically introducing 4.0 mm diameter screws. The submission highlights mechanical testing conducted to demonstrate substantial equivalence to predicate devices, rather than a study involving human subjects or AI-based performance metrics.
Therefore, many of the requested elements are not applicable to this type of submission, as they pertain to clinical studies or AI/software validation.
Here's an analysis based on the provided document:
1. A table of acceptance criteria and the reported device performance
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Substantial Equivalence to Predicate Devices (Blackstone Pedicle Screw System K081684) | Mechanical testing demonstrated that the additional 4.0 mm diameter screw components are substantially equivalent to the current Blackstone Pedicle Screw System. |
2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
The document primarily discusses mechanical testing, not clinical studies or data involving human subjects in a "test set" in the context of AI or diagnostic performance. Therefore, the concepts of "sample size for the test set" and "data provenance" (country, retrospective/prospective) as they relate to human data are not applicable here. The data provenance would be from manufacturing and testing facilities.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)
Not applicable. This is a submission for a mechanical medical device, not a diagnostic or AI device that requires expert-established ground truth from images or clinical assessments. Ground truth for mechanical testing would involve engineering standards, material properties, and physical measurements.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
Not applicable. Adjudication methods are relevant for clinical assessments or expert reviews, not for mechanical device testing where results are quantifiable through engineering metrics.
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 submission. There is no AI component or human reader involvement described.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Not applicable. This is a mechanical device submission.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
For mechanical testing, the "ground truth" would be established by:
- Engineering Standards: Adherence to established ASTM or ISO standards for spinal implants (e.g., fatigue strength, torsional rigidity, pull-out strength).
- Predicate Device Performance Data: The performance characteristics of the legally marketed predicate devices (K081684, K052123, K052151) serve as the benchmark for substantial equivalence.
8. The sample size for the training set
Not applicable. There is no "training set" in the context of AI or machine learning for this mechanical device.
9. How the ground truth for the training set was established
Not applicable. There is no "training set" for this mechanical device.
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