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510(k) Data Aggregation
(53 days)
FixxSure**®** X-Link
The SpineWorks™ FixxSure® X-Link is intended to work with the Innovasis® Excella® Spinal System to provide immobilization and stabilization of spinal segments in skeletally mature patients as an adjunct to fusion in treatment of the following acute and chronic instabilities or deformities of thoracic, lumbar, and sacral spine:
- i) Severe spondylolisthesis (Grades 3 and 4) of the L5-S1 vertebra;
- ii) Degenerative spondylolisthesis with objective evidence of neurologic impairment;
- iii) Fracture;
- Dislocation; iv)
- Scoliosis: v)
- vi) Kyphosis;
- vii) Spinal tumor; and
- viii) Previous failed fusion (pseudarthrosis).
The SpineWorks™ FixxSure® X-Link can also be used with the Talon® Pedicle Screw System.*
The SpineWorks FixxSure X-Link is a transverse stabilizing device utilized to increase the strength of a pedicle screw instrumentation construct in posterior spinal fusion. The FixxSure implant comes in multiple lengths and has the capability of being manipulated into various planes of anqulation. The FixxSure implant has a proprietary dual locking mechanism allowing maximum cross-Link/rod connection while maintaining ease of insertion/use.
Here's an analysis of the acceptance criteria and study information based on the provided document:
1. Table of Acceptance Criteria and Reported Device Performance
Acceptance Criteria & Test | Reported Device Performance |
---|---|
Mechanical Testing | |
Dynamic compression bending | Both constructs successfully completed 5,000,000 cycles. |
(ASTM F1717-14) | |
Applied load: 175N (7.0Nm) | |
Frequency: 5Hz | |
Test duration: 5,000,000 cycles |
2. Sample Size Used for the Test Set and Data Provenance
- Sample Size for Test Set: Two Excella II pedicle screw constructs with the FixxSure X-Link were tested.
- Data Provenance: The document does not specify the country of origin for the data. The testing was non-clinical, implying it was conducted as part of the device development and validation by Innovasis, Inc. or a contracted testing facility. It is retrospective in the context of the 510(k) submission, meaning the tests were completed before the submission.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts
This information is not applicable as the "test set" in this context refers to physical device constructs undergoing mechanical testing, not a dataset requiring expert interpretation for ground truth.
4. Adjudication Method for the Test Set
This information is not applicable as the "test set" in this context refers to physical device constructs undergoing mechanical testing, not a dataset requiring adjudication.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size
This information is not applicable. The document describes a mechanical performance (non-clinical) study, not a clinical effectiveness study involving human readers or AI.
6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done
This information is not applicable. The device, FixxSure® X-Link, is a physical medical implant, not a software algorithm. Therefore, "standalone algorithm performance" is not relevant.
7. The Type of Ground Truth Used
The "ground truth" for this device's performance is based on objective mechanical performance metrics as defined by the ASTM F1717-14 standard. The standard itself provides the criteria for evaluating the device's ability to withstand dynamic compression bending without failure for a specified number of cycles.
8. The Sample Size for the Training Set
This information is not applicable. As a physical implant, there is no "training set" in the context of machine learning or algorithm development. The device's design is based on engineering principles and previous successful designs (predicates).
9. How the Ground Truth for the Training Set Was Established
This information is not applicable for the reasons stated above. The device's design and manufacturing rely on validated engineering specifications and quality control, not on a "ground truth" derived from a training dataset.
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