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510(k) Data Aggregation
(286 days)
Nexis**®** compressive screws
Nexis® compressive screws system is a single use device indicated for the fixation, correction or stabilization of bones and bone fragments of the foot and ankle in adult patients. The system is indicated for:
Ø5.0mm compressive screw:
- Os Calcis and talar fractures
- Calcaneus osteotomies
- Arthrodesis of the tarsals
Ø7.0mm compressive screw:
- Ankle arthrodesis
- Calcaneus osteotomies
Nexis® is a range of osteosynthesis compressive single use screws, made of titanium alloy, designed to address foot and ankle indications. These devices are designed for stable fixation and have quick insertion features.
They are implantable medical devices intended to be used in orthopedics for foot and ankle surgery. The device is sold sterile. The shelf life is 5 years.
This FDA 510(k) premarket notification summary for the Nexis® compressive screws describes non-clinical testing to demonstrate substantial equivalence to predicate devices. It does not involve AI or algorithms, and therefore, an analysis of the device's performance based on AI/ML criteria is not applicable. The provided document focuses on mechanical and biological properties of the screws.
Here's an analysis of the available information regarding acceptance criteria and the study (non-clinical) that proves the device meets them:
1. A table of acceptance criteria and the reported device performance
Test | Acceptance Criteria (Implicit) | Reported Device Performance |
---|---|---|
Torsion Resistance | Prevent screw breakage during insertion/removal (evaluated against predicate device) | Performed according to ASTM F543-17 and evaluated against a predicate device. (Specific values not provided, but deemed acceptable by equivalence) |
Strength (Insertion/Removal) | Avoid failure of the screw during insertion or removal | Performed according to ASTM F543-17. (Specific values not provided, but deemed acceptable by equivalence) |
Axial Pull-out Resistance | Valid suitable anchorage when subjected to tensile forces, poor bone quality, or osteoporotic bone | Assessed using the equation described by Chapman et al., 1996. (Specific values not provided, but deemed acceptable by equivalence) |
Sterilization and Reprocessing | Cleanliness and sterility of the device and instruments, sterility assurance level of 10-6 | Performed according to ISO 11137-1, ISO 11607-1, and ISO 11607-2. (Specific results not provided, but deemed acceptable) |
Biocompatibility | Device is biocompatible for implantable use | Assessed using ISO 10993-1:2018. (Specific results not provided, but deemed acceptable) |
Notes on Acceptance Criteria: The document primarily relies on demonstrating substantial equivalence to predicate devices through established industry standards (ASTM, ISO) and relevant guidance (FDA Guidance "orthopedic non-Spinal metallic bone screw and washers – Performance Criteria for safety and Performance based pathway"). The specific quantitative acceptance criteria (e.g., minimum torque values, pull-out strength in Newtons) are not explicitly stated in this summary but would have been defined within the full test reports submitted to the FDA and would align with the predicate device's performance or standard requirements.
2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
- Sample Size for Test Set: Not explicitly stated for each test. The testing involved various mechanical and biological evaluations of the screws. Typically, mechanical testing involves a statistically relevant number of samples to ensure reproducibility and confidence in results (e.g., 5-10 samples per test condition), but this detail is omitted from the summary.
- Data Provenance: The studies are non-clinical, so "country of origin of the data" in the sense of patient data is not applicable. The testing was performed in the context of the manufacturer (Novastep® S.A.S.) who is based in France. The studies are by nature prospective, as they are conducted specifically to support the 510(k) submission.
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 medical device (screw) clearance based on mechanical, material, and biological properties, not an AI/ML diagnostic or prognostic device that requires expert-established ground truth from medical images or patient data.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
Not applicable. Adjudication methods are relevant for studies involving human interpretation of data, typically in diagnostic or screening contexts, often with images. This submission is for a physical orthopedic implant and does not involve such an adjudication process.
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 not an AI/ML-driven device. Therefore, no MRMC study or assessment of human reader improvement with AI assistance was conducted.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Not applicable. This is not an AI/ML-driven device or an algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
Not applicable. For this type of device, "ground truth" is established through engineering principles, material science, and conformance to recognized standards (e.g., ASTM, ISO), rather than medical consensus or clinical outcomes data. The performance of the device itself (e.g., its strength, sterility, biocompatibility) is the "ground truth" being assessed against predefined engineering and quality specifications.
8. The sample size for the training set
Not applicable. This involves non-clinical testing of physical devices, not an AI/ML algorithm that requires a training set.
9. How the ground truth for the training set was established
Not applicable. As noted in point 8, there is no training set for an AI/ML algorithm in this submission.
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