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510(k) Data Aggregation
(40 days)
The Distal Radius Plating System is indicated for use in open reduction and internal fixation of Frykman type I-IV dorsally displaced Colles fractures, intomies, and carpal fusions of the distal radius in the presence of appropriate immobilization.
The Distal Radius Plating System consists of resorbable dorsal and volates. The plates are used in conjunction with 2.5mm resorbable screws. The plates and screws are made of a L-lactide/glycolide co-polymer.
This document is a 510(k) premarket notification for a medical device called the "Distal Radius Plating System." It outlines the device's description, intended use, and a comparison to substantially equivalent devices. However, it explicitly states that no clinical data was completed. Therefore, the request for acceptance criteria and a study proving the device meets those criteria cannot be fully answered as these were not provided or conducted for this specific submission.
Given the information provided, here's what can be extracted and what cannot:
1. A table of acceptance criteria and the reported device performance
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Mechanical Properties Equivalence (to predicate devices: Bionx Biodegradable Threaded Distal Radius Screw and Resorbable Bone Pins) | "Extensive testing determined that the Distal Radius Plating System and Bionx Biodegradable Threaded Distal Radius Screw have equivalent mechanical properties." |
| Biocompatibility (non-toxic, non-mutagenic, non-pyrogenic) | "Biocompatibility testing was completed and demonstrated that the co-polymer material is non-toxic, non-mutagenic, and non-pyrogenic." |
| In-vitro Mechanical Testing (equivalence to predicate devices) | "In-vitro mechanical testing was completed and demonstrated that the Distal Radius Plating System was equivalent to the predicate devices." |
| Clinical Performance (e.g., fracture healing rates, complication rates, functional outcomes) | NOT APPLICABLE - "No clinical data was completed." |
2. Sample sized used for the test set and the data provenance
- Mechanical and biocompatibility testing: The document does not specify the sample sizes used for the in-vitro mechanical testing or the biocompatibility testing.
- Clinical test set: There was no clinical test set.
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 as no clinical testing was performed for this 510(k) submission. For the non-clinical testing (mechanical and biocompatibility), the "ground truth" would be established by the testing methodology itself, rather than expert consensus on retrospective data.
4. Adjudication method for the test set
- This information is not applicable as no clinical testing was performed.
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
- This information is not applicable. The device is a physical orthopedic implant, not an AI-assisted diagnostic or therapeutic tool. Therefore, an MRMC study and AI-related metrics are irrelevant.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- This information is not applicable. The device is a physical orthopedic implant, not an algorithm.
7. The type of ground truth used
- For mechanical properties, the "ground truth" was established by recognized testing standards and comparison to the mechanical integrity of legally marketed predicate devices.
- For biocompatibility, the "ground truth" was established by standardized laboratory tests to assess toxicity, mutagenicity, and pyrogenicity.
- For clinical outcomes, there was no ground truth established as no clinical data was collected.
8. The sample size for the training set
- This information is not applicable as the device is not an AI algorithm requiring a training set. The "training" for this type of device development involves materials science, engineering design, and testing, not machine learning.
9. How the ground truth for the training set was established
- This information is not applicable as the device is not an AI algorithm.
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