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510(k) Data Aggregation
(83 days)
The Conventus PRSTM System is indicated for treatment of proximal radial fractures when internal fixation is desired, and fracture fragments are not too numerous and/or too small to be stabilized with the use of the device.
The Conventus PRSTM is an intramedullary device intended for proximal radius fractures. The PRSTM System is a self-expanding implant which is deployed into the medullary canal and provides a scaffold to which bone fragments are attached using fragment screws. The implant is made from titanium alloy (Ti-6Al-4V ELI) and Nitinol.
This document is a 510(k) premarket notification decision letter from the FDA to Conventus Orthopaedics, Inc. It concerns the Conventus PRSTM System, an intramedullary device for proximal radial fractures. The letter confirms substantial equivalence to predicate devices based on pre-clinical testing mentioned in the 510(k) Summary.
Here's an analysis of the provided information, focusing on acceptance criteria and study details:
1. A table of acceptance criteria and the reported device performance
The provided document does not explicitly state specific acceptance criteria (e.g., pass/fail thresholds) for the pre-clinical tests. It lists the types of tests performed and concludes that "The results demonstrate that the PRSTM System is substantially equivalent to the legally marketed predicate devices." This implies that the device performance met the criteria necessary to demonstrate equivalency to the predicate devices, whatever those inherent criteria were for each test.
| Acceptance Criteria Type (Implicit) | Reported Device Performance (Summary) |
|---|---|
| Static and cyclic axial/bend testing | Met performance equivalent to predicate devices. |
| Static and cyclic torsional testing | Met performance equivalent to predicate devices. |
| Screw pullout testing | Met performance equivalent to predicate devices. |
| Corrosion testing | Met performance equivalent to predicate devices. |
| Wear testing | Met performance equivalent to predicate devices. |
| Nickel ion release testing | Met performance equivalent to predicate devices. |
| Surface analysis testing | Met performance equivalent to predicate devices. |
| Nitinol phase composition | Met performance equivalent to predicate devices. |
| Nitinol transition temperature (Af) | Met performance equivalent to predicate devices. |
| Biocompatibility testing | Met performance equivalent to predicate devices. |
| Animal Testing | Met performance equivalent to predicate devices. |
| MRI Testing | Met performance equivalent to predicate devices. |
2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective)
The document does not provide specific sample sizes for any of the listed pre-clinical tests. It also does not specify the data provenance in terms of country of origin or whether the studies were retrospective or prospective. Given these are pre-clinical (laboratory and animal) tests, the concept of retrospective/prospective human data provenance does not apply.
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)
This section is not applicable to the type of pre-clinical studies described. These studies involve material science, mechanical engineering, and animal models, not human diagnostic interpretation requiring expert consensus on ground truth.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
This section is not applicable as the studies are physical/mechanical/biological tests, not diagnostic interpretations requiring adjudication.
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
An MRMC comparative effectiveness study was not conducted. This is a pre-clinical evaluation of a surgical implant, not an AI-assisted diagnostic tool.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done
This refers to AI algorithm performance and is not applicable to the pre-clinical evaluation of a medical device implant.
7. The type of ground truth used (expert concensus, pathology, outcomes data, etc)
For these pre-clinical studies, "ground truth" refers to the established scientific and engineering principles, material properties, and biological responses measured by validated test methods. For example:
- Mechanical tests: Ground truth is derived from engineering standards, material specifications, and the established performance characteristics of the predicate devices.
- Corrosion, wear, nickel ion release, surface analysis, Nitinol properties: Ground truth is based on established material science standards and acceptable ranges for medical implant materials.
- Biocompatibility: Ground truth is established by ISO standards and recognized biological response criteria (e.g., cytotoxicity, sensitization, irritation).
- Animal Testing: Ground truth involves histological analysis, imaging, and functional assessment to determine biological response and healing in comparison to expected outcomes or predicate device performance.
8. The sample size for the training set
This refers to AI model training and is not applicable to the pre-clinical evaluation of a medical device implant.
9. How the ground truth for the training set was established
This refers to AI model training and is not applicable to the pre-clinical evaluation of a medical device implant.
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