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510(k) Data Aggregation
(74 days)
EBI X FIX DYNAFIX SYSTEM/EBI DFS DISTAL RADIUS FIXATOR SC BONE SCREWS
The EBI X FIX DynaFix System is intended for the treatment of bone conditions including leg lengthening, osteotomies, arthrodesis, fracture fixation, and other bone conditions amenable to treatment by use of the external fixation modality. The EBI DFS™ Distal Radius Fixator is intended for use in upper extremity applications for the reduction, alignment and stabilization of intra-articular and extra-articular fractures, corrective osteotomies, and soft tissue deformities.
The bone screws have a tapered thread diameter and are available in a variety of diameters and lengths in both cortical and cancellous thread patterns. The screws will be available with and without the additional proprietary silver coating which has been shown to significantly reduce bacterial colonization of the surface, and will be sold sterile and nonsterile.
This 510(k) summary (K961433) describes external fixation bone screws (EBI X FIX™ DynaFix™ System - SC Bone Screws and EBI DFS™ Distal Radius Fixator - SC Bone Screws) manufactured from stainless steel, 316L, with an optional silver coating. The primary focus of the submission appears to be demonstrating substantial equivalence to existing devices, particularly regarding the silver coating's safety and effectiveness.
Here's an analysis of the provided information against your requested criteria:
1. Table of Acceptance Criteria and Reported Device Performance
The provided text does not explicitly state specific acceptance criteria in terms of performance metrics (e.g., a certain reduction in bacterial colonization percentage, or a specific fatigue life in cycles). Instead, it states that the silver coating "has been shown to significantly reduce bacterial colonization of the surface" and that the "coated screws underwent biocompatibility, fatigue, and direct inoculation testing. They are substantially equivalent to the predicate devices in design and function."
Therefore, constructing a table with explicit "acceptance criteria" is not possible from this document as presented. The implicit acceptance criteria are that the device (specifically the silver coating) is safe, performs its intended function (bacterial reduction), and does not negatively impact existing device functionality (fatigue, biocompatibility) when compared to predicate devices.
Acceptance Criteria (Implied) | Reported Device Performance |
---|---|
Significant reduction in bacterial colonization | "significantly reduce bacterial colonization of the surface" |
Biocompatibility | "underwent biocompatibility... testing" |
Fatigue performance equivalent to predicate | "underwent...fatigue...testing" |
"Direct inoculation" performance acceptable | "underwent...direct inoculation testing" |
Substantially equivalent in design and function to predicate devices | "They are substantially equivalent to the predicate devices in design and function." |
2. Sample Size Used for the Test Set and Data Provenance
The document does not specify the sample size used for any testing (biocompatibility, fatigue, direct inoculation).
The data provenance is not explicitly stated (e.g., country of origin). It can be inferred that the testing was conducted to support a US FDA 510(k) submission, suggesting it adheres to relevant US regulatory standards, but the physical location of the studies is not mentioned.
The document does not explicitly state whether the studies were retrospective or prospective. Given the nature of premarket testing for a 510(k), these would typically be prospective laboratory studies or animal studies (for biocompatibility and direct inoculation) and benchtop studies (for fatigue).
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications of Those Experts
This information is not provided in the document. The studies mentioned (biocompatibility, fatigue, direct inoculation) are typically laboratory-based tests with objective endpoints and do not typically involve human experts establishing a "ground truth" in the same way clinical imaging studies might.
4. Adjudication Method for the Test Set
This information is not applicable/not provided. Adjudication methods are relevant when there are subjective assessments or interpretations, often by multiple human readers, in clinical studies. The tests mentioned (biocompatibility, fatigue, direct inoculation) are objective laboratory tests.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size of Human Improvement with AI vs. Without AI Assistance
This information is not applicable. This submission is for an external fixation bone screw, not an AI-powered diagnostic or assistive tool. Therefore, MRMC studies and the concept of human readers improving with AI are not relevant to this device.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done
This information is not applicable. This is a medical device (bone screw) and not software or an algorithm.
7. The Type of Ground Truth Used
The "ground truth" for the tests mentioned would be based on:
- Biocompatibility: Standardized toxicity assays (e.g., cytotoxicity, irritation, sensitization), often defined by international standards (e.g., ISO 10993 series) and assessed against negative and positive controls.
- Fatigue: Physical endurance testing to a predefined load until failure or to a specified number of cycles, according to relevant ASTM or ISO standards for medical implants.
- Direct Inoculation: Laboratory studies where the device surface is directly exposed to specific bacterial strains to quantify bacterial growth or inhibition.
- Predicate Device Performance: The ground truth for "substantial equivalence" relies on the known performance and safety profiles of the legally marketed predicate devices.
8. The Sample Size for the Training Set
This information is not applicable/not provided. The device is not an AI/machine learning model, so there is no "training set" in that context. If "training set" refers to samples used for initial development and iteration prior to formal testing, that information is not disclosed.
9. How the Ground Truth for the Training Set Was Established
This information is not applicable. As stated above, there is no "training set" in the context of an AI/machine learning model for this device.
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