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510(k) Data Aggregation
(30 days)
The ORTHOFIX CHIMAERA Hip Fracture System – trochanteric nailing system is intended for insertion into the medullary canal of a femur for the alignment, stabilization of various types of fractures or deformities.
The ORTHOFIX CHIMAERA Hip Fracture System - trochanteric nailing system is indicated for treatment of stable and unstable pertrochanteric, intertrochanteric and subtrochanteric fractures of the femur alone or when these fractures occur in combination with shaft fractures extending distally to a point approximal to the intercondylar notch. These includes traumatic fractures, refractures, non-union, reconstruction, malalignment, pathological fractures and impending pathological fractures.
The ORTHOFIX CHIMAERA Hip Fracture System - Trochanteric Nailing System consists of implantable components (nails, end caps and screws) and instrumentation. The proximal part of the nail features a threaded bore to connect the nail to the targeting handle by means of a cannulated bolt. The insertion of the nail into the femur medullary canal is typically performed by some instruments, including: guide wire, awl, reamer and impactor elements.
This document describes the ORTHOFIX CHIMAERA Hip Fracture System – Trochanteric Nailing System, an intramedullary fixation rod. The information provided is a 510(k) premarket notification summary, which focuses on demonstrating substantial equivalence to a predicate device rather than presenting detailed performance data against specific acceptance criteria for a novel device.
Therefore, much of the requested information regarding acceptance criteria, specific study designs, sample sizes for test sets, and ground truth establishment for AI-based devices is not applicable to this submission, as it describes a traditional medical device (hardware) rather than a software or AI-driven diagnostic tool.
The "study" that proves the device meets acceptance criteria primarily refers to mechanical testing to demonstrate the structural integrity and performance of the hardware components.
Here's a breakdown of the available information in relation to your request:
1. Table of Acceptance Criteria and Reported Device Performance:
| Acceptance Criteria (Implied) | Reported Device Performance |
|---|---|
| Mechanical Performance: | |
| Withstand expected loads without failure | "All testing met or exceeded the requirements, as established by the test protocols and applicable standard." "A review of the mechanical data indicates that the components of the Subject device continues to be capable of withstanding expected loads without failure." |
| Compliance with ASTM F1264-16 Standard | "The following standard has been followed to perform mechanical test on the System configuration: ASTM F1264 -16 Standard Specifications and Test Methods for Intramedullary Fixation Devices." |
| Material Biocompatibility: | Implied similar to predicate (not explicitly detailed, but generally a requirement for implantable devices). |
| Sterility: | Implied similar to predicate (not explicitly detailed, but generally a requirement for implantable devices). |
| Intended Use: | "Has the mechanical properties to perform its indications safely." |
2. Sample size 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: This is not applicable in the context of device hardware mechanical testing. The "test set" here refers to the number of physical device components or constructs subjected to mechanical evaluation. The document does not specify the exact number of implants tested, but rather refers to "components" and "System configuration" being tested according to a standard.
- Data Provenance: The testing is laboratory-based mechanical testing, not clinical data provenance. The device manufacturer is Orthofix Srl, based in Italy.
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 is not applicable. For hardware mechanical testing, the "ground truth" is established by the specified mechanical properties and failure limits defined in the ASTM standard (ASTM F1264-16) and internal test protocols, not by expert human interpretation of data.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:
- This is not applicable. Mechanical testing results are typically objectively measured and compared against defined thresholds from standards or specifications, not subject to human adjudication in the way medical image interpretation is.
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:
- No, an MRMC comparative effectiveness study was NOT done. This type of study is relevant for AI-powered diagnostic devices or software that assist human readers. The ORTHOFIX CHIMAERA Hip Fracture System is a physical implant (hardware). The document explicitly states: "Clinical data was not needed to support the safety and effectiveness of the Subject Device."
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
- No, this is not applicable. The device is a physical implant, not an algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
- The "ground truth" for this device's performance is based on mechanical engineering principles and established industry standards (specifically ASTM F1264-16). This standard defines the acceptable mechanical properties and failure modes for intramedullary fixation devices. The device's performance is compared against these objective, quantifiable criteria.
8. The sample size for the training set:
- This is not applicable. There is no "training set" as this is not an AI/machine learning device. The design and manufacturing processes are refined through engineering principles and testing, not machine learning.
9. How the ground truth for the training set was established:
- This is not applicable. As there is no training set for an AI model, there is no ground truth established in this context.
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