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510(k) Data Aggregation
(257 days)
The XtraFix Small External Fixation System is indicated for use in construction of an external fixation frame for treatment of appropriately sized long bone (foot, arm, wrist and hand) fractures that require external fixation. Specifically, the system is intended for:
- Stabilization of open or closed fractures, typically in the context of polytrauma or where open or alternative closed treatment is undesirable or otherwise contraindicated;
- Arthrodesis and osteotomies with associated soft tissue problems;
- Stabilization of limbs after removal of total joint arthroplasty for infection or other failure:
- Stabilization of non-unions; and
- Intraoperative temporary stabilization tool to assist with indirect reduction.
The XtraFix Small External Fixation System subject of this 510(k) submission includes the following elements: Clamps (Bar/Pin to Bar/Pin, Integrated Multi-Pin); Bars; and Half Pins. The XtraFix Small External Fixation System is designed in such a way that several different types of frames can be assembled. Pins are inserted into bone, and then clamps are assembled to the pins. Bars are assembled to the clamps and a frame is constructed. After reducing the fracture, all clamps are tightened to hold the frame in place.
The provided document describes a 510(k) premarket notification for the Zimmer XtraFix® Small External Fixation System, which is a medical device, not an AI/ML device. Therefore, the questions related to AI/ML specific acceptance criteria, studies, and ground truth establishment are not applicable.
The document discusses the substantial equivalence of the XtraFix® Small External Fixation System to previously cleared predicate devices based on technological characteristics and performance data.
Here's the relevant information based on the provided text, adapted for a medical device rather than an AI system:
1. A table of acceptance criteria and the reported device performance
| Acceptance Criteria (Performance Data) | Reported Device Performance |
|---|---|
| Interconnection strength & system rigidity (per ASTM F1541-02(2007) and FDA Guidance) | Confirmed substantial equivalence to predicate devices. |
| MRI Conditional Claim: Force generated for worst component in 3T MRI | 43% the force of gravity |
| MRI Conditional Claim: Measurable torque in 3T static field | No measurable torque |
| MRI Conditional Claim: Heating for 15 minutes at a SAR of 3.1 W/kg | At most 4.7 ℃ |
| MRI Conditional Claim: Image artifact extension | Approximately 53-63mm from the device |
2. Sample size used for the test set and the data provenance
The document does not specify a "test set" in the context of an AI/ML system. Instead, it refers to non-clinical performance data obtained through characterization and evaluation.
- Sample Size: Not explicitly stated for specific tests (e.g., how many devices were tested for MRI compatibility or mechanical strength). The evaluation was conducted on the "XtraFix Small External Fixation System," implying various components and configurations were subject to testing.
- Data Provenance: The tests were conducted according to established standards (ASTM F1541-02(2007)) and FDA guidance documents. This indicates laboratory testing and analysis, not data collected from human subjects (prospective or retrospective).
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
Not applicable. This is not an AI/ML device, and ground truth, in this context, is established through standardized engineering tests, not expert consensus on medical images or diagnoses.
4. Adjudication method for the test set
Not applicable. This is not an AI/ML device. Performance is determined by meeting physical and material standards measured by equipment, not by human adjudication of results.
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 device. The study focused on the physical performance and safety characteristics of the device itself, not on human reader interpretation.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
This refers to the performance of the device itself in a standalone capacity, as its function is mechanical/structural, not diagnostic or AI-driven. The "performance data (nonclinical)" presented (interconnection strength, system rigidity, MRI compatibility) reflects the intrinsic properties and behavior of the device without human interaction once installed or during the MR environment.
7. The type of ground truth used
The "ground truth" for this device is based on:
- Engineering Standards and Specifications: Adherence to requirements outlined in ASTM F1541-02(2007) for external fixation devices.
- FDA Guidance Documents: Specific guidelines for orthopedic external fixation devices and establishing safety/compatibility of passive implants in MRI environments.
- Measured Physical Properties: Quantified measurements for force, torque, heating, and image artifact extension in MRI, compared against predefined safety thresholds.
8. The sample size for the training set
Not applicable. This is not an AI/ML device, so there is no training set in that sense.
9. How the ground truth for the training set was established
Not applicable. As there is no training set for an AI/ML system, this question is not relevant.
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