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510(k) Data Aggregation
(105 days)
FRAG-LOC SYSTEM
The Frag-Loc® System is intended to provide compression to bones and bone fragments for the fixation of fractures, fusions, or osteotomies.
The Frag-Loc® System consists of various sizes of screws, sleeves, and washers which are implanted from opposite ends of a bone in order to provide compression to bones and bone fragments for the fixation of fractures, fusions, or osteotomies.
Here's an analysis of the provided text regarding the Frag-Loc® System, focusing on the acceptance criteria and the study that proves the device meets them:
1. Table of Acceptance Criteria and Reported Device Performance:
Acceptance Criteria (Type of Test) | Reported Device Performance |
---|---|
Axial Pull-Out Testing | Met acceptance criteria |
4-Point Bend Testing | Met acceptance criteria |
Explanation: The documentation explicitly states that "The new Frag-Loc® System components were subjected to axial pull-out and 4-point bend testing to characterize their strength. The results demonstrate that the acceptance criteria defined in the Design Control Activities Summary were met." However, the specific numerical thresholds for these acceptance criteria (e.g., minimum pull-out force in Newtons, maximum deflection in mm under a given load for bend testing) are not provided in the given text. The text only confirms that criteria, which were defined externally in a "Design Control Activities Summary," were met.
Regarding the other requested information, the provided text contains very limited details, as this is a 510(k) summary for a mechanical orthopedic device, not an AI/software as a medical device (SaMD). Therefore, many of the requested points are not applicable or cannot be answered from the given information.
2. Sample Size Used for the Test Set and Data Provenance:
- Test Set Sample Size: The document does not specify the sample size used for the axial pull-out or 4-point bend tests.
- Data Provenance (e.g., country of origin of the data, retrospective or prospective): The document does not provide information about data provenance. This type of preclinical testing is typically conducted in a laboratory setting by the manufacturer (Acumed, LLC, located in Hillsboro, Oregon, USA).
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts:
- This question is not applicable to this type of device. The "ground truth" for mechanical testing is established by engineering specifications and material science principles, not by human expert interpretation (like a radiologist reading images).
4. Adjudication Method (e.g., 2+1, 3+1, none) for the Test Set:
- This question is not applicable to this type of device. Adjudication methods are typically used when human interpretation or clinical outcomes require consensus, which is not relevant for preclinical mechanical testing.
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 question is not applicable to this device. An MRMC study is relevant for AI-powered diagnostic devices that assist human readers (e.g., radiologists). The Frag-Loc® System is a physical orthopedic implant.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) was done:
- This question is not applicable to this device. This refers to the performance of an AI algorithm on its own. The Frag-Loc® System is a physical orthopedic implant.
7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc):
- For the preclinical testing, the "ground truth" is based on engineering specifications and scientific principles of material strength and biomechanics. The acceptance criteria would have been established based on industry standards (if applicable), predicate device characteristics, and the intended biomechanical function of the device (providing compression and fixation to bone).
8. The Sample Size for the Training Set:
- This question is not applicable to this type of device. "Training set" refers to data used to train an AI algorithm. The Frag-Loc® System is a physical orthopedic implant and does not involve AI.
9. How the Ground Truth for the Training Set Was Established:
- This question is not applicable to this type of device, as there is no "training set" for a physical implant.
In summary, the provided 510(k) summary focuses on the substantial equivalence of a physical orthopedic implant. The "study" proving device performance is limited to preclinical mechanical testing (axial pull-out and 4-point bend tests), which the device "met acceptance criteria" for. Details about specific numerical criteria or sample sizes for this testing are not included in the summary.
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