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510(k) Data Aggregation
(68 days)
XMCP, HALLUX, TARSX, EXTREMITY MEDICAL SCREW SYSTEM
The Extremity Medical Screw System is intended for fixation arthrodesis of the metatarsal-cuneiform, navicular-cuneiform, metatarsal-cuboid, Talonavicular, calcaneocuboid, metatarsal-phalangeal, and metacarpal-phalangeal joints.
The EXTREMITY MEDICAL Screw System
The provided text describes a 510(k) submission for the EXTREMITY MEDICAL Screw System. This is a medical device, and the submission focuses on demonstrating substantial equivalence to predicate devices, rather than establishing acceptance criteria and conducting a study to prove performance against those criteria in the way a diagnostic AI/ML device would.
Therefore, many of the requested categories (e.g., sample size for test set, number of experts, adjudication method, MRMC study, training set, ground truth) are not applicable to this type of device and submission.
Here's the information that can be extracted or deduced from the provided text:
1. A table of acceptance criteria and the reported device performance
| Acceptance Criteria (Implied) | Reported Device Performance |
|---|---|
| Mechanical Equivalence: Comparable pull-out strength and torque to predicate devices. | Bench testing (pull-out strength and torque) was performed and compared to predicate devices. |
| Surgical Technique Verification: Demonstrated suitability through clinical simulation. | Clinical simulations in cadavers were performed to verify the surgical technique. |
| Material Equivalence: Made of similar materials to predicate devices. | Stated: "are made of similar materials" to predicate devices. |
| Design Equivalence: Similar design to predicate devices. | Stated: "have a similar design" to predicate devices. |
| Indications for Use Equivalence: Same indications as predicate devices. | Stated: "have the same indications for use" as predicate devices. |
| Overall Substantial Equivalence: To predicate devices. | "The EXTREMITY MEDICAL Screw System is substantially equivalent to its predicate devices. This conclusion is based upon indications for use, materials, design, test data and principles of operation." |
2. Sample sized used for the test set and the data provenance
- Sample Size for Test Set: Not applicable. The "tests" here are bench tests and cadaveric simulations, not clinical trials with human subjects.
- Data Provenance: Not applicable in the context of clinical data provenance. The bench testing and cadaveric simulations would have been performed in a lab setting by the manufacturer.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
Not applicable. This device is not a diagnostic tool that requires ground truth establishment by experts in the same way an AI/ML device would. The "ground truth" for mechanical properties would be derived from engineering standards and measurements, and for surgical technique from established surgical practices.
4. Adjudication method for the test set
Not applicable. There was no "test set" in the sense of patient data requiring expert 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
Not applicable. This is not an AI/ML device, and no MRMC study was conducted.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Not applicable. This is a physical medical device (screw system), not an algorithm.
7. The type of ground truth used
For Bench Testing (pull-out strength and torque): The "ground truth" would be the measured physical properties of the predicate devices based on established engineering test methods and standards.
For Clinical Simulations in Cadavers: The "ground truth" would be the expert assessment of the surgical technique's feasibility and success in relation to the intended use, likely by orthopedic surgeons.
8. The sample size for the training set
Not applicable. This is not an AI/ML device.
9. How the ground truth for the training set was established
Not applicable. This is not an AI/ML device.
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