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The Hybrid Anterior Cervical Plate System is indicated for stabilization of the cervical spine from C2 to C7 employing unicortical screw fixation at the anterior face of the vertebral bodies. Specific clinical indications for anterior plating include: instability caused by trauma; instability associated with correction of cervical lordosis and kyphosis deformity; instability associated with pseudoarthosis as a result of previously failed cervical spine surgery; instability associated with major reconstructive surgery for primary tumors or metastatic malignant tumors of the cervical spine; instability associated with single or multiple level corpectomy in advanced degenerative disc disease, spinal canal stenosis and cervical myleopathy.

The Hybrid Anterior Cervical Plate System consists of an assortment of plate and screws. The Hybrid Anterior Cervical Plate System also contains Class 1 manual surgical instruments and cases that are considered exempt from premarket notification.

This is a 510(k) premarket notification for a medical device (Hybrid Anterior Cervical Plate System), not an AI/ML device. Therefore, the majority of the requested information (e.g., acceptance criteria for AI performance, sample sizes for AI training/test sets, expert adjudication, MRMC studies, standalone AI performance) is not applicable.

However, I can extract information related to the device's performance data and indications for use, which are analogous to acceptance criteria in the context of a 510(k) submission for a non-AI device.

Here's the relevant information:

1. A table of acceptance criteria and the reported device performance

For a 510(k) device like this, "acceptance criteria" are generally demonstrated through material properties, mechanical testing, and comparisons to a legally marketed predicate device to establish substantial equivalence. The document states that "Performance data were submitted to characterize the Hybrid Anterior Cervical Plate System components." This implies that the device underwent testing to ensure its mechanical integrity and functional performance.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

This information is typically not detailed in a 510(k) summary for mechanical devices, as the "test set" refers to mechanical test samples, not patient data. The document does not specify the number of test samples used for material or mechanical testing. Data provenance in the sense of patient data is not applicable here.

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 to a 510(k) submission for a mechanical device. Ground truth, in this context, would be established through engineering specifications and objective mechanical testing.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

Not applicable to a conventional mechanical device 510(k). Mechanical testing results are typically evaluated against pre-defined engineering standards.

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, as this is not an AI/ML device.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

Not applicable, as this is not an AI/ML device.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

For this mechanical device, the "ground truth" for performance would be established through:

• Engineering specifications and material standards: Ensuring the materials meet ASTM F-136 implant grade titanium alloy.
• Mechanical test results: Demonstrating the device's strength, stability, and integrity under simulated physiological conditions, showing substantial equivalence to the predicate device.

8. The sample size for the training set

Not applicable, as this is not an AI/ML device.

9. How the ground truth for the training set was established

Not applicable, as this is not an AI/ML device.

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The Reflex™ ACP System and Reflex™ Hybrid ACP System are intended for anterior intervertebral screw fixation of the cervical spine at levels C2-T1. The Reflex™ ACP System and Reflex™ Hybrid ACP System are indicated for temporary stabilization of the anterior spine during the development of cervical spine fusions in patients with the following indications: Degenerative Disc Disease (as defined by neck pain of discogenic origin with degeneration of the disc confirmed by history and radiographic studies), trauma (including fractures), tumors, deformities or curvatures (including kyphosis, lordosis or scoliosis), pseudoarthrosis, failed previous fusion, decompression of the spinal cord following total or partial cervical vertebrectomy, spondylolisthesis and spinal stenosis.

This submission is intended to expand the Reflex " ACP System product line by adding the Reflex" Hybrid ACP System, a low profile anterior cervical plate system, intendcd for unilateral fixation. Similar to its predicate device, the Reflex " Hybrid ACP System consists of bonc plates and screws, available in a variety of lengths. The components of the subject device are fabricated from Titanium alloy as described in ASTM F-136 and ISO 5832-3. The Reflex™ Hybrid ACP System will be provided non-sterile.

This is a submission for a spinal intervertebral body fixation orthosis, not an AI/ML device. Therefore, the requested information regarding acceptance criteria and studies proving device performance with respect to AI/ML metrics (like those used for diagnostic algorithms) is not applicable. The device is a physical medical implant (anterior cervical plate system), and its acceptance is based on manufacturing, material, and design similarity to a predicate device, along with mechanical testing to demonstrate substantial equivalence, rather than performance in a clinical study to detect or classify disease.

Here's why the AI/ML specific questions are not relevant in this context:

• No AI/ML Component: The provided text describes a "Reflex™ Hybrid Anterior Cervical Plate System" which is a physical implant made of titanium alloy for spinal fixation. There is no mention of any software, algorithm, or AI/ML component.
• Device Type: This is a Class II medical device (spinal intervertebral body fixation orthosis), which typically involves verification and validation through engineering testing (e.g., strength, durability, biocompatibility) and comparison to a predicate device for substantial equivalence, not through diagnostic performance studies.
• "Study that proves the device meets the acceptance criteria": For this type of device, the "study" would refer to mechanical and material testing, and comparison of design features and intended use to a legally marketed predicate device. The text explicitly states: "Testing has been conducted demonstrating substantial equivalence to the predicate device."

Therefore, I cannot provide the requested information in the format of the table or answer the specific questions about sample sizes for test/training sets, expert qualifications, adjudication methods, MRMC studies, or standalone algorithm performance, as these pertain to AI/ML product validation, which is not relevant here.

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