Search Results

• 1. • Cementing crowns
• 2. • Cementing bridges
• • Cementing inlays 3)
• • Cementing orthodontic appliances 4)

Glass Ionomer (Polyalkenoate) Luting Dental Cement (Powder/Liquid Kit and Injectable Capsules)

The provided text is a 510(k) clearance letter from the FDA for a dental cement product called "GlasIonomer Cement CX Plus™". This document grants market clearance based on substantial equivalence to a predicate device, rather than providing data from a new clinical study with specific acceptance criteria and performance metrics typically seen for AI/ML medical devices.

Therefore, the requested information elements (acceptance criteria table, sample sizes, expert qualifications, adjudication, MRMC studies, standalone performance, ground truth types, and training set details) are not present in this document because the device is a conventional dental material and not an AI/ML diagnostic tool.

The letter explicitly states:
"We have reviewed your Section 510(k) notification of intent to market the device referenced above and we have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices..."

This means the device's safety and effectiveness were established by demonstrating its similarity to an already approved device, not by conducting a new performance study that would generate the kind of data you are asking for.

However, I can extract the following relevant information:

Device Description:

• Trade Name: GlasIonomer Cement CX Plus™
• Regulatory Class: II
• Product Code: EMA
• Type of Device: Glass Ionomer (Polyalkenoate) Luting Dental Cement (Powder/Liquid Kit and Injectable Capsules)

Indications for Use:

• Cementing crowns
• Cementing bridges
• Cementing inlays
• Cementing orthodontic appliances

Study Information Not Applicable:

Since this is a 510(k) clearance based on substantial equivalence for a dental cement, a "study that proves the device meets the acceptance criteria" in the context of AI/ML performance metrics (like sensitivity, specificity, F1 score, etc.) is not provided or typically required for this type of device. There is no information regarding sample sizes, data provenance, expert qualifications, ground truth, or MRMC studies for performance evaluation in this document.

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