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This product is to be used in a diagnostic laboratory setting, by qualified laboratory technologists, for the quantitative determination of fructosamine in human serum. The determination of fructosamine is most commonly performed for the evaluation of glycemic control in diabetes. Fructosamine values provide an indication of glucose levels over the preceding 2-3 weeks. A higher fructosamine value indicates poorer glycemic control. This reagent set is intended for in vitro diagnostic use only.

Fructosamine Reagent Set, Fructosamine Calibrator and Fructosamine Controls

This document is a 510(k) clearance letter from the FDA for a Fructosamine Reagent Set, Fructosamine Calibrator, and Fructosamine Controls. It acknowledges the substantial equivalence of the device to a legally marketed predicate device.

Crucially, this document is an FDA clearance letter and does not contain the actual study data, acceptance criteria, or performance metrics that would be submitted to the FDA as part of the 510(k) application.

Therefore, I cannot directly extract the specific information requested in your prompt based on the provided text. The letter only states that the device was found substantially equivalent to a predicate and the indications for use.

To answer your questions, I would need access to the full 510(k) submission (or at least the relevant sections detailing performance studies) that this letter refers to.

Here's what I can tell you based on the provided document, and what is missing:

1. Table of acceptance criteria and reported device performance: Not available in this document. The FDA letter grants clearance based on the determination of substantial equivalence, implying that the submitted performance data met the necessary criteria, but the criteria and results themselves are not detailed here.

2. Sample size used for the test set and the data provenance: Not available in this document. This information would be found in the performance studies submitted to the FDA.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable/available in this document. This device is an in vitro diagnostic (IVD) for quantitative determination of fructosamine. Ground truth for such devices is typically established through a reference method or known concentration standards, not expert panel consensus as might be seen for imaging or subjective diagnostic aids. The letter does not detail the methods used to establish ground truth for the performance studies.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable/available in this document. Adjudication methods are typically used in studies where subjective interpretation is involved, such as medical imaging. For a quantitative IVD, the "ground truth" samples would have known reference values, not adjudicated interpretations.

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 an in vitro diagnostic reagent set, not an AI-assisted diagnostic tool or an imaging device requiring human reader interpretation. No MRMC study would be performed for this type of device.

6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done: Not applicable. This is a reagent set for laboratory use, not an algorithm. Its performance is inherent to the chemical reaction and instrumentation.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc): Not explicitly stated in this document. For an IVD like this, ground truth for performance studies would typically be established using:

   • Reference methods with known accuracy and precision.
   • Certified reference materials or calibrators with accurately assigned fructosamine concentrations.
   • Clinical samples collected from patients with known glycemic status (often confirmed by other recognized methods like HbA1c or long-term glucose monitoring).

8. The sample size for the training set: Not applicable/available in this document. This device is a reagent set, not a machine learning algorithm that requires a "training set."

9. How the ground truth for the training set was established: Not applicable/available in this document. As it's not an AI/ML device, there's no "training set" in that context.

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