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The UREA UV CINETICA AA test system is intended to be used in the quantitative determination of urea in human serum and plasma. Urea measurements are used in the diagnosis and treatment of certain renal and metabolic diseases.

Kinetic method.
The device is based on the following reaction system:
Urease
Urea + H2O --------> 2 NH3 + CO2
NH3 + NADH + H+ + 2-oxoglutarate --------> I-glutamate + NAD+ + H2O

The provided text describes a 510(k) submission for a medical device, the "Wiener lab. UREA UV CINETICA AA" test system, and its substantial equivalence to a predicate device, the "DMA BUN-KINETIC, UREASE PROCEDURE test system." It outlines the device's intended use, principle, and various performance characteristics.

Here's an analysis of the acceptance criteria and study information:

Acceptance Criteria and Reported Device Performance

The document does not explicitly state "acceptance criteria" in a pass/fail sense, but rather presents a comparison of the performance characteristics of the proposed device ("WIENER LAB. Test System") against a predicate device ("DMA Test System"). The implicit acceptance criterion is that the Wiener Lab device demonstrates comparable or improved performance relative to the predicate device.

Here's a table summarizing the reported device performance compared to the predicate device:

The Wiener Lab system demonstrates:

• Improved Reagent Stability: 30 days vs. 14 days.
• Improved Linearity: Higher upper limits for both BUN and urea.
• Higher Minimum Detection Limit: This is a difference, not necessarily an improvement, and could be seen as a negative depending on the clinical context where very low urea levels need to be detected accurately.
• Improved Precision (Lower CVs): Both intra-assay and inter-assay for normal and abnormal serum controls are significantly better than the predicate device.
• Slightly different Expected Values range: The lower end for BUN is lower, and the lower end for urea is slightly higher, while the upper ends are similar.

The document concludes that the data "show substantial equivalency to the predicate device."

Study Design and Information

The provided text is a 510(k) summary, which focuses on demonstrating substantial equivalence to a legally marketed predicate device. It summarizes the key performance characteristics without detailing the specific study protocols or designs for generating these numbers. Therefore, much of the requested information about the specific study that proves the device meets the criteria (beyond the direct comparison presented) is not explicitly available in this document.

1. Sample size used for the test set and the data provenance:

   • Sample Size: Not explicitly stated for each performance characteristic. The precision data (intra-assay and inter-assay CVs) would typically involve multiple repetitions and samples, but the exact number of samples or runs is not provided.
   • Data Provenance: Not explicitly stated (e.g., country of origin, retrospective/prospective). This information would usually be detailed in the full test report, not the summary.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

   • Not Applicable. For a quantitative chemical assay like a urea test system, "ground truth" is established by the analytical measurement itself, often against certified reference materials or established methods. There are no "experts" establishing a ground truth in the sense one might find in image interpretation or diagnostic classification. The accuracy of the measurements is compared against known concentrations or a reference method.

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

   • Not Applicable. Adjudication methods are used when human interpretation of ambiguous data is involved (e.g., pathology, radiology). For a quantitative chemical assay, the result is a numerical value, and the data is typically analyzed statistically.

4. 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 a chemical diagnostic device, not an AI-assisted diagnostic imaging or interpretation device. There are no "human readers" or "AI assistance" in this context.

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

   • Not Applicable. This device is a reagent system for a chemical assay. Its performance is inherent to the chemical reactions and measurement principles. It operates "stand-alone" in the sense that its analytical results are independent of human interpretation intervention at the point of measurement, but it requires a user to perform the test.

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

   • For a chemical assay, the "ground truth" for evaluating accuracy (not directly detailed in this summary but implied by the reported linearity and minimum detection limit) would typically be:
     • Reference materials/standards: Samples with precisely known concentrations of urea.
     • Comparison to a reference method: Testing samples also analyzed by a gold standard (e.g., isotope dilution mass spectrometry) or a well-established, validated method.
   • The "expected values" provided are ranges typically found in a healthy population, not ground truth for individual test samples.

7. The sample size for the training set:

   • Not Applicable/Not Provided. This is not a machine learning or AI-based device, so the concept of a "training set" for an algorithm is not relevant. The device is a chemical reagent system.

8. How the ground truth for the training set was established:

   • Not Applicable. As above, no training set in the context of machine learning. The development and optimization of such a reagent system would involve extensive laboratory work and validation against known chemical principles and reference data.

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