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The ABX PENTRA Urine Cal is a calibrator for use in the calibration of the quantitative method : ABX PENTRA Urinary Proteins CP on ABX PENTRA 400 clinical chemistry analyzer as specified on the vials.

The calibrator included in this submission is for use on the ABX PENTRA 400 (K052007), which is a discrete photometric benchtop clinical chemistry analyzer. The ABX PENTRA TPU Cal is a liquid calibrator based on a buffered aqueous solution, containing human serum. The assigned values of the calibrator components are given on the calibrator vials, ensuring optimal calibration of the appropriate HORIBA ABX methods on the ABX PENTRA 400 analyzer. This calibrator is provided in three vials of 3 ml.

The provided document is a 510(k) Premarket Notification for a calibrator device (ABX PENTRA TPU Cal) used with a clinical chemistry analyzer. It is not a diagnostic imaging or AI-powered device, and therefore the requested information fields related to AI performance, such as sample size for test sets (including data provenance), number of experts, adjudication methods, MRMC studies, standalone performance, and training set details, are not applicable to this type of submission.

The document primarily focuses on demonstrating that the new calibrator (ABX PENTRA TPU Cal) is substantially equivalent to a predicate calibrator (ABX PENTRA Urine Cal) for the purpose of calibrating total proteins in urine measurements on the ABX PENTRA 400 analyzer.

Here's an analysis of the provided information, addressing the applicable points:

Acceptance Criteria and Reported Device Performance

The document states that "The performance testing data conclude that the safety and effectiveness of the device are not compromised, and that they met all acceptance criteria, demonstrating that the device is substantially equivalent to the predicate device." However, no specific quantitative acceptance criteria or detailed device performance metrics (e.g., accuracy, precision values) are explicitly listed in the provided text.

The acceptance criteria for a calibrator would typically relate to its stability, assigned values, and its ability to enable accurate and precise measurements when used with the associated assay and analyzer. The document implies these were met, but does not provide the specifics.

Table of Acceptance Criteria and Reported Device Performance:

Study Details:

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

   • N/A. This is a calibrator, not an AI or diagnostic device that analyzes patient data. The "performance testing" mentioned would have involved laboratory studies on the calibrator's characteristics and its performance on the analyzer, not a test set of patient cases.

2. 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):

   • N/A. Ground truth for patient cases is not relevant for a calibrator.

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

   • N/A. Adjudication methods for diagnostic test results are not relevant for a calibrator.

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:

   • N/A. This is a calibrator, not an AI-assisted diagnostic device.

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

   • N/A. This is a physical calibrator solution, not an algorithm.

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

   • N/A. For a calibrator, "ground truth" would refer to the accurately assigned values of the analytes within the calibrator itself, established through reference methods and internal validation according to good manufacturing practices. The document states: "The assigned values of the calibrator components are given on the calibrator vials."

7. The sample size for the training set:

   • N/A. This is a calibrator, not an AI model that requires a training set.

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

   • N/A. Not applicable as there is no training set for a calibrator.

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