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The AUTION MAX AX-4030 Urinalysis System (AUTION MAX) is an automated urine analyzer intended for the in vitro measurement of the following analytes: glucose, protein, bilirubin, urobilinogen, pH, blood, ketones, nitrite, leukocytes, specific gravity, turbidity, and color. The AUTION MAX is intended for use only with AUTION Sticks 9EB multi-parameter test strips.

The AX-4030 device is composed of one main unit. A power cord provides the necessary electricity to run both the device and all of its components. The device is powered by the power cord which, itself, provides 100-200/200-240VAC with a frequency of 50-60Hz. The front of the main unit includes the LCD display screen and operator panel (top-center). In addition, there are several other features located along the bottom of the device including loading and u unloading sides for urine samples. One of the best features that the AX-4030 includes is a builtin printer that is located on top of the device.

Here's a summary of the acceptance criteria and study information for the AUTION MAX AX-4030 Urinalysis System, extracted from the provided text.

The provided document is a 510(k) summary for the AUTION MAX AX-4030 Urinalysis System. This type of document focuses on demonstrating substantial equivalence to a predicate device rather than presenting detailed clinical study results and acceptance criteria in the same way a typical medical device study report might. Therefore, some of the requested information (like specific acceptance criteria values, detailed study designs, and expert qualifications/adjudication) is not explicitly present in this regulatory filing.

However, based on the information provided:

1. Table of Acceptance Criteria and Reported Device Performance

Specific numerical acceptance criteria for each analyte are not explicitly detailed in this 510(k) summary. The document states "Non-clinical verification and validation testing was conducted on the AX-4030 device and the results of such testing appear in Section 18 of this submission." This indicates that detailed performance data exists, but it is not included in the publicly available summary provided.

For a device like this, acceptance criteria would typically be defined for parameters such as:

• Accuracy/Correlation: Comparison of results to a reference method or predicate device results (e.g., % agreement, correlation coefficient).
• Precision/Reproducibility: Repeatability and intermediate precision (e.g., coefficient of variation within acceptable limits).
• Limit of Detection (LoD) / Limit of Quantitation (LoQ): The lowest concentration at which an analyte can be reliably detected/quantified.
• Interference: Performance in the presence of common interferents in urine.
• Carryover: Ensuring no significant contamination between samples.

Since these specific values are not in the provided text, a table cannot be fully constructed. The summary states that the results of non-clinical testing "appear in Section 18," indicating that the device met whatever acceptance criteria were established for those tests to support its substantial equivalence claim.

2. Sample Size for the Test Set and Data Provenance

• Sample Size for Test Set: Not specified in the provided 510(k) summary. The document mentions "Non-clinical verification and validation testing," but does not detail the sample sizes used for this testing.
• Data Provenance: Not specified in terms of country of origin for the test data, nor whether it was retrospective or prospective. It is implied to be internal verification and validation conducted by ARKRAY, Inc., likely involving various urine samples.

3. Number of Experts Used to Establish Ground Truth and Their Qualifications

Not applicable/provided. For an automated urinalysis system measuring defined analytes, "ground truth" is typically established by reference methods or validated laboratory techniques, not by human expert interpretation in the same way an imaging study would.

4. Adjudication Method for the Test Set

Not applicable/provided. Adjudication methods are typically relevant for studies involving human interpretation or subjective assessments, which is not the primary mode of operation for this automated system.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No. An MRMC study is not relevant for an automated urinalysis system like the AX-4030, which performs objective measurements of chemical analytes. This type of study is typically used for imaging diagnostics where human readers interpret images, often with and without AI assistance, to assess diagnostic performance.

6. If a Standalone Study (Algorithm Only Without Human-in-the-Loop Performance) Was Done

Yes, implicitly. The "Non-clinical verification and validation testing" described in the document as appearing in "Section 18" would constitute standalone performance testing of the device (its algorithms and hardware) without human intervention in the analysis process itself. The device is described as an "automated urine analyzer."

7. The Type of Ground Truth Used

The ground truth for an automated urinalysis system is typically established by:

• Reference Laboratory Methods: Gold standard chemical assays for each analyte (e.g., enzymatic methods for glucose, turbidimetric methods for protein).
• Gravimetric methods for specific gravity, etc.
• Microscopic examination for correlation with certain parameters (e.g., blood, leukocytes, though the AX-4030 measures these chemically).
• Predicate Device Comparison: Often, a key component of a 510(k) submission is demonstrating performance equivalent to a legally marketed predicate device.

The specific ground truth methods are not detailed in this summary but would be found in Section 18 of the original submission.

8. The Sample Size for the Training Set

Not specified. The 510(k) summary does not provide details about a training set, as this document focuses on the performance validation rather than the development of the algorithm itself. For a device that measures analytes using test strips, the "training" would primarily relate to calibration and ensuring the spectrophotometric readings accurately correlate with analyte concentrations, rather than machine learning training in the contemporary sense.

9. How the Ground Truth for the Training Set Was Established

Not specified. As mentioned above, the concept of a "training set" with established ground truth is less directly applicable in the sense of a machine learning model for image interpretation. For a chemical analyzer, ground truth for calibration and initial validation would involve using precisely prepared calibrators, controls, and known concentration samples analyzed by reference methods.

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