Search Results

The Olympus AU5400 Clinical Chemistry Analyzer is a fully automated photometric analyzer intended for clinical laboratory use. Applications include colorimetric, turbidimetric, latex agglutination, and homogeneous enzyme immunoassay.

The Olympus AU5400 Clinical Chemistry Analyzer is a fully automated photometric analyzer.

While the provided document is a 510(k) clearance letter for the Olympus AU5400 Clinical Chemistry Analyzer, it does not contain the detailed performance study results, acceptance criteria, or ground truth information typically found in the actual 510(k) submission or a scientific publication.

The letter confirms that the device has been found substantially equivalent to predicate devices, meaning it is considered safe and effective for its indicated use. However, it does not explicitly state the specific performance metrics (like sensitivity, specificity, accuracy), the thresholds for acceptance of those metrics, or the specifics of the validation study.

Therefore, I cannot populate all the requested fields from the given text. I can only infer some information based on the nature of a 510(k) submission for a clinical chemistry analyzer.

Here's what I can convey based on the provided document and general understanding of 510(k) submissions for similar devices:

1. Table of Acceptance Criteria and Reported Device Performance

• Acceptance Criteria: Not explicitly stated in the provided letter. For a clinical chemistry analyzer, acceptance criteria would typically involve demonstrating analytical performance similar to or better than a predicate device across various parameters, including:

  • Accuracy: Agreement with a reference method.
  • Precision (Reproducibility & Repeatability): Consistency of results.
  • Linearity: Accuracy across the analytical measurement range.
  • Detection Limits: Lowest concentration that can be reliably measured.
  • Interference: Lack of significant impact from common interfering substances.
  • Carry-over: Minimal contamination between samples.
  • Stability: Reagent and calibration stability.
  • Correlation: Strong correlation with predicate device or reference method.

• Reported Device Performance: Not explicitly stated in the provided letter. The 510(k) submission would have contained data supporting these performance characteristics, demonstrating that the device meets the established acceptance criteria. The FDA's clearance implies that this evidence was found satisfactory.

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size: Not specified in the provided letter. For a clinical chemistry analyzer, test sets would include a variety of patient samples (normal, abnormal) and spiked samples to assess different analytical aspects.
• Data Provenance: Not specified in the provided letter. Typically, clinical chemistry analyzer validation involves prospective collection of patient samples, often from multiple sites to ensure representativeness, as well as characterization of control materials.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications

• Experts and Qualifications: Not specified in the provided letter. For clinical chemistry analyzers, "ground truth" for analytical performance is typically established through:
  • Reference interval studies: Involving a statistically significant number of healthy individuals.
  • Comparison studies: Against a recognized reference method or a legally marketed predicate device, where the predicate device's results serve as the comparison standard.
  • Control materials and calibrators: With known, certified values.
  • Analytical experts (e.g., clinical chemists, laboratory directors) would be involved in designing and overseeing these studies, and interpreting the results.

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable in the traditional sense for analytical performance of a clinical chemistry analyzer. Adjudication methods (like 2+1, 3+1) are typically used for subjective interpretations, such as image analysis or pathology review, where expert opinion is directly establishing "ground truth." For an automated analyzer, the output is quantitative, and performance is assessed against established analytical standards or comparison methods.

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

• MRMC Study: Not applicable. MRMC studies are used to evaluate human reader performance, often with AI assistance, for tasks involving interpretation (e.g., radiology). The Olympus AU5400 is an automated clinical chemistry analyzer that produces quantitative results, not an AI-assisted diagnostic imaging tool with human interpretation.

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

• Standalone Performance: As an automated analyzer, the device's performance is inherently "standalone" in generating the quantitative results. The entire 510(k) submission would be focused on demonstrating this standalone analytical performance. However, there's no "algorithm only without human-in-the-loop" contrast needed, as the device's function is to perform the chemical analysis automatically.

7. The Type of Ground Truth Used

• Ground Truth Type: For a clinical chemistry analyzer, the "ground truth" is typically established through:
  • Reference methods: Highly accurate and validated analytical methods.
  • Certified reference materials/calibrators: Materials with known, traceable analyte concentrations.
  • Comparison to a legally marketed predicate device: Demonstrating equivalent performance to a device already on the market.
  • Pathology/Outcomes data: Would generally not be the primary "ground truth" for the analytical performance of the analyzer itself, though the results generated by the analyzer would be used in conjunction with such data for clinical decision-making.

8. The Sample Size for the Training Set

• Training Set Sample Size: Not applicable in the conventional machine learning sense. This device is a traditional analytical instrument, not a machine learning or AI model that requires a "training set" to learn its function. Its operational parameters are determined by its design, engineering tolerances, and chemical principles, not by training on a dataset.

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

• Ground Truth for Training Set: Not applicable, as there is no "training set" for a traditional clinical chemistry analyzer. The device's calibration involves using calibrator materials with known concentrations, but this is part of routine operation and quality control, not "training" in the ML sense.

Ask a specific question about this device

The IMMAGE Immunochemistry System Prealbumin (PAB) reagent, in conjunction with Beckman Calibrator 3, is intended for use in the quantitative determination of human prealbumin concentrations in human serum samples by rate nephelometry. This assay is designed for use with the Beckman IMMAGE Immunochemistry System.

The IMMAGE Immunochemistry System Prealbumin (PAB) Reagent, in coniunction with Beckman Calibrator 3, is intended for use in the quantitative determination of human prealbumin concentrations in human serum samples. The reagent kit contains one cartridge of reagent, evaporation caps and a lot specific bar code card. Calibrators and control materials are purchased separately.

Here's a breakdown of the acceptance criteria and study details for the IMMAGE™ Immunochemistry System Prealbumin (PAB) Reagent, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't explicitly state "acceptance criteria" with numerical targets for accuracy, stability, or precision. Instead, it presents performance data and implies that these results demonstrate substantial equivalence to the predicate device. Therefore, the "acceptance criteria" are inferred as aligning with the predicate's performance and generally accepted good laboratory practices for these types of assays.

2. Sample Size Used for the Test Set and Data Provenance:

• Sample Size (Method Comparison): 124 (samples)
• Data Provenance: Not explicitly stated (e.g., country of origin, prospective/retrospective). The samples were "Serum."

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications:

This information is not provided in the document. For an immunochemistry system like this, the "ground truth" for method comparison is typically established by measurements from a reference method or a predicate device. There isn't typically "expert adjudication" in the same way there would be for image-based diagnostics.

4. Adjudication Method for the Test Set:

Not applicable in the traditional sense for this type of device. The "ground truth" for comparison is the result obtained from the Beckman Immunochemistry System PAB Prealbumin Reagent (on ARRAY® System), which is the predicate device. Therefore, no expert adjudication process (like 2+1 or 3+1) is mentioned or implied.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done:

No. This is an immunochemistry assay, not an image-based diagnostic that involves human readers.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) was done:

Yes, implicitly. The device (IMMAGE Immunochemistry System Prealbumin Reagent) is an automated system for quantitative determination. Its performance is measured directly against a predicate device and through stability and precision studies. There is no "human-in-the-loop" component in the operation or interpretation of the numerical results from this system.

7. The Type of Ground Truth Used:

• Method Comparison: The "ground truth" was established by measurements obtained from the predicate device, specifically the "Beckman Prealbumin Reagent (PAB) on the ARRAY® Systems." This is a comparative measurement against an already marketed and accepted device.
• Stability/Precision: The ground truth for these studies is the inherent performance of the device under controlled conditions, demonstrating reproducible and stable results. This is established through internal testing protocols.

8. The Sample Size for the Training Set:

Not applicable/Not provided. This is a reagent and assay system, not a machine learning or AI model that requires a distinct "training set." The development of the assay itself involves optimization and validation, but not in the sense of training a discrete algorithmic model with a specific dataset.

9. How the Ground Truth for the Training Set was Established:

Not applicable. As stated above, there is no "training set" in the context of an AI/ML model for this type of device. The development and validation of the reagent and assay involve standard laboratory procedures and chemical/biological principles.

Ask a specific question about this device