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 Haptoglobin (HPT) reagent, in conjunction with Beckman Calibrator 1, is intended for use in the quantitative determination of human haptoglobin concentrations in human serum samples by rate nephelometry. This assay is designed for use with Beckman's IMMAGE Immunochemistry System.

The IMMAGE Immunochemistry System Haptoglobin (HPT) reagent, in conjunction with Beckman Calibrator 1, is intended for use in the quantitative determination of human haptoglobin concentrations in human serum samples.

Here's an analysis of the provided text, focusing on the acceptance criteria and study information for the IMMAGE™ Immunochemistry System Haptoglobin (HPT) Reagent.

Please note: The provided document is a 510(k) summary, which often focuses on demonstrating substantial equivalence to a predicate device rather than presenting de novo acceptance criteria for a novel device. As such, some information (like standalone performance targets without a comparative predicate, or extensive details on ground truth setting for complex clinical scenarios) might be less explicit or not present, as the primary goal is to show the new device performs similarly to an already-approved device.

Acceptance Criteria and Device Performance

1. Table of Acceptance Criteria and Reported Device Performance

Explanation of Implicit Criteria:
For 510(k) submissions, the acceptance criteria are largely implicit in demonstrating "substantial equivalence" to a predicate device. This means the new device needs to perform as well as, or virtually identically to, the predicate device in relevant performance characteristics. The strong correlation (r = 0.996) and slope/intercept close to 1 and 0 respectively for method comparison are key indicators of this equivalence. Similarly, the stability and imprecision data are presented without explicit numerical targets but are intended to show acceptable performance for an in vitro diagnostic.

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

• Test Set Sample Size:
  • Method Comparison: Not explicitly stated, but the summary refers to "method comparison" studies. The number of samples (e.g., patient samples) used to generate the slope, intercept, and 'r' value is not provided.
  • Imprecision:
    • For each of the three control levels, 80 results were used to calculate the mean, SD, and %CV.
• Data Provenance: Not specified (e.g., country of origin, retrospective/prospective). This type of detail is often omitted in a 510(k) summary for in vitro diagnostic devices unless there are specific clinical or demographic implications. The samples are human serum, but their origin is not described.

3. Number of Experts and Qualifications for Ground Truth

• Ground Truth Establishment: For an in vitro diagnostic (IVD) reagent like this, "ground truth" typically refers to the reference method (the predicate device in this case) or highly characterized control materials. It does not generally involve human expert interpretation in the same way as imaging or clinical decision support AI.
• Experts: Not applicable in the context of human expert review for establishing ground truth for a quantitative immunoassay.

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable. This document describes performance characteristics of a quantitative immunoassay, not a subjective diagnostic interpretation requiring adjudication among human readers.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• MRMC Study: No, an MRMC comparative effectiveness study was not done. These studies are typically relevant for AI-powered diagnostic imaging or interpretation tools where human readers are involved in the diagnostic process. This device is a reagent for a quantitative immunoassay system.
• Effect Size with AI Assistance: Not applicable, as no human readers or AI assistance in interpretation are described for this IVD.

6. Standalone Performance Study

• Standalone Performance: Yes, standalone performance was assessed for the IMMAGE HPT Reagent. The "Method Comparison Study Results" compare the IMMAGE HPT Reagent's measurements against the predicate device, effectively showing its performance in isolation (though compared to a reference). The "Estimated Within-Run Imprecision" also represents a standalone performance characteristic of the device.
  • Method Comparison: The IMMAGE HPT results were directly correlated with the predicate.
  • Imprecision: The device's internal variability was measured independently.

7. Type of Ground Truth Used

• Ground Truth Type:
  • For Method Comparison: The "ground truth" was established by the predicate device (Beckman's HPT Haptoglobin Reagent on the Array® Systems). The IMMAGE HPT Reagent's values were compared to those obtained from the predicate.
  • For Imprecision: The "ground truth" for the mean values was derived from control materials with established concentrations (Level 1, Level 2, Level 3).

8. Sample Size for the Training Set

• Training Set Sample Size: Not specified. For IVD reagents, the concept of a "training set" in the context of machine learning (where the term is most common) is generally not applicable. Reagent development involves extensive analytical validation (specificity, linearity, interference, matrix effects, etc.) rather than training an algorithm on a 'sample set'. The development process involves optimizing the chemical formulation and assay parameters based on performance against established analytical standards and reference methods.

9. How Ground Truth for the Training Set was Established

• Ground Truth for Training Set: Not applicable in the machine learning sense. The "ground truth" during the development and optimization of such a reagent would be based on:
  • Chemical principles and established analytical methods for quantitative determination of haptoglobin.
  • Reference materials and calibrators with certified or highly accurate haptoglobin concentrations.
  • Performance characteristics required for clinical utility.

Ask a specific question about this device