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The Prealbumin SPIA™ is a quantitative turbidimetric assay intended for the detection of prealbumin levels in human serum and plasma. Measurement of prealbumin levels may aid in the assessment of an individual's nutritional status.

Raichem's Prealbumin SPIA ™ is a quantitative turbidimetric assay for the detection and measurement of prealbumin in human serum and plasma. The assay has been standardized to a CAP Reference Preparation. The assay reagents consist of a polymer diluent, a polyclonal antibody to human prealbumin, calibrators, and controls. In this assay, a complex forms between the prealbumin, and anti-prealbumin antibodies causing turbidity. The change in optical density is proportional to the amount of prealbumin present. A quantitative determination of the amount of prealbumin present in a serum/plasma sample is made by comparison to a standard curve.

Here's a breakdown of the acceptance criteria and the study that proves the device meets them, based on the provided text:

Acceptance Criteria and Device Performance

The device, Prealbumin SPIA™, is a quantitative turbidimetric assay for detecting and measuring prealbumin in human serum and plasma. Its intended use is to aid in assessing an individual's nutritional status. The primary "acceptance criteria" for this 510(k) submission are related to demonstrating substantial equivalence to an existing predicate device. This is primarily shown through performance data that confirms the proposed device's analytical precision, correlation with the predicate, and suitability for its intended use.

Here's a table summarizing the performance data presented, which serves as the fulfillment of acceptance criteria for substantial equivalence:

Study Details for Acceptance Criteria

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

• Inter-assay reproducibility: 8 different serum samples, assayed 10 times over 6 different days.
• Intra-assay reproducibility: 8 serum samples, assayed 20 consecutive times in a single run.
• Method Comparison (Predicate): 134 serum specimens.
• Method Comparison (Manual vs. Automated): 30 serum samples.
• Assay Performance with Serum and Plasma: 25 matched serum and EDTA-plasma samples.

Data Provenance: The document does not explicitly state the country of origin for the samples or if they were retrospective or prospective. Given the context of a 510(k) submission in the US, it is reasonable to assume the studies were conducted in the US, likely with a mix of patient and healthy donor samples. The phrase "serum specimens from individuals being screened for prealbumin levels and apparently healthy blood donors" suggests a mix, likely from a clinical lab setting.

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

• Not applicable in the traditional sense for this type of device. This device is an in-vitro diagnostic (IVD) for measuring a biomarker. The "ground truth" for the test set is established by the analytical measurement itself, cross-referenced against established methods or reference materials.
• For the standardization of calibrators, the College of American Pathologists (CAP) Reference Preparation for Proteins in Human Serum (Catalog Number RM002) served as the reference standard. This means an established, certified reference material sets the "ground truth" for the calibrators, not individual experts.

4. Adjudication Method for the Test Set

• Not applicable. Adjudication typically refers to expert review processes for subjective data (e.g., imaging, pathology slides). For quantitative IVD assays, the "truth" is determined by the analytical method and reference materials, not by expert consensus or review of conflicting interpretations.

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

• No, an MRMC study was not done. MRMC studies are typically used for diagnostic imaging or other subjective interpretation tasks where multiple human readers interpret cases, often with and without AI assistance, to assess the impact of AI on reader performance. This device is an automated, quantitative assay, not an assistive tool for human interpretation in that context.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

• Yes, this entire submission effectively describes standalone performance. The Prealbumin SPIA™ device is an automated or manual assay that directly produces quantitative results without requiring human interpretation for its primary function. The performance data (precision, sensitivity, correlation) are all measures of the algorithm/reagent system's intrinsic analytical capabilities. The "manual method" comparison is still about the assay's performance, not human interpretation.

7. The Type of Ground Truth Used

• Analytical Reference Standards and Comparative Methods.
  • For calibrator standardization, the ground truth was the College of American Pathologists (CAP) Reference Preparation for Proteins in Human Serum.
  • For method comparison studies, the "ground truth" was established by the predicate device (Incstar Antibody Reagent Set II for Prealbumin) or the manual method of the proposed device, to which the automated method was compared for correlation. These are accepted analytical methods rather than clinical outcomes or pathology.
  • For precision and sensitivity, the ground truth is statistical derivation from multiple measurements around known concentrations or the absence of the analyte.

8. The Sample Size for the Training Set

• The document does not explicitly mention a separate "training set" as would be typical for machine learning algorithms. This device is a reagent-based turbidimetric assay, not a machine learning model that undergoes a distinct training phase with a dedicated dataset. The development and optimization of the assay would involve internal testing and validation, but this is not usually referred to as a "training set" in the context of traditional IVD development.

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

• Not applicable. As noted above, there's no mention of a distinct "training set" in the machine learning sense. The ground truth for developing and optimizing the assay would have been established through a combination of using purified prealbumin, established reference methods, and internal quality control materials to ensure the assay reagents and protocols accurately measure prealbumin concentrations.

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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.

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