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In-vitro diagnostic reagents for the quantitative determination of immunoglobulins (IgG. IgA and IgM) in human serum, heparinized and EDTA plasma, and IgG in human urine and cerebrospinal fluid (CSF) by means of immunonephelometry on the BN II and BN ProSpec® System. Measurements of IgG aid in the diagnosis of abnormal protein metabolism and the body's lack of ability to resist infectious agents.

The N Antiserum to Human IgG reagent containing animal serum, produced by immunization of rabbits with highly purified human immunoglobulin (

The provided text describes a special 510(k) premarket notification for a modified device, "N Antisera to Human Immunoglobulins (IgG, IgA, and IgM)". The sole modification is the addition of a High Dose Hook (HDH) effect claim for IgG in cerebrospinal fluid (CSF) samples.

Here's a breakdown of the requested information based on the provided document:

1. A table of acceptance criteria and the reported device performance

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

• Sample Size: The study used a "CSF high sample pool." The exact number of individual patient samples contributing to this pool (if multiple were pooled) is not specified. However, the study involved a dilution scheme with twelve (12) individual dilution levels, including the neat sample.
• Data Provenance: Not explicitly stated. The manufacturer is Siemens Healthcare Diagnostics Products GmbH, located in Marburg, Germany, which suggests the study was likely conducted in Germany or a similar geographic region. It is implicitly a prospective study designed to evaluate the HDH effect for the modified device.

3. 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)

This section is not applicable as the device is an in-vitro diagnostic reagent for quantitative determination, not an imaging or interpretive device that would typically require expert ground truth establishment in the described manner. The "ground truth" for this type of test is the quantitatively measured concentration of IgG in a sample, established through laboratory methods and comparison to known standards.

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

This section is not applicable. Adjudication methods like 2+1 or 3+1 are typically used for establishing ground truth in interpretive studies (e.g., radiologists reviewing images). For a quantitative in-vitro diagnostic test, the "ground truth" is determined by the analytical method itself against known standards.

5. 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

This is not applicable. The device is an in-vitro diagnostic reagent, not an AI-assisted diagnostic tool or an imaging device requiring human reader interpretation. No MRMC study was performed.

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

This refers to the performance of the analytical system (N Antisera reagent on BN II System) without human intervention in the measurement process. The HDH study performed is a standalone performance evaluation of the reagent/instrument system. The acceptance criteria and performance data in the table above demonstrate this standalone performance.

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

For this in-vitro diagnostic device, the "ground truth" for the High Dose Hook study was established by creating known dilutions of a high-concentration CSF sample, which were then measured by the device. The reported concentrations for these dilutions serve as the reference. The ultimate analytical ground truth for the quantitative measurement itself is tied to international standards like ERM-DA470k/IFCC (as stated in the "Traceability/Standardization" section).

8. The sample size for the training set

This document does not describe the development or training of a machine learning model, so there is no training set in the typical sense. The "training" for such a diagnostic test involves method development, optimization, and validation using various samples and controls, but these are not referred to as a "training set" for an algorithm.

9. How the ground truth for the training set was established

As there is no training set for an algorithm, this question is not applicable.

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In vitro diagnostic reagents for the quantitative determination of immunoglobulins (IgG, IgA and IgM) in human serum, heparinized and EDTA plasma, and IgG in human urine and cerebrospinal fluid (CSF) by means of immunonephelometry on the BNTM Systems. Measurement of immunoglobulins aid in the diagnosis of abnormal protein metabolism and the body's lack of ability to resist infectious agents.

N/T Protein Control LC is intended for use as an assayed intralaboratory quality control for assessment of precision and analytical bias in immunochemical determination of the proteins IgG in CSF, IgA in CSF, IgM in CSF, IgG in urinc, transferrin in urine, albumin in urine and CSF, a1-microglobulin in urine and total protein in urine and CSF, using the BNTM Systems.

N Antisera to Human Immunoglobulins (IgG, IgA, and IgM): Proteins contained in human body fluids form immune complexes in an immunochemical reaction with specific antibodies. These complexes scatter a beam of light passed through the sample. The intensity of the scattered light is proportional to the concentration of the respective protein in the sample. The result is evaluated by comparison with a standard of known concentration.

N/T Protein Control LC: The N/T Protein Control LC is a multi-analyte, lyophilized, polygeline and rabbit albumin based product.

The provided text describes a 510(k) summary for N Antisera to Human Immunoglobulins (IgG, IgA, and IgM) and N/T Protein Control LC. However, it does not contain detailed acceptance criteria and a study proving the device meets these criteria in the format requested.

The document primarily focuses on establishing substantial equivalence to previously marketed devices based on the general operating principle, reagent composition, and a single method comparison dato point. There is no mention of a traditional "acceptance criteria" table with specific thresholds for performance metrics (such as sensitivity, specificity, accuracy) and corresponding study results to demonstrate compliance.

Therefore, many of the requested sections, such as sample size for the test set, data provenance, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance, training set details, and ground truth establishment for the training set, are not available in the provided text.

Based on the available information, here's an attempt to answer the questions:

1. A table of acceptance criteria and the reported device performance

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

• Sample Size: Not specified in the provided text.
• Data Provenance: Not specified in the provided text (e.g., country of origin, retrospective or prospective). The "Method Comparison Data" section does not provide these details.

3. 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)

Not applicable / Not provided. This is a comparison of quantitative assays, not an expert-driven diagnostic review. The "ground truth" for the method comparison appears to be the results obtained by the predicate device.

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

Not applicable / Not provided. Adjudication methods are typically relevant for expert review in image analysis or clinical diagnosis scenarios.

5. 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

Not applicable. This is a submission for in vitro diagnostic reagents and controls, not an AI-assisted diagnostic device involving human readers.

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

This refers to the performance of the device itself (the N Antisera and N/T Protein Control LC reagents/systems) as a standalone diagnostic tool. The method comparison data is effectively a standalone performance assessment of the device against a predicate, focusing on quantitative agreement. The reported correlation coefficient of 0.99 for IgG demonstrates its standalone performance relative to the predicate.

7. The type of ground truth used (expert concensus, pathology, outcomes data, etc)

The "ground truth" for the method comparison study was the measurements obtained from the legally marketed predicate device, the Beckman Coulter IMMAGE® Immunochemistry Systems Urine Immunoglobulin G (IGU) (K951635).

8. The sample size for the training set

Not applicable / Not provided. This is a traditional IVD device clearance, not an AI/machine learning device that would typically involve a separate "training set." The development of the reagents/system itself would have involved extensive R&D and calibration, but not in the context of a "training set" for an algorithm.

9. How the ground truth for the training set was established

Not applicable / Not provided for the reasons stated in point 8.

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In vitro diagnostic reagents for the quantitative determination of immunoglobulins (IgG, IgA and IgM) in human serum, heparinized and EDTA plasma as well as IgG in human cerebrospinal fluid (CSF) using the BN™ Systems. Measurements of these immunoglobulins aids in the diagnosis of abnormal protein metabolism and the body's lack of ability to resist infectious agents.

Proteins contained in human body fluids form immune complexes in an immunochemical reaction with specific antibodies. These complexes scatter a beam of light passed through the sample. The intensity of the scattered light is proportional to the concentration of the relevant protein in the sample. The result is evaluated by comparison with a standard of known concentration.

The provided information is for an In Vitro Diagnostic (IVD) device, not an AI/ML medical device. Therefore, many of the requested categories (e.g., number of experts for ground truth, adjudication methods, MRMC study, sample size for training set) are not applicable to the information contained within this 510(k) summary.

However, I can extract information related to acceptance criteria (often tied to performance characteristics) and the study details that demonstrate the device meets these criteria.

Here's an analysis of the provided text:

Acceptance Criteria and Reported Device Performance

The 510(k) summary for "N Antisera to Human Immunoglobulins (IgG, IgA, and IgM)" describes performance characteristics based on method comparison studies. While explicit "acceptance criteria" (e.g., minimum correlation coefficient or acceptable bias range) are not stated in a tabular form, the equivalency claim to a legally marketed device (K860894) implies that the new device's performance should be comparable.

The device performance is reported in terms of correlation (r) and bias (y-intercept) from method comparison studies, comparing results obtained using the modified N Antisera with results obtained using the current N Antisera (K860894). The goal is to show substantial equivalence.

Implicit Acceptance Criteria: The reported correlation coefficients (all above 0.9) and low bias values indicate good agreement between the modified device and the predicate device, suggesting the performance is acceptable for substantial equivalence. For IVDs, strong correlation and minimal bias are standard expectations for method comparison studies to demonstrate equivalency.

Study Details

1. Sample sizes used for the test set and the data provenance:

   • Test Set Sample Sizes:
     • IgG (Heparinized): 49 samples
     • IgG (EDTA): 20 samples
     • IgA (Heparinized): 49 samples
     • IgA (EDTA): 20 samples
     • IgM (Heparinized): 49 samples
     • IgM (EDTA): 20 samples
   • Data Provenance: Not explicitly stated in the provided text (e.g., country of origin, retrospective/prospective). However, for IVD performance studies, samples are typically collected from a relevant patient population and tested prospectively or retrospectively.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

   • This is an IVD device measuring immunoglobulin concentrations. The "ground truth" for such devices is typically the result obtained from a reference method or a legally marketed predicate device. No human expert interpretation is involved in establishing the "ground truth" for quantitative analyte measurement in this context. Therefore, this question is not applicable.

3. Adjudication method for the test set:

   • Not applicable as the "ground truth" is established by a quantitative assay, not by expert interpretation requiring adjudication.

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:

   • Not applicable. This is an IVD assay, not an AI/ML-driven diagnostic imaging device requiring human reader interpretation or assistance.

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

   • Yes, this is a standalone IVD assay. Its performance is evaluated independently by comparing its results to a predicate device. There is no "human-in-the-loop" component in the operational analysis of this quantitative assay.

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

   • The "ground truth" (or reference standard) is the measurement obtained from the legally marketed predicate device (K860894), also "N Antisera to Human Immunoglobulins (IgG, IgA, and IgM) assay" on the BN™ Systems. This is a comparison between two quantitative assays.

7. The sample size for the training set:

   • Not applicable. This is not an AI/ML device that requires a training set. Performance is evaluated on test samples.

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

   • Not applicable as there is no training set for this type of IVD device.

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