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The Audit™ MicroCVTM D-Dimer Linearity Set is a quantitative, assayed quality control material consisting of five levels of D-dimer analyte. The five D-dimer levels demonstrate a linear relationship to each other for D-dimer analyte. The Audit TM MicroCVTM D-Dimer Linearity Set is intended to use with the Biomerieux miniVIDAS® analyzer and VIDAS® Ddimer assay to verify the calibration of the measuring range. Audit TM MicroCV™ D-Dimer Linearity Set is "For In Vitro Diagnostic Use Only."

The Audit™ MicroCV™ D-Dimer Linearity Set is a human based, Iyophilized, five level set of QC material, with each level containing D-Dimer complex. It is used to confirm the proper calibration, linear operating range, and reportable range of D-Dimer complex, Level A is near the lower limit level and Level E has concentrations near the upper limit of instruments. Levels B - D are related by linear dilution of Level A and Level E.

The provided text does NOT describe specific acceptance criteria and a study proving the device meets them in the typical sense of diagnostic accuracy or clinical performance.

Instead, the document is a 510(k) summary for a linearity set (Audit™ MicroCV™ D-Dimer Linearity Set), which is a quality control material intended to verify the calibration and linear operating range of an instrument (Biomerieux miniVIDAS® analyzer) for a D-Dimer assay. It is not a diagnostic device that directly measures a patient's condition.

Therefore, many of the requested categories (like sample size for test set, number of experts for ground truth, MRMC study, standalone performance) are not applicable to this type of device and submission.

Here's an analysis based on the provided content:

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

The document does not explicitly state numerical acceptance criteria in terms of linearity. Instead, it describes its intended function: "The five D-dimer levels demonstrate a linear relationship to each other for D-dimer analyte." The performance reported is primarily related to stability.

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

This information is not provided. For a linearity set, the "test set" would typically refer to the samples used to demonstrate linearity on the target instrument. The document mentions "All supporting data is retained on file at Aalto Scientific, Ltd." but does not elaborate on the sample sizes or provenance of these internal studies.

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. This device is a quality control material, not a diagnostic tool requiring expert interpretation of results. The "ground truth" for a linearity set would be the expected concentrations of D-Dimer in each level, established during manufacturing and characterized against a reference method.

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

Not applicable.

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 device is not an AI diagnostic tool and does not involve human readers in the context of comparative effectiveness for clinical diagnosis.

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

Not applicable. This is a physical linearity set, not an algorithm.

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

For the linearity set itself, the "ground truth" would be the assigned D-Dimer concentration values for each of the five levels, which are pre-determined during manufacturing and characterization rather than being derived from clinical ground truth like pathology or expert consensus. These values are then used to verify the linearity of an instrument's measuring range.

8. The sample size for the training set

Not applicable. This device is not a machine learning or AI algorithm, so there is no "training set."

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

Not applicable.

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