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This in vitro method is intended to quantitatively measure HDL Cholesterol in human serum and plasma on the Bayer ADVIA® IMS systems. Measurements of HDL Cholesterol are used in assessing cardiovascular risk.

The Bayer ADV/A IMS Direct HDL Cholesterol (D-HDL) method is for in vitro diagnostic use to measure HDL Cholesterol in human serum and plasma. Such measurements are used in the risk assessment of cardiovascular diseases.

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Here's a breakdown of the acceptance criteria and study information for the Direct HDL Cholesterol Method for ADVIA® Modular System (IMS), based on the provided 510(k) summary:

Acceptance Criteria and Reported Device Performance

Note: The document does not explicitly state numerical "acceptance criteria" values (e.g., "CV must be < X%"). Instead, it presents the performance of the new device (ADVIA IMS) and compares it to a legally marketed predicate device (ADVIA 1650). The implicit acceptance criterion is that the new device's performance is comparable to or better than the predicate device. For the correlation study, the strong R-value, a slope near 1, and an intercept near 0, along with a low Syx, suggest good agreement. The provided table includes the performance of the predicate device (ADVIA 1650) for comparison.

Study Details

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

   • Sample Size: 100 specimens for the correlation study (serum).
   • Data Provenance: Not explicitly stated (e.g., country of origin, retrospective or prospective). However, it's typically assumed to be a controlled laboratory study conducted to support regulatory submission.

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

   • This is a quantitative assay, not an interpretive imaging or diagnostic device requiring expert consensus for ground truth. The "ground truth" is established by the comparative system (ADVIA 1650) which is a legally marketed device for the same measurement, or by a reference method which is not explicitly stated as distinct from the predicate device.

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

   • Not applicable as this is a quantitative analytical measurement, not a subjective 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 device is an in vitro diagnostic (IVD) assay for measuring a biomarker (HDL Cholesterol), not an AI-powered diagnostic imaging tool or a system involving human interpretation.

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

   • Yes, this is a standalone device performance study. The measurements are performed by the ADVIA IMS system without human interpretive input for the result generation. Human operators would load samples and review results, but the analytical measurement itself is automated.

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

   • The "ground truth" for the correlation study is the measurements obtained from the predicate device, ADVIA 1650. For an IVD, the standard method for establishing accuracy (or substantial equivalence in this context) is comparison to a legally marketed predicate device or a recognized reference method.

7. The sample size for the training set:

   • Not applicable in the context of this 510(k) submission. This device is a chemical assay, not a machine learning or AI model that requires a distinct "training set" in the computational sense. The development of the assay itself would involve optimization and calibration, but not a "training set" like an AI algorithm.

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

   • Not applicable, as there isn't a "training set" in the AI sense. The development and calibration of the assay would rely on established analytical chemistry principles and reference materials, but this distinction isn't made in the document.

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