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XN CHECK is used for control and calibration verification of Sysmex XN series (XN-10, XN-11, XN-20, XN-21, XN-L) analyzers. It is not, however, intended for actual calibration of these analyzers. Assayed parameters include:

RBC(106/μL), HGB(g/dL), HCT(%), MCV(fL), MCH(pg), MCHC(g/dL), PLT(103/μL), PLT-F*(103/μL), RDW-SD(fL), RDW-CV(%), MPV(fL), WBC(103/uL), NEUT(%), LYMPH (%), MONO(%), EO(%), BASO(%), IG(%), NEUT#(103/pL), LYMPH#(103/pL), MONO# (103/pL), BASO#(103/pL), IG#(103/ μL), IPF(%), IPF# (103/pL), RET#(106/μL), RET%, IRF%, RET-HE(pg), NRBC#* (100 WBC)

*Not Available on the XN-L.

XN CHECK™ is a three level hematology control the following: stabilized red blood cell component(s), stabilized white blood cell component(s) stabilized platelet component(s), and stablic on onnonent(s) in a preservative medium. The product is packaged in polypropylene plastic vials with screw caps with a 3 mL fill. The vials will be pacum formed clamshell container with the Instructions for Use (FU) / assay sheet. Product storage conditions are 2 - 8° C.

The provided text is a 510(k) Summary for the XN CHECK™ hematology quality control mixture. It details the device's intended use, comparison to a predicate device, and conclusions from tests. However, it does not fully elaborate on the detailed acceptance criteria for each claimed parameter or explicitly describe the "study that proves the device meets the acceptance criteria" in terms of specific statistical analyses, sample sizes for test sets with ground truth, expert qualifications, or multi-reader studies.

Therefore, many of the requested details cannot be extracted directly from this document. The information provided is at a high level, focusing on demonstrating substantial equivalence to a predicate device.

Here's what can be extracted and what information is missing:

1. Table of Acceptance Criteria and Reported Device Performance:

The document states that "XN CHECK is used for control and calibration verification... and that the product is stable for the entire product dating." It also mentions "reproducible" and "stable" in the conclusions. However, it does not provide specific numerical acceptance criteria (e.g., maximum allowable coefficient of variation for precision, or specific stability limits for each parameter) nor quantified performance data for each of the numerous assayed parameters. It only describes the types of studies conducted.

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

• Sample Size for Test Set: Not explicitly stated. The document mentions "Multi-Site Precision Study" and "Single-Site Precision Study," implying multiple samples were tested, but the exact number of control vials or measurements is not provided.
• Data Provenance: Not explicitly stated (e.g., country of origin). The studies appear to be conducted by Streck, Inc.
• Retrospective or Prospective: Not explicitly stated, but clinical validation studies for a device like this are typically prospective for stability and precision.

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

• This device is a hematology quality control mixture, not an AI/imaging device requiring expert interpretation for ground truth. Therefore, this question is not applicable in the context of this document. The "ground truth" for a control material would typically be the reference values established by the manufacturer using reference methods and calibrated instruments, not expert consensus on images.

4. Adjudication method for the test set:

• Not applicable as this is a quality control mixture and not an interpretive device.

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 as this is a quality control mixture, not an AI-assisted diagnostic device.

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

• Not applicable as this is a quality control mixture, not an algorithm. Performance assessment would be based on instrument measurement against established target values.

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

• For a hematology quality control mixture, the "ground truth" (or reference values) would be established through a rigorous process of assaying the control material on validated reference instruments using established methodologies. This is typically done by the manufacturer's skilled laboratory personnel, using calibrated equipment, and adhering to strict quality control protocols. It is not expert consensus, pathology, or outcomes data in the typical sense for diagnostic devices.

8. The sample size for the training set:

• Not applicable. This device is a quality control material, not a machine learning algorithm that requires a "training set."

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

• Not applicable. As above, this device does not use a training set in the context of machine learning.

Summary of Missing Information:

The document provides a regulatory summary demonstrating substantial equivalence for a quality control device. It does not contain the detailed study protocols, specific acceptance criteria values, quantified performance results (precision, stability range for each parameter), or detailed method of "ground truth" establishment (beyond implying standard laboratory practices) that would typically be found in a full scientific validation report. The questions about experts, adjudication, MRMC, and standalone AI performance are not relevant to this type of device.

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