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XN CAL PF is used for calibration and calibration verification of Sysmex XN series (XN-10, XN-20) analyzers. The assayed parameter is:

PLT-F (103/pL)

XN CAL™ PF is an in-vitro diagnostic product that contains the following: stabilized red blood cell component(s), and stabilized platelet component(s) in a preservative medium. The product is packaged in polypropylene plastic vials with screw caps containing 3 ml. The vials will be packaged in (5) welled or (1) welled vacuum formed clamshell container with the Instructions for Use / assay sheet. The product must be stored at 2 - 8° C.

Here's a breakdown of the acceptance criteria and study information based on the provided text, while noting the limitations in what can be extracted for a medical device approval that is not based on AI/ML.

Important Note: The provided document is a 510(k) summary for a hematology calibrator (XN CAL™ PF), not an AI/ML powered medical device. Therefore, many of the requested points related to AI/ML (like training sets, experts for ground truth, MRMC studies, standalone performance) are not applicable to this type of device and will not be found in the document. This device is an in-vitro diagnostic product used for instrument calibration.

Acceptance Criteria and Reported Device Performance

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't explicitly state "acceptance criteria" in a quantitative table format for performance metrics. Instead, it relies on demonstrating "substantial equivalence" to a predicate device and stability studies.

Study Details (Applicable to XN CAL™ PF)

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

• Sample Size for Test Set: The document does not specify a numerical sample size for the test sets used in the Open-Vial Stability, Closed-Vial Stability, and Precision Performance studies. It only states that "all testing showed" the results.
• Data Provenance: Not specified in the document. The studies were likely conducted internally by Streck.

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

• Not Applicable. This is a calibrator for a hematology analyzer, not a diagnostic device requiring human expert ground truth for interpretation of images or patient data. Its "ground truth" is its own verified composition and stability, and its performance is evaluated against the instrument's measurements.

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

• Not Applicable. No human adjudication is involved for this type of 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. This is not an AI/ML-powered device or one that involves human readers interpreting cases.

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

• Not Applicable. This is not an algorithm. The "performance" of the device is its ability to properly calibrate the instrument and remain stable.

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

• For this device, the "ground truth" for its performance evaluation would likely be:
  • Defined values/concentrations for the stabilized red blood cell and platelet components (for calibration accuracy).
  • Time-based measurements against predefined stability limits (for open and closed vial stability).
  • Repeatability measurements (for precision performance).
  • These are internal quality control and validation metrics, not external clinical ground truth derived from human experts or pathology.

8. The sample size for the training set:

• Not Applicable. This is not an AI/ML device that requires a "training set."

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

• Not Applicable. As there is no training set for an AI/ML model, this question is not relevant.

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