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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.

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XN CHECK BF is used for control and calibration 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:

WBC-BF (10^3/μL), RBC-BF (10^6/μL), MN# (10^3/μL), PMN# (10^3/μL), MN%, PMN%, TC-BF# (10^3/uL)

XN CHECK™ BF is an in-vitro diagnostic, two level, control. It contains the following: stabilized red blood cell component(s) and stabilized white blood cell component(s) in a preservative medium in polypropylene plastic vials with screw caps with a 3 mL fill. The vials will be packaged in (4) welled vacuum formed clamshell container with the Instructions for Use (IFU) / assay sheet. Product storage conditions are 2 - 8° C.

The provided document is a 510(k) premarket notification for a medical device called "XN CHECK BF." This device is a hematology quality control mixture, and the submission is for a new iteration of an already marketed product (K141957). The primary change in the new device is the addition of compatibility with the Sysmex XN-L analyzer.

The document does not contain the information requested regarding acceptance criteria for an AI/ML device, the study to prove it meets those criteria, sample sizes, expert involvement, or MRMC studies. This is because XN CHECK BF is a quality control material for laboratory analyzers, not an AI/ML diagnostic or image analysis device.

Therefore, I cannot extract the requested information from the provided text. The document focuses on performance testing relevant to a quality control material, such as precision and stability studies, which are different from the types of studies performed for AI/ML diagnostic tools.

To answer your request, I would need a document describing the regulatory submission for an AI/ML-driven medical device.

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

WBC-BF (10^3/μl), RBC-BF (10^6/ μl), ΜΝ# (10^3/μl), ΜΝ% (%), ΡΜΝ% (%), ΡΜΝ% (%), ΤC-ΒΓ# (10°3/μl)

XN CHECK™ BF is an in-vitro diagnostic product the following: stabilized red blood cell component(s) and stabilized white blood cell component(s) in a preservative medium. The product is packaged in polypropylene plastic vials with a 3 m fill. The vials will be packaged in (4) welled vacuum formed clamshell container with the Instructions for Use / assay sheet. The product storage conditions are at 2 - 8° C.

The provided text describes a 510(k) premarket notification for a medical device called XN CHECK™ BF. This document focuses on the substantial equivalence of the new device to a predicate device, rather than providing a detailed study design with specific acceptance criteria and performance metrics typically found for AI/ML-based medical devices or diagnostic tests.

The XN CHECK™ BF is a hematology quality control mixture for Sysmex XN series analyzers, not an AI-powered diagnostic device. Therefore, many of the questions related to AI/ML device studies (such as sample size for test/training sets, ground truth establishment, expert adjudication, MRMC studies, and standalone performance) are not applicable to this submission.

However, based on the information provided, here's a breakdown of what can be articulated regarding acceptance criteria and the study:

1. Table of Acceptance Criteria and Reported Device Performance

The document doesn't explicitly state quantitative acceptance criteria in a table format with specific thresholds (e.g., "accuracy > 90%"). Instead, the "acceptance criteria" are implied by the nature of a quality control product and its intended use, which is to demonstrate stability, reproducibility, and substantial equivalence to a predicate.

2. Sample Size Used for the Test Set and Data Provenance

The document does not specify the sample size used for the test set in terms of the number of samples or runs for the stability and precision studies. It mentions "product performance data" was collected but does not provide details on the experimental design, number of replicates, or number of lots tested.

• Data Provenance: Not explicitly stated, but the studies were conducted by Streck, Inc., implying internal company data.
• Retrospective or Prospective: Given the nature of stability and precision studies for a quality control material, they would typically be prospective studies designed and executed specifically for this submission, following predefined protocols.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

This is not applicable. The device is a hematology quality control mixture, not a diagnostic device requiring expert interpretation for "ground truth." The "ground truth" for a control material would be its manufacturing specifications and the measured values on reference instruments.

4. Adjudication Method for the Test Set

This is not applicable for a quality control product study. Adjudication methods are typically used when subjective interpretations (e.g., image reads) are involved to resolve discrepancies among experts.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

No, an MRMC study was not done. This type of study is relevant for diagnostic devices (especially those involving human readers like radiologists) to assess the impact of AI assistance on human performance. The XN CHECK™ BF is a quality control material.

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

No, a standalone performance study in the context of an "algorithm only" is not applicable. The device itself is a physical quality control material used with an analyzer, not an algorithm. The "performance" refers to the stability and reproducibility of the control material's measured parameters, not an algorithm's output.

7. The Type of Ground Truth Used

The "ground truth" for a quality control material like XN CHECK™ BF would be the expected target values and ranges for its assayed parameters, established through a rigorous manufacturing and assay process using reference methods and calibrated instruments. This is analogous to a reference standard, not ground truth derived from pathology, expert consensus, or outcomes data used for diagnostic algorithms.

8. The Sample Size for the Training Set

This is not applicable. The XN CHECK™ BF is a manufactured quality control material, not an AI/ML algorithm that requires a "training set."

9. How the Ground Truth for the Training Set Was Established

This is not applicable, as there is no "training set" for this type of device.

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

RBC(10^6/uL), HGB(g/dL), HCT(%), MCV(fL), MCH(pg), MCHC(g/dL), PLT(10^3/uL), PLT-F(10^3/uL), RDW-SD(fL), RDW-CV(%), MBC(10^3/uL), NEUT(%), LYMPH (%), MONO(%), EQ(%), BASO(%), IG(%), NEUTH(10^3/uL), LYMPH#(10^3/uL), MONO# (10^3/uL), EO#(10^3/uL), BASO#(10^3/uL), IG#(10^3/μL), IPF(%), IPF# (10^3/μL), RET%, IRF%, RET-HE(pg), NRBC#(10^3/uL), NRBC% (/100 WBC)

XN CHECK™ is an in-vitro diagnostic product that onlowing: stabilized red blood cell component(s), stablized white blood cell component(s), stablized platelet component(s), and stabilized nuclement(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 packaged in (4) welled vacuum formed clamshell ontainer with the Instructions for Use (FU) / assay sheet. Product storage conditions are 2 - 8° C.

Here's an analysis of the provided text regarding the acceptance criteria and study for the XN Check™ device:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state numerical acceptance criteria in a dedicated section. Instead, it discusses the outcomes of the studies. Based on the "Discussion of Tests and Test Results" and "Conclusions Drawn From Tests" sections, the implied acceptance criteria were related to stability and reproducibility, with the reported performance indicating these criteria were met.

Since no specific numerical thresholds are given, the table below reflects what can be inferred:

2. Sample Size Used for the Test Set and Data Provenance

The document does not specify the sample size used for the test set for any of the studies (Open-Vial Stability, Closed-Vial Stability, and Precision Performance).

The data provenance is not explicitly stated in terms of country of origin. However, the product is being submitted for FDA approval in the USA, implying studies were conducted to support this market. The studies are described as prospective in nature, as they are performed to "substantiate the product performance claims" for the device being submitted.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

The document does not mention the use of experts to establish ground truth for the test set. Given that XN CHECK is a hematology quality control mixture, the "ground truth" would likely be established through predefined assay values and analytical methods, rather than expert interpretation of patient data.

4. Adjudication Method for the Test Set

The document does not describe any adjudication method, as it does not involve expert review or interpretation that would typically require adjudication. The performance evaluation is based on analytical measurements against expected values for the control material.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

A Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not conducted, or at least not described in this document. This type of study is typically performed for diagnostic devices where human readers interpret medical images or data. XN CHECK is a quality control material, not a diagnostic device involving human interpretation.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

A standalone performance study was implicitly done. The studies mentioned (Open-Vial Stability, Closed-Vial Stability, and Precision Performance) relate to the intrinsic performance of the XN CHECK control material itself when analyzed by the Sysmex XN series analyzers. There is no human-in-the-loop component for the function of the control material.

7. Type of Ground Truth Used

The ground truth for this type of device (a quality control mixture) would be the assigned target values and acceptable ranges for each hematology parameter. These values are typically established through rigorous analytical testing and cross-validation against reference methods or previously validated control materials. The document implies these established analytical expectations as the basis for evaluating "reproducibility" and "stability."

8. Sample Size for the Training Set

The document does not specify a training set sample size. For a quality control material, the concept of a "training set" as understood in machine learning (where algorithms learn from data) does not directly apply. The manufacturing and validation process would involve extensive analytical testing during development and manufacturing, but this is not typically referred to as a "training set."

9. How the Ground Truth for the Training Set Was Established

As explained above, a "training set" in the context of machine learning is not applicable here. For the XN CHECK, the "ground truth" (i.e., the expected values and acceptable ranges for performance) would be established by:

• Manufacturing specifications: Parameters are designed to fall within specific ranges.
• Analytical testing: Extensive in-house testing under controlled conditions to determine the mean and standard deviation for each parameter.
• Methodology: Following established laboratory practices and potentially using reference instruments or methods.
• Comparison to predicate: Ensuring the new control material performs comparably to the previously accepted predicate (XN CHECK K120742).

In summary, the provided document focuses on the regulatory submission for a hematology quality control product. As such, the studies described are analytical performance studies (stability, precision) rather than diagnostic efficacy studies and therefore many of the requested elements (like experts, adjudication, MRMC, training sets for algorithms) are not directly relevant or discussed.

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

WBC-BF (103/μl), RBC-BF (10°/μl), MN# (103/μl), PMN# (103/μl), MN% (%), PMN% (%), TC-BF# (103/ul)

XN CHECK™ BF is an in-vitro diagnostic product that contains the following: stabilized red blood cell component(s) and stabilized white blood cell 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 (4) welled vacuum formed clamshell container with the product information sheet / assay sheet. The product must be stored at 2 - 8° C.

The provided document is a 510(k) summary for the Streck XN CHECK™ BF device, which is a hematology quality control mixture. It describes the device, its intended use, and compares it to a predicate device (Cell-Chex Auto-[K053362](https://510k.innolitics.com/search/K053362)). The document also includes information about the tests conducted to establish performance.

Based on the provided text, here's an analysis of the acceptance criteria and study information:

**1. Table of Acceptance Criteria and Reported Device Performance**

The document does not explicitly state quantitative acceptance criteria in a table format for performance metrics. Instead, it makes general statements about the study results. The primary "performance" assessed for this type of device (a quality control mixture) relates to its stability and consistency, and its substantial equivalence to a predicate device.

| Performance Metric          | Acceptance Criteria (Implied)                                    | Reported Device Performance                                    |
|-----------------------------|------------------------------------------------------------------|----------------------------------------------------------------|
| Open-Vial Stability         | Stability for 30 days (matching predicate device)                | "Same" as predicate (30 days)                                  |
| Closed-Vial Stability       | Stability for at least 75 days (matching predicate device)       | 84 days (exceeds predicate's 75 days)                          |
| Precision Performance       | Consistency and reproducibility                                  | "consistently reproducible"                                    |
| Substantial Equivalence     | Performance comparable to the predicate device (Cell-Chex Auto)  | "substantially equivalent to the predicate product"            |
| Safety and Effectiveness    | Device is safe and effective for its intended use                | "XN CHECK™ BF is a safe and effective product, which fulfills its intended use" |

**2. Sample Size Used for the Test Set and Data Provenance**

The document does not specify the exact sample sizes used for the Open-Vial Stability, Closed-Vial Stability, or Precision Performance tests. It simply states that "The following studies were conducted to establish performance of XN CHECK™ BF."

Data Provenance: Not explicitly stated, but these types of studies for in-vitro diagnostic controls are typically conducted internally by the manufacturer using fresh device samples, often in a laboratory setting. It is not mentioned whether the data is retrospective or prospective, but stability studies inherently involve prospective evaluation over time.

**3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts**

This information is not applicable and therefore not provided in the document. For a hematology quality control mixture, "ground truth" isn't established by human expert consensus on interpretations of images or clinical data. Instead, the "truth" is derived from the established values of the control material, measured on high-precision reference instruments or by defined methods. The stability and precision studies would involve comparing measurements over time and across different runs/lots, rather than expert interpretation.

**4. Adjudication Method for the Test Set**

Not applicable. Adjudication methods (like 2+1, 3+1) are used to resolve discrepancies in human readings or interpretations, typically in studies involving imaging or clinical diagnosis. This device is a quality control material, and its performance is assessed through quantitative laboratory measurements, not through subjective human interpretation requiring adjudication.

**5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, and 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 control, not an AI-powered diagnostic tool for human readers. Therefore, an MRMC study and a human-in-the-loop comparison with AI assistance are not relevant to its evaluation.

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

Not applicable. This device is a physical quality control material for analyzers, not a software algorithm. Therefore, "standalone algorithm performance" is not a relevant concept for this product. Its performance is inherent to its chemical and biological composition and how it performs on specific analyzers.

**7. The Type of Ground Truth Used**

The concept of "ground truth" as typically applied in AI/diagnostic imaging studies (e.g., pathology, clinical outcomes, expert consensus) does not directly apply here. For a quality control material like XN CHECK™ BF, the "ground truth" is established by:

*   **Reference Methodology:** The manufacturing process and characterization of the control material itself, which targets specific analyte concentrations (e.g., WBC-BF, RBC-BF counts).
*   **Assayed Values:** The expected range of values for each parameter (WBC-BF, RBC-BF, etc.) determined through rigorous testing on reference instruments and methods, often by the manufacturer. These assayed values serve as the "true" or target values against which the control material's performance (stability, precision) is measured when run on user instruments.
*   **Comparison to Predicate Device:** Substantial equivalence implies that the performance characteristics (including stability and precision of measurements) are comparable to an already legally marketed and accepted control material, the Cell-Chex™ Auto.

**8. The Sample Size for the Training Set**

Not applicable. This device is not an AI algorithm that requires a "training set" in the conventional machine learning sense. The "training" here would be the manufacturing process and initial characterization of the control material.

**9. How the Ground Truth for the Training Set was Established**

Not applicable, as there is no "training set" in the context of an AI algorithm. The "truth" for this control material is established through its manufacturing specifications and extensive testing to determine its assayed values and stability characteristics, often using validated laboratory methods and reference instruments.

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

RBC(108/μL), HGB(g/dL), HCT(%), MCV(fL), MCH(pg), MCHC(g/dL), PLT(103/μL), PLT-F(102/pL), RDW-SD(fL), RDW-CV(%), MPV(fL), WBC(103/pL), NEUT(%), LYMPH (%), MONO(%), EO(%), BASO(%), IG(%), NEUT#(103)µL), LYMPH#(103/pL), MONO# (10°/µL), EO#(10°/µL), BASO#(103/pL), IG#(103/pL), RET#(10°/μL), RET%, IRF%, RET-HE(pg), NRBC#(10°/μL), NRBC% (/100 WBC)

XN CHECK™ is an in-vitro diagnostic product that contains the following: stabilized red blood cell component(s), stabilized white blood cell component(s), stabilized platelet component(s), and stabilized nucleated red blood cell 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 (4) 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:

1. Table of Acceptance Criteria and Reported Device Performance

The provided text does not explicitly state numerical acceptance criteria for performance metrics (like accuracy, sensitivity, specificity, etc.) for the XN CHECK™. Instead, the performance objective was to be "consistently equivalent and effective" to the predicate product. The studies aimed to demonstrate stability (open and closed vial) and overall performance comparable to the predicate.

2. Sample Size Used for the Test Set and Data Provenance

The document does not specify the exact sample size for the test set or the data provenance (e.g., country of origin of the data, retrospective or prospective). It only states that "The following studies were conducted to establish performance of XN CHECK™" and mentions "All testing" for stability. Given the nature of a hematology control product, the "test set" would likely refer to batches of the control material tested against the predicate, rather than patient data.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

This information is not provided because this type of device (a quality control mixture) does not typically involve human expert interpretation for establishing ground truth in the same way an imaging AI diagnostic might. The ground truth for a control material is typically established through analytical methods and comparisons to a known standard or predicate device.

4. Adjudication Method for the Test Set

Not applicable for this type of device. The evaluation of a hematology control mixture relies on analytical measurements against established values and comparison to a predicate, not expert adjudication.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size

No, an MRMC comparative effectiveness study was not done. This type of study is relevant for AI-powered diagnostic tools that assist human readers (e.g., radiologists, pathologists). The XN CHECK™ is a quality control product, not a diagnostic tool that interacts with human readers in that capacity.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

The XN CHECK™ is a physical control material, not an algorithm. Therefore, the concept of "standalone (algorithm only)" performance does not apply. Its performance is assessed by how well it maintains its specified parameter values and how consistently it performs across analyzers, similar to a known reference standard.

7. The Type of Ground Truth Used

The ground truth for the XN CHECK™ would be the expected assayed values for each parameter (RBC, HGB, etc.) as determined by the manufacturer, and its performance is evaluated by demonstrating conformance to these expected values and equivalency to the predicate device. The predicate device (e-CHECK (XE)™) itself serves as a reference point for performance comparison.

8. The Sample Size for the Training Set

This product is a physical control material and not an AI algorithm, so the concept of a "training set" in the context of machine learning does not apply. Its manufacturing process and formulation are developed through R&D, and its performance is validated through testing batches of the product, not by training a model on a dataset.

9. How the Ground Truth for the Training Set Was Established

Given that this is not an AI algorithm, there is no "training set" or ground truth established in that manner. The "ground truth" for the development of such a control would involve rigorous analytical methods, characterization of its components, and extensive testing to ensure stability and accuracy across different batches and on the target analyzers.

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