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XN CAL is used for the calibration and calibration verification of Sysmex XN series (XN-10, XN-11, XN-20, XN-21, XN-L) analyzers. Assayed parameters include:

WBC (10^3/μL), RBC (10^6/μL), HGB (g/dL), HCT (%), PLT (10^3/ μL), and RET (%)

XN CAL 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 medical device in question is the XN CAL, a calibrator for cell indices used with Sysmex XN series analyzers. The provided text, a 510(k) summary, describes its intended use, comparison to a predicate device, and results of performance testing.

Here's a breakdown of the requested information based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state "acceptance criteria" with numerical targets for each parameter. Instead, it describes general study objectives and conclusions about reproducibility and stability. The "reported device performance" is given as conclusions derived from tests.

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

The document does not specify the exact sample sizes (number of measurements, number of vials, etc.) used for the multi-site precision, single-site precision, open-vial stability, or closed-vial stability studies.

The data provenance is not explicitly stated regarding country of origin. The studies are described as "Multi-Site" and "Single-Site," suggesting they were conducted at different locations. The studies were likely prospective as they were conducted to substantiate product performance claims for the 510(k) submission.

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

This information is not provided in the document. As XN CAL is a calibrator for automated hematology analyzers, "ground truth" would typically refer to the accurately assigned values for the calibrator, which are then used to calibrate the analyzers. This process usually involves highly controlled laboratory methods rather than expert human interpretation in the way, for example, a radiograph would be interpreted.

4. Adjudication Method for the Test Set

This information is not applicable to this type of device and study. Adjudication methods like 2+1 or 3+1 are typically used in studies where human interpretation of medical images or data is involved and discrepancies need to be resolved. For a calibrator, performance is measured objectively against established reference values or reproducible results.

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

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. This type of study is relevant for diagnostic devices that involve human interpretation of results (e.g., radiology AI), not for a laboratory calibrator.

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

This question is not directly applicable in the context of XN CAL as it is a physical calibrator solution, not an algorithm. Its performance is evaluated based on its measured values and stability when run on the specified analyzers, which are themselves automated devices. The "algorithm" here would be the instrument's measurement algorithm, and the calibrator helps ensure that algorithm produces accurate results.

7. The Type of Ground Truth Used

The concept of "ground truth" for a calibrator usually refers to the assigned or reference values for the parameters (WBC, RBC, HGB, HCT, PLT, RET) within the calibrator. These values are established through rigorous, highly accurate, and often multi-replicate testing using reference methods or predicate devices, ensuring their accuracy. The document implies that the "intended use" and "consistently reproducible" nature suggest these established values serve as the ground truth.

8. The Sample Size for the Training Set

This information is not provided and is not applicable for this device. The XN CAL is a physical calibration material, not a machine learning or AI algorithm that requires a "training set" of data. The performance studies described (precision, stability) are a form of verification/validation, not model training.

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

This information is not applicable as there is no "training set" in the context of this device.

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XN CAL PF is used for the calibration and calibration verification of Sysmex XN series (XN-10, XN-11, XN-20, XN-21) analyzers. Assayed parameters include: PLT-F (10^3/ uL)

XN CAL PF contains the following: stabilized red blood cell component(s), and stabilized platelet component(s) in a preservative medium.

This document describes the XN CAL™ PF device, a calibrator for cell indices used with Sysmex XN series analyzers. The primary purpose of the submission (K141955) is to expand the compatible analyzers and extend the closed-vial stability.

Here's an analysis of the provided text in relation to acceptance criteria and study details:

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

The document does not explicitly state numerical acceptance criteria for the different studies. Instead, it states that "The resultant data set established that XN CAL PF is safe and effective for its intended use and that the product is stable for the entire product dating. The product fulfills its intended use as instructed in the Instructions for Use." and "Study results show XN CAL PF to be consistently reproducible, substantially equivalent to the predicate products, and stable for the entire product dating."

Based on the studies conducted and the claims made, the inferred performance metrics and outcomes are:

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

The document does not provide details on the specific sample sizes used for the Open-Vial Stability, Closed-Vial Stability, and Precision Performance studies. It also does not specify the country of origin of the data or whether the studies were retrospective or prospective. It only states that "Streck collected product performance data for the following 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)

This information is not applicable to this device. XN CAL™ PF is a calibrator for laboratory analyzers, not an diagnostic imaging or AI-driven decision support tool that requires expert human interpretation to establish ground truth for a test set in the traditional sense. The "truth" or reference values for a calibrator are established through manufacturing processes and validation against primary reference methods or standards, not through expert consensus on cases.

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

This information is not applicable for the same reasons as #3. Adjudication methods are typically used in clinical studies where human interpretation or diagnoses are being compared, often with an AI system. Ground truth for a laboratory calibrator is determined by its intrinsic properties and manufacturing metrology.

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

An MRMC study is not applicable to this type of device. XN CAL™ PF is a calibrator, not an AI system or software that assists human readers.

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

This concept is not applicable to XN CAL™ PF. It is a physical calibrator product, not a standalone algorithm.

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

The document does not explicitly state how the "ground truth" or reference values for the calibrator were established. However, for a calibrator, the ground truth would typically be established through:

• Manufacturer's certified reference values: The company manufactures the calibrator to specific concentrations/values (e.g., PLT-F) and validates these values using highly accurate and precise reference methods or instruments, often traceable to international standards.
• Traceability: The values are likely traceable to a recognized standard or method for cell enumeration, ensuring accuracy and consistency across different batches and against a predicate.

8. The sample size for the training set

This information is not applicable. XN CAL™ PF is a physical calibrator product; it does not involve machine learning or a "training set" in the context of AI.

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

This information is not applicable for the same reasons as #8.

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XN CAL is used for the calibration and calibration verification of Sysmex XN series (XN-10, XN-11, XN-20, XN-21) analyzers. Assayed parameters include:

WBC (10^3/uL), RBC (10^6/uL), HGB (g/dL), HCT (%), PLT (10^3/ uL), and RET (%)

XN CAL 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 provided text describes a 510(k) premarket notification for the XN-CAL™ device, a calibrator for cell indices used with Sysmex XN series analyzers. The submission aims to demonstrate substantial equivalence to a legally marketed predicate device.

Here's an analysis of the acceptance criteria and the study that proves the device meets them, based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of formal acceptance criteria with numerical targets. Instead, it discusses the outcomes of various studies to demonstrate the device's performance claims. The key performance claims evaluated are related to stability and precision.

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

The document primarily focuses on the regulatory submission and does not provide specific details regarding the sample sizes or data provenance (e.g., country of origin, retrospective/prospective) for the studies performed. It generally states that "Streck collected product performance data for the following studies: Open-Vial Stability, Closed-Vial Stability, and Precision Performance."

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

This information is not provided in the document. For a medical device calibrator, the "ground truth" would likely be established through highly controlled laboratory assays using reference methods, rather than expert interpretation of images or clinical cases.

4. Adjudication Method for the Test Set

This information is not applicable and not provided. Adjudication methods are typically relevant for studies involving human interpretation or diagnosis, which is not the primary function of a calibrator for cell indices.

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

An MRMC comparative effectiveness study was not done. This type of study is relevant for diagnostic devices that involve human interpretation (e.g., radiologists reading images) and the impact of AI on their performance. The XN-CAL™ is a calibrator, which does not involve human interpretation in the same way.

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

A standalone performance study was done. The document describes studies on "Open-Vial Stability, Closed-Vial Stability, and Precision Performance" for the XN CAL device itself. These studies assess the intrinsic performance of the calibrator, independent of human interaction during the calibration process beyond following the instructions for use. The device's performance as a calibrator is evaluated based on its ability to provide stable and precise values for the specified hematological parameters.

7. Type of Ground Truth Used

The ground truth used for evaluating a calibrator like XN-CAL™ would typically be established through:

• Reference materials/methods: Highly accurate and traceable reference materials or established laboratory methods (e.g., manual cell counts, spectrophotometric hemoglobin measurements) would serve as the "true" values against which the calibrator is manufactured and tested.
• Assayed values: The calibrator itself comes with "assayed values," which are the target values for each parameter determined through rigorous testing against reference methods.

The document implicitly refers to this by stating the product performance data "established that XN CAL is safe and effective for its intended use" and "consistently reproducible."

8. Sample Size for the Training Set

The document does not mention a "training set" because XN-CAL™ is a calibrator, not an AI/machine learning algorithm that requires training data. Its performance is based on its chemical and biological formulation and manufacturing consistency.

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

As explained above, there is no "training set" for this type of device. The "ground truth" for calibrator values would be established through meticulous laboratory analysis using established reference methods, not through a training process in the AI sense.

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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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XN CAL is used for the calibration and calibration verification of Sysmex XN series (XN-10, XN-20) analyzers. Assayed parameters include:

WBC (103/μL), RBC (108/μL), HGB (g/dL), HCT (%), PLT (103/ μL), and RET (%)

XN CAL™ 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 (5) welled or (1) welled vacuum formed clamshell container with the Instructions for Use (IFU) / assay sheet. The product must be stored at 2 - 8° C.

Here's an analysis of the provided text regarding the acceptance criteria and study for the XN CAL™ device, formatted as requested:

Acceptance Criteria and Device Performance Study

1. Table of Acceptance Criteria and Reported Device Performance

The provided 510(k) summary does not explicitly state quantitative acceptance criteria in a table format, nor does it provide specific numerical performance results for the XN CAL™ device against such criteria. Instead, it makes general claims about the device's performance relative to the predicate. The "Discussion of Tests and Test Results" section indicates that the studies demonstrated that XN CAL™ is "consistently reproducible, substantially equivalent to the predicate product and stable for the shelf life claimed."

Based on the text, the implicit acceptance criteria would be that the device:

• Is consistently reproducible. (No specific numerical reproducibility target given.)
• Is substantially equivalent to the predicate product (X-CAL™). (No specific equivalence margin or statistical criteria are provided.)
• Is stable for the claimed shelf life. This includes:
  • Open-Vial Stability: 4 hours (Claim based on "Comparison to Predicate Device" table).
  • Closed-Vial Stability: 35 days (Claim based on "Comparison to Predicate Device" table).

The reported device performance, in the absence of numerical data, is a qualitative statement: "All testing showed that XN CAL™ is consistently reproducible, substantially equivalent to the predicate product and stable for the shelf life claimed."

Table of Implicit Acceptance Criteria and Reported Performance:

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

The 510(k) summary does not specify the sample size used for the test set in the Open-Vial Stability, Closed-Vial Stability, or Precision Performance studies.

The data provenance is not explicitly stated (e.g., country of origin, retrospective/prospective). As the submitter is Streck, a US-based company, and the context is a US regulatory filing, it is highly probable the data was generated in the US or under US guidance, but this is not explicitly confirmed. The studies are described in the past tense ("were conducted"), suggesting they were completed prior to submission, but does not explicitly state if they were retrospective or prospective.

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 not provided in the document. XN CAL™ is a quality control material (calibrator) for hematology analyzers. The "ground truth" for calibrator performance is established through laboratory methods and reference standards, not by expert interpretation of patient data as might be the case for diagnostic imaging or AI devices. The parameters (WBC, RBC, HGB, HCT, PLT, RET) are quantitative measurements.

4. Adjudication Method for the Test Set

This information is not applicable and not provided. Adjudication typically refers to resolving disagreements among multiple human readers/experts. Since the "ground truth" for a calibrator is based on instrumental measurements and adherence to specifications, not expert consensus on qualitative interpretation, an adjudication method is not relevant here.

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

A MRMC comparative effectiveness study was not done. This type of study is relevant for AI-assisted diagnostic devices where human readers interpret medical cases. XN CAL™ is a calibrator, not an AI diagnostic device. Therefore, AI assistance for human readers is not a component of this device's intended use.

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

A standalone performance study was not done/is not applicable in the context of an algorithm. XN CAL™ is a physical chemical product (an in-vitro diagnostic product), not a software algorithm. Its performance is evaluated through laboratory stability and precision testing on hematology analyzers, not through an algorithm's standalone accuracy.

7. The Type of Ground Truth Used

The "ground truth" for performance of XN CAL™ would be established through a combination of:

• Reference Methods/Standard Measurements: The concentrations/values of the assayed parameters (WBC, RBC, HGB, etc.) in the calibrator material would be determined using highly accurate and precise reference methods or against established reference materials.
• Predicate Device Performance: A key aspect of the "ground truth" in this 510(k) is the performance of the legally marketed predicate device (X-CAL™), as the newer device (XN CAL™) aims to demonstrate substantial equivalence.

8. The Sample Size for the Training Set

This information is not applicable and not provided. XN CAL™ is a physical calibrator material, not a machine learning algorithm that requires a "training set."

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

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

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CELL-DYN 22 Plus Calibrator is manufactured for calibration of the CELL-DYN Emerald 22 system. Assayed parameters include: WBC (109/L), RBC (1012/L), HGB (g/dL), MCV (fL), PLT (109/L)

CELL-DYN 22 Plus Calibrator is an in-vitro diagnostic product that may contain any or all of the following: stabilized human or mammalian red blood cells, human, mammalian or simulated white blood cells and a platelet component in a preservative medium. The product is packaged in polypropylene plastic vials containing 2.5ml. The closures are polypropylene screw caps with polyethylene liners. The vials will be packaged in a four (4) welled vacuum formed clamshell container with the package insert / assay sheet. The product must be stored at 2 - 10° C.

Here's an analysis of the provided text regarding the CELL-DYN 22 Plus Calibrator, structured to answer your questions about acceptance criteria and the supporting study:

1. Table of Acceptance Criteria and Reported Device Performance

The provided text does not explicitly state numerical acceptance criteria for the CELL-DYN 22 Plus Calibrator. Instead, it describes general performance characteristics and equivalence to the predicate device. The "Acceptance Criteria" are implied by the conclusions drawn from the tests, focusing on reproducibility, substantial equivalence, and stability.

2. Sample Size 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 (Run-to-Run Reproducibility, Closed-Vial Stability, Open-Vial Stability, Calibrator Performance Verification, Calibration Equivalency).

The data provenance (country of origin, retrospective/prospective) is not explicitly stated. Given that Streck is a US-based company (Omaha, NE), it is highly probable the studies were conducted in the US. The studies appear to be prospective, laboratory-based verification and validation tests rather than clinical studies with patient data.

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

The document does not mention the involvement of experts for establishing ground truth in the context we typically associate with human interpretation of medical images or diagnostic tests. For a calibrator device, the "ground truth" would be established by reference methods or highly accurate analytical techniques within a laboratory setting, rather than expert consensus on diagnostic interpretations. Therefore, the number and qualifications of experts in this sense are not applicable or reported here.

4. Adjudication Method for the Test Set

As mentioned above, the nature of a calibrator device's validation does not typically involve adjudication methods like "2+1" or "3+1" that are used for subjective interpretations. The "truth" for a calibrator's performance is determined by quantitative measurements against established standards or predicate devices. Therefore, an adjudication method is not applicable or reported here.

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

A Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not performed. This type of study is relevant for diagnostic devices where human readers interpret output (e.g., medical images) and their performance (with or without AI assistance) is evaluated. For a hematology calibrator, this type of study is not appropriate.

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

The device itself is a calibrator, not a diagnostic algorithm. The studies conducted (Run-to-Run Reproducibility, Closed-Vial Stability, Open-Vial Stability, Calibrator Performance Verification, and Calibration Equivalency) are essentially "standalone" performance evaluations of the calibrator's inherent characteristics. The device's "performance" is its ability to consistently provide a known value for calibration, not to make a diagnosis or interpretation. Therefore, in a sense, all listed studies are standalone performance studies of the calibrator material itself.

7. Type of Ground Truth Used

The ground truth for the performance of a calibrator is established by:

• Reference materials/standards: For parameters like WBC, RBC, HGB, MCV, PLT, there are established reference methods and materials to determine the true values.
• Predicate device comparison: The study explicitly mentions "Calibration Equivalency" to the predicate device, Cal-Chex. This implies the predicate device, with its established performance, serves as a de facto "ground truth" for comparison.
• Internal laboratory validation using metrological traceability: Ensuring the calibrator's values are traceable to higher-level reference standards.

The document refers to "Calibrator Performance Verification," which would involve verifying that the calibrator produces expected values when analyzed on the target system (CELL-DYN Emerald 22).

8. Sample Size for the Training Set

The concept of a "training set" is typically associated with machine learning algorithms. The CELL-DYN 22 Plus Calibrator is a physical reference material, not an AI or algorithm. Therefore, there is no training set in the conventional sense for this device. Its values are assigned through manufacturing and analytical testing, not an algorithmic learning process.

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

As there is no training set for this calibrator device, this question is not applicable. The values assigned to the calibrator batches are determined through analytical testing and metrological principles, not through an iterative learning process with a "ground truth" dataset.

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X-Cal is used to calibrate and verify calibration of Sysmex hematology analyzers. Refer to product assay sheet.

X-Cal is a stabilized suspension of human and animal blood, in a solution containing biological salts and anti-microbial preservatives. The product is packaged in plastic vials containing 4.5 ml. The closures are polypropylene screw caps with polyethylene liners. The vials will be packaged in a five welled vacuum formed "clamshell" container. The product must be stored at 2 - 8℃.

The provided text describes a 510(k) summary for the X-Cal™ Assayed hematology calibrator. It focuses on demonstrating substantial equivalence to a predicate device and does not involve typical acceptance criteria related to diagnostic performance metrics (e.g., sensitivity, specificity, AUC) for an AI device. Instead, the "acceptance criteria" here are implicitly tied to product stability and reproducibility to show it functions similarly to the predicate.

Given the nature of the device (a calibrator) and the provided documentation (a 510(k) summary for substantial equivalence), many of the requested categories for AI/diagnostic studies are not applicable. I will address the relevant points based on the information provided and explicitly state when information is not available or not relevant to this type of device submission.

Here's an analysis based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Test Set Sample Size: Not explicitly stated. The text mentions "Three studies of X-Cal were conducted: Run to Run Reproducibility and Comparison to Whole Blood; Open Vial Stability and Closed Vial Stability." However, the number of samples, runs, or batches used in these studies is not provided in this summary.
• Data Provenance: Not explicitly stated. Given the context of a US 510(k) submission for a device manufactured by an Omaha, NE-based company (Streck), it is highly probable the testing was conducted in the USA, but no specific country of origin for the data is mentioned. The studies appear to be prospective in nature, as they involve testing the performance and stability of the newly developed X-Cal product.

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

• Not Applicable. This device is a calibrator, not an AI or diagnostic device that relies on expert interpretation of images or other data to establish a ground truth. Its performance is measured against instrument readings and stability parameters, which do not inherently require expert "ground truth" in the diagnostic sense. The "ground truth" for calibrators relates to established reference methods or certified reference materials, but these details are not provided in this summary.

4. Adjudication Method for the Test Set

• Not Applicable. As noted above, this type of device does not involve expert adjudication for its performance evaluation.

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 diagnostic device.

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

• Not Applicable. This is not an AI diagnostic device. The "standalone performance" of the calibrator would refer to its inherent physical and chemical stability and its ability to produce consistent results on hematology analyzers, which is what the "Run to Run Reproducibility" and stability studies address. It does not involve an algorithm.

7. The Type of Ground Truth Used

• For the Open Vial Stability and Closed Vial Stability studies, the "ground truth" would implicitly be the initial measured parameters of the X-Cal product at time zero, against which subsequent measurements at various time points are compared to determine degradation or change within acceptable limits.
• For the Run to Run Reproducibility study, the "ground truth" is the inherent consistency expected from a calibrator, often evaluated by parameters like Coefficient of Variation (CV) or standard deviation across multiple runs.
• For the Comparison to Whole Blood study, the "ground truth" would be the established values or behavior of whole blood samples measured by the analyzer, against which the calibrator's performance (e.g., its ability to set the calibration curve accurately to yield correct whole blood results) is evaluated.
• The comparison to the predicate device (Cal-Chex) uses the known performance characteristics of Cal-Chex as a reference point for demonstrating substantial equivalence.

Specific quantitative "ground truth" values (e.g., target values for specific parameters, acceptable CVs, or deviation limits) are not provided in the summary.

8. The Sample Size for the Training Set

• Not Applicable. This is not an AI device, so there is no concept of a "training set."

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

• Not Applicable. As there is no training set for this calibrator device.

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Cal-Chex CD Plus is intended to be used as a calibrator for the calibration of WBC, RBC, Hgb, MCV, PLT and MPV (MPV on CD4000 only) on the Abbott Cell-Dyn 3200 and 4000 hematology instruments.

Cal-Chex CD Plus is a suspension of stabilized human red blood cells, human white blood cells, and human platelets packaged in glass vials containing 3.0 mL volumes. Closures are injection molded polypropylene screw-top caps. The vials are packaged in a PVC clamshell.

The provided text describes the Cal-Chex CD Plus device, an in-vitro diagnostic calibrator for hematology instruments. Let's break down the acceptance criteria and study details based on the information provided.

1. Table of Acceptance Criteria and Reported Device Performance

The submission does not explicitly list quantitative acceptance criteria with specific thresholds (e.g., "accuracy > 95%"). Instead, the acceptance criteria are framed around performance characteristics observed in the studies, demonstrating the device's suitability as a calibrator.

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

The document does not explicitly state the sample size used for the test set in terms of the number of samples or runs. It mentions "Three studies of Cal-Chex CD Plus were conducted," but details on the number of units or measurements within these studies are not provided.

• Sample Size: Not specified quantitatively.
• Data Provenance: Not specified (e.g., country of origin). The studies were conducted by Streck Laboratories, Inc., the manufacturer. It is a retrospective analysis of internal studies.

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

This information is not provided. For a calibrator, "ground truth" would typically refer to established reference values or methods for calibration. The document states the device was compared to "whole blood calibration methods," implying these methods served as a reference, but does not detail the process or expert involvement in establishing these reference values.

4. Adjudication Method for the Test Set

This information is not applicable and therefore not provided. Adjudication methods (like 2+1, 3+1) are typically used for subjective assessments where multiple experts might disagree on an interpretation, often in imaging or clinical diagnosis. For a quantitative calibrator, the assessment is based on measurements against a reference.

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

This information is not applicable and therefore not provided. MRMC studies and the concept of "human readers improve with AI" are relevant for devices involving human interpretation of data, often in the context of AI-assisted diagnostics. Cal-Chex CD Plus is a calibrator for automated hematology instruments, not a device that assists human readers in interpreting data.

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

This concept is not directly applicable in the same way it would be for an AI algorithm. Cal-Chex CD Plus is the device (a physical calibrator), and its performance is its "standalone" performance when used with the specified hematology instruments. The studies evaluate the performance of the calibrator itself.

7. The Type of Ground Truth Used

The ground truth used for comparison was "whole blood calibration methods." This implies using fresh patient samples calibrated through established and presumably validated laboratory procedures as the reference standard against which the performance of Cal-Chex CD Plus was assessed.

8. The Sample Size for the Training Set

This information is not provided. For a physical calibrator, the concept of a "training set" as understood in machine learning is not directly applicable. The formulation and initial testing of the product would involve extensive internal R&D, but this is not typically framed as a distinct "training set" in the context of device validation for regulatory submission.

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

This information is not applicable in the typical machine learning sense. The "ground truth" for developing the calibrator (its formulation, stability, etc.) would have been established through a combination of scientific principles, laboratory development, and comparison to existing validated calibration methods for hematology parameters.

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CDS LTX-Control Latex Particle Suspension is intended to serve as a calibration standard for the d.c. impedance, r.f. impedance and optical light scatter parameters of the VCS module of Coulter® Models STKS, MAXM and Gen.S Hematology Analyzer systems. Models STKS and MAXM analyzers equipped with 5-part differential capability only require aspiration of the CDS LTX-Control Latex Particle Suspension through the secondary mode aspiration inlet with the analyzer set to function F5S. STKS and Gen. S analyzers equipped with 5-part differential and reticulocyte capability require aspiration of the CDS LTX-Control Latex Particle Suspension through the secondary mode aspiration inlet with the analyzer set to function F57.

The CDS LTX-Control for red cell, white cell, and platelet counting is a device that resembles red cells, white cells, and platelets, and is used to validate the electronic calibration of the volume, conductivity and light scatter parameters on Coulter® MAXM®, STKS® and GEN.S® instruments intended to count red cells, whire cells, and platelets. It is a suspension of uniform particles whose shape, size, and concentration and other characteristics have been precisely and accurately determined.

CDS LTX-Control is supplied as ready-to-use latex particles in a buffered suspension fluid. The particles pass through the flow cell producing characteristic electrical signals that are measured as volume, conductivity and light scatter for quality monitoring of the previously mentioned COULTER instruments.

Matrix base - aqueous, buffered, bacteriostatic and fungistatic medium containing a surfactant.

Constituents - alkali metal salts, detergents, antimicrobial materials and polymer beads of known size.

The document describes the CDS LTX-Control, a latex particle suspension used as a calibrator for hematology analyzers (Coulter MAXM, STKS, and GEN.S). It aims to validate the electronic calibration of volume, conductivity, and light scatter parameters.

Here's an analysis of the acceptance criteria and the study that proves the device meets them:

1. Table of Acceptance Criteria and Reported Device Performance:

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

• Test Set Sample Size: For stability testing and value assignment, 31 cycles are performed repeatedly for the LTX-Control. The first cycle is discarded, and the mean is calculated from the remaining 30 replicates.
  • For the NIST-traceable primary particle standard, it is assayed 11 times, with the first value discarded, and the remaining 10 values used to calculate a mean.
  • For validation of the analyzer system with commercial controls, at least three levels of commercial control materials are assayed for three cycles each.
  • For comparison with normal human blood, "normal human blood specimens" are used, but a specific number / sample size is not stated beyond "mean average of the normal sample results."
  • Data tables (Tables I and II) are presented for two lot numbers of CDS LTX-Control.
  • Table 100 shows the analysis of the NIST-traceable primary particle standard.
• Data Provenance: The document does not explicitly state the country of origin of the data. Given the address of the manufacturer (Clinical Diagnostic Solutions, Inc. in Plantation, FL, USA) and the FDA 510(k) submission, it is highly likely the data was generated in the United States. The stability studies refer to "pilot production material." The studies appear to be prospective as they involve specific testing protocols for stability, value assignment, and comparison studies.

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

• The document does not explicitly mention the use of human experts or radiologists to establish ground truth for the test set.
• The ground truth for the CDS LTX-Control is established through comparison with:
  • Previous values from the same lot (for stability).
  • Reference values assigned by the manufacturer for commercial control materials.
  • A NIST-traceable primary particle standard.
  • Mean averages derived from normal human blood specimens.
  • This implies an objective, quantitative ground truth based on established measurement standards and existing commercial controls, rather than subjective expert consensus.

4. Adjudication Method for the Test Set:

• No human adjudication method (e.g., 2+1, 3+1) is described.
• The determination of acceptance is based on pre-defined quantitative criteria (e.g., ±3% deviation, ±10% deviation) and statistical calculations (mean, standard deviation, coefficient of variation, t-test). If an instrument malfunction affects results, recalibration to known standards is used to correct values.

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

• No, an MRMC comparative effectiveness study was not done. This device is a calibrator for automated hematology analyzers, not an AI diagnostic tool used by human readers. Therefore, the concept of human readers improving with or without AI assistance is not applicable.

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

• Yes, the studies described are essentially standalone performance evaluations of the CDS LTX-Control itself and its ability to calibrate the specified automated hematology analyzers. The device is a physical standard, and its performance (e.g., consistency, accuracy relative to other standards) is assessed directly through repetitive measurements on the target analyzers. There is no "human-in-the-loop" directly interacting with the calibrator's output in a diagnostic capacity; rather, the calibrator ensures the instrument's algorithm/measurement system is working correctly.

7. Type of Ground Truth Used:

• The ground truth used is primarily objective, quantitative, and traceable to established standards:
  • Manufacturer-assigned reference values for commercial control materials.
  • NIST-traceable primary particle standards (for transferring known particle sizes).
  • Statistical averages/means derived from a large number of replicates and normal human blood specimens, serving as a baseline for expected performance.
  • Instrument calibration standards.

8. Sample Size for the Training Set:

• The document describes a calibration and quality control product, not a machine learning algorithm. Therefore, the concept of a "training set" in the context of AI/ML is not applicable. The device itself is a "standard" or "control" that is used to calibrate or train other instruments, rather than being "trained" itself.

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

• As the concept of a "training set" in the AI/ML sense is not applicable, the ground truth for an AI training set was not established.
• Instead, the "ground truth" for the CDS LTX-Control's assigned values is established through rigorous comparative studies as outlined in point 7, involving traceability to NIST standards, comparisons with commercial controls, and assessment against normal human blood values on properly calibrated instruments.

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