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CLINIQA LiniCAL™ Enzyme Calibration Verifiers Levels A - E for Beckman Coulter Synchron® Systems are assayed, liquid, quality control products which may be used to evaluate the performance of the Beckman Coulter Synchron® System for Alkaline Phosphatase, Alanine Aminotransferase, Amylase, Aspartate Aminotransferase, Cholinesterase, Creatine Kinase, Creatine Kinase MB, Lactate Dehydrogenase, Lipase, Gamma Glutamyl Tranferase, and Pancreatic Amylase at five useful concentrations.

assayed, liquid, quality control products

This is a 510(k) premarket notification for a medical device called "LiniCAL™ Enzyme Calibration Verifiers Levels A - E for Beckman Coulter Synchron® Systems". This document is a clearance letter from the FDA, not a study report or a detailed technical submission. Therefore, it does not contain the specific details required to fully answer your request regarding acceptance criteria and a study proving device performance.

However, based on the information provided, I can infer some aspects and highlight what is missing:

Missing Information: The provided document is an FDA clearance letter for a Class I device (Quality control material). Such letters generally confirm substantial equivalence to a predicate device and do not typically include detailed study designs, acceptance criteria, or performance data in the same way a premarket approval (PMA) application or a more complex 510(k) for a novel device might.

Regarding the device's performance and acceptance criteria:

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

   • Acceptance Criteria: Not explicitly stated in this document. For a quality control material like this, acceptance criteria would typically involve demonstrating that the calibrator material produces expected, consistent, and accurate results when run on the specified Beckman Coulter Synchron® Systems for the listed enzymes, within defined statistical limits (e.g., specific bias, precision, linearity, or recovery ranges). These criteria would have been established internally by CLINIQA.
   • Reported Device Performance: Not explicitly reported in this document. The FDA letter confirms the device is "substantially equivalent" to legally marketed predicate devices, implying that its performance is comparable and acceptable for its intended use. Performance data would have been submitted in the original 510(k) application, but it is not detailed here.

   Hypothetical Example (what would be expected in a detailed submission):

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

   • Sample Size: Not specified in this document.
   • Data Provenance: Not specified in this document. As a quality control material for in vitro diagnostics, the testing would likely be performed in a laboratory setting, typically with controlled samples, rather than patient data.

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

   • Not applicable / Not specified. For a calibration verifier, "ground truth" would generally be established by highly accurate reference methods or certified reference materials, not typically by expert consensus in the diagnostic sense. The "ground truth" would be the assigned value of the calibrators, likely determined through rigorous analytical testing by CLINIQA and possibly external certified labs, rather than expert judgment on individual cases.

4. Adjudication method for the test set:

   • Not applicable / Not specified. Adjudication methods like 2+1 or 3+1 are typically used in studies where human readers interpret images or clinical cases and their interpretations need to be reconciled. This is not relevant for a quality control material where performance is assessed through quantitative analytical measurements.

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:

   • No. This is a calibration verifier, not an AI-powered diagnostic tool, so an MRMC study comparing human readers with and without AI assistance is not applicable.

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

   • No. This is a physical quality control material, not a software algorithm. Its performance is evaluated intrinsically on an analyzer, not as a standalone algorithm.

7. The type of ground truth used:

   • Reference Methods/Certified Reference Materials/Assigned Values: For calibration verifiers, the ground truth is the "assigned value" of each level (A-E) for each enzyme. This value would be determined using highly accurate, traceable reference methods or against certified reference materials, ensuring the calibrators' accuracy.

8. The sample size for the training set:

   • Not applicable / Not specified. "Training set" is a concept primarily used in machine learning and AI. For a physical quality control material, there isn't a "training set" in this sense. The manufacturing process is controlled and verified, and the product is characterized, but it's not "trained."

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

   • Not applicable. As explained above, the concept of a "training set" and its "ground truth" does not apply to this type of device. The accuracy of the product itself (the calibrators) is established through analytical characterization against reference materials.

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