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The Liquid Assayed Chemistry Control Premium Plus Levels 1, 2 and 3 are assayed quality control materials intended for in vitro diagnostic use in the quality control of diagnostic assays. This material can be used to monitor the accuracy or reproducibility of analytes listed in the package insert. This device is for prescription use only.

The Liquid Assayed Chemistry Control Premium Plus is human liquid sera to which purified biochemical material, chemicals, drugs, preservatives and stabilizers have been added. The material is supplied at levels 1, 2 and 3. Each 5 ml vial of liquid serum is stored at -20°C to -70°C. Each level is supplied in a 12 by 5ml vials.

I am sorry, but the provided text does not contain information about acceptance criteria or a study proving that a device meets those criteria.

The document is a 510(k) premarket notification for a medical device called "Liquid Assayed Chemistry Control Premium Plus Level 1, 2 and 3". It describes the device, its intended use, compares it to a predicate device, and includes summaries of stability studies (thawed open vial stability and shelf-life study) and value assignment.

Here's what I can extract, focusing on "acceptance criteria" as applied in the context of the control material stability studies:

1. Table of Acceptance Criteria and Reported Device Performance

Important Note: The document states that "All acceptance criteria were met for all the analytes" for both stability studies, but it does not explicitly list the specific numerical or qualitative acceptance criteria themselves. It only mentions that the percentage deviation was calculated for the shelf-life study.

Regarding the other requested information, there is no data in the provided text:

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 specify the sample size for the stability studies or value assignment process.
• It does not mention the country of origin of the data or whether the studies were retrospective or prospective.

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 as the device is a quality control material, not an AI or diagnostic imaging device that requires interpretation by experts for ground truth establishment in a test set.
• For value assignment, it mentions "a number of external laboratories" and "in-house testing," but does not specify the number or qualifications of personnel involved.

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

• This information is not applicable. Adjudication methods are typically used in studies involving human interpretation or subjective data, which is not the primary focus of testing a quality control material.

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. The device is a quality control material, not an AI-assisted diagnostic tool.

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

• This information is not applicable. The device is a quality control material, not an algorithm.

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

• For the stability studies, the "ground truth" or reference is assumed to be the established values or expected performance of the control material under specific conditions, compared to its performance over time. The document mentions "statistical analysis including the mean, SD and % CV were calculated" and that "an assigned value is calculated from the target mean specific value." This implies a reference standard derived from analytical measurements rather than expert consensus or pathology.

8. The sample size for the training set

• This information is not applicable as the device is a quality control material, not an AI model requiring a training set.

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

• This information is not applicable.

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