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Medica EasyQC Blood Gas / Electrolyte assayed controls are intended to be used to monitor and evaluate the analytical performance of instruments and analytes listed in the package insert.
For In Vitro Diagnostic Use

Medica EasyQC is a specially formulated, three-level, aqueous liquid material intended for use to monitor all analytes measured by the Medica EasyStat and Easy Blood Gas analyzers. Medica EasyQC provides a convenient method of performing periodic QC checks for laboratories selecting to measure liquid QC material as a part of their quality assurance program.
Medica EasyQC contains clinically relevant quantities of pH, PCO2, PO2, sodium, potassium, ionized calcium and chloride in three levels suitable to evaluate the measurement of the Medica EasyStat Analyzer and Medica Easy Blood Gas Analyzers.
Medica EasyQC is a non-hazardous aqueous solution containing no biological materials.

The provided 510(k) summary for Medica EasyQC Blood Gas / Electrolyte Control describes a medical device, but it does not include a study that establishes performance against acceptance criteria in the way a typical AI/ML medical device submission would. This submission is for an in-vitro diagnostic quality control material, not an AI/ML algorithm.

Therefore, many of the requested categories in your template (e.g., sample size for test set, ground truth experts, MRMC studies, standalone performance, training set size) do not apply to this type of submission.

However, I can extract the relevant information regarding the non-clinical tests and the basis for substantial equivalence.

Here's a summary tailored to the information provided in the 510(k) for Medica EasyQC:

Acceptance Criteria and Study for Medica EasyQC Blood Gas / Electrolyte Control

1. Table of Acceptance Criteria and Reported Device Performance
The K021930 submission for Medica EasyQC (a quality control solution, not an AI/ML device) does not define explicit "acceptance criteria" and "reported device performance" in the manner of an AI/ML algorithm's diagnostic accuracy. Instead, the "performance" is demonstrated through its formulation and intended use matching that of predicate devices and through non-clinical stability and precision tests.

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

• Sample Size for Test Set: Not applicable in the context of an AI/ML algorithm's diagnostic accuracy. For the non-clinical tests (stability and precision), the sample sizes for the conducted tests are not specified in this 510(k) summary.
• Data Provenance: Not specified, but likely from internal Bionostics, Inc. lab testing, given it's a quality control solution.

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)

• Not Applicable. This is a quality control material, not a diagnostic device requiring expert interpretation for ground truth. The "ground truth" for a QC material is its assayed values, established through reference methods and internal validation by the manufacturer.

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

• Not Applicable. This is for a quality control material where performance is assessed through analytical testing, not human adjudication of diagnostic findings.

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 quality control material. MRMC studies are not relevant for this device.

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

• Not Applicable. There is no algorithm for this device. Its performance is intrinsic to the chemical properties and stability of the solution.

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

• For quality control materials, the "ground truth" for the analyte values is established through the manufacturer's gravimetric, volumetric, and analytical processes using reference methods and traceable standards. The analytical results from precision and stability tests are compared against these established values.

8. The sample size for the training set

• Not Applicable. This is not an AI/ML device, so there is no training set.

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

• Not Applicable. No training set for this device.

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