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The Elecsys hGH CalSet is used for calibrating the quantitative Elecsys hGH assay on the Elecsys and cobas e immunoassay analyzers.

The Elecsys hGH CalCheck 5 is an assayed control for use in calibration verification and for use in the verification of the assay range established by the Elecsys hGH reagent on the indicated Elecsys and cobas e immunoassay analyzers.

The Elecsys hGH CalSet and hGH CalCheck 5 are lyophilized products consisting of human growth hormone (hGH) in human serum matrix. During manufacture, the analyte is spiked into the matrix at the desired concentration levels.

The provided 510(k) summary (K103221) for the "Elecsys hGH CalSet" and "Elecsys hGH CalCheck 5" focuses on demonstrating substantial equivalence to predicate devices, rather than establishing specific performance acceptance criteria for the devices themselves. These devices are calibrators and quality control materials, not diagnostic tools that produce a diagnostic result or image. Therefore, the information typically requested for AI/diagnostic devices regarding sample size, expert review, ground truth, and MRMC studies is not directly applicable to this submission.

However, based on the document, here's a description of what is presented regarding performance and equivalence:

Acceptance Criteria and Reported Device Performance

The submission does not explicitly list quantitative acceptance criteria in terms of sensitivity, specificity, accuracy, or similar metrics typically associated with AI diagnostic devices. Instead, it demonstrates substantial equivalence to predicate devices (Elecsys C-Peptide CalSet and Elecsys C-Peptide CalCheck 5) based on shared characteristics and equivalent performance evaluations. The performance evaluations described are "value assignment" and "stability."

The "acceptance criteria" here implicitly refer to demonstrating similar intended use, analytical characteristics, and comparable stability and value assignment performance to the predicate devices.

Study Information (Not applicable in the context of an AI/diagnostic device)

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

• Not applicable. This is a premarket notification for calibrators and controls, not a diagnostic device with a clinical test set. The "test set" would refer to the experiments conducted for value assignment and stability. The number of samples/replicates used in these analytical studies is not specified in the summary.

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. Ground truth, in the context of diagnostic devices, refers to the definitive diagnosis or condition. For calibrators and controls, the "truth" is their assigned value and stability, which are determined through analytical testing procedures and validated methods, not expert consensus on clinical cases.

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

• Not applicable. Adjudication methods are for reconciling discrepancies among human readers of diagnostic images/results. This device is a calibrator/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

• Not applicable. This is not an AI diagnostic device, nor does it assist human readers in interpreting results.

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

• Not applicable. This is not an algorithm or AI system.

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

• For calibrators and controls, the "ground truth" relates to the assigned concentration values and stability characteristics. This is established through rigorous analytical methods, often traceable to reference materials and International Standards, rather than clinical 'ground truth' such as pathology or outcomes data. The summary states "value assignment" and "stability" were evaluated, implying these analytical parameters serve as the basis for performance.

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.

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