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Liquichek Anti-Jo-1 Control, EIA is intended for use as an unassayed quality control to monitor enzyme immunoassay procedures for the detection of Jo-1 autoantibodies.

Liquichek Anti-Jo-1 Control, EIA is prepared from human serum with added preservatives and stabilizers. This product is provided in liquid form for convenience. This product contains 0.1% sodium azide as a preservative.

The provided text is a 510(k) summary for the Bio-Rad Liquichek Anti-Jo-1 Control, EIA. It describes the device, its intended use, and claims substantial equivalence to a predicate device. However, it does not contain information about acceptance criteria or a study that proves the device meets specific acceptance criteria in the way typically expected for a performance study evaluating a new diagnostic algorithm or device's accuracy.

This document is a regulatory submission for a quality control product, not a diagnostic test with performance metrics like sensitivity, specificity, or AUC. Therefore, many of the requested categories (like sample size for test/training set, number of experts for ground truth, MRMC study, standalone performance) are not applicable or not provided in this context.

Based on the provided text, here's the information that can be extracted, with explanations for what is not present:

1. Table of acceptance criteria and the reported device performance

The document does not specify quantitative "acceptance criteria" or "reported device performance" in terms of accuracy metrics (e.g., sensitivity, specificity, precision) typically seen for diagnostic devices. Instead, the substantial equivalence claim focuses on the device's characteristics (intended use, form, matrix, levels, storage, analytes, open vial claim) being similar to a legally marketed predicate device.

Explanation: The "acceptance criteria" for a quality control device typically relate to its stability, uniformity, and ability to produce expected results within a specified range when tested with appropriate assays. This document, being a 510(k) summary, primarily focuses on demonstrating that the device is "substantially equivalent" to a predicate device rather than presenting a detailed performance study with quantitative acceptance thresholds for accuracy. The comparison table essentially serves as the "study" for substantial equivalence, showing that the key characteristics align or are appropriately addressed.

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

This information is not provided in the document. The 510(k) summary for this quality control device focuses on demonstrating substantial equivalence based on technological characteristics and intended use, rather than clinical performance data from patient samples. Therefore, there is no mention of a "test set" of patient data in the context of typical diagnostic device evaluation.

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 and not provided for this type of device (quality control). Ground truth determination by experts is relevant for diagnostic devices that interpret patient results.

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

This information is not applicable and not provided for this type of device (quality control). Adjudication methods are used for resolving discrepancies in expert interpretations of diagnostic data.

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 not provided. An MRMC study is relevant for diagnostic imaging or interpretation systems, particularly those that involve human readers and AI assistance. This device is a quality control product.

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

This information is not applicable and not provided. A standalone performance evaluation is relevant for automated diagnostic algorithms. This device is a biochemical control.

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

This information is not applicable and not provided. "Ground truth" in the context of diagnostic accuracy is not relevant for a quality control product where the objective is to ensure the consistent performance of an assay. The "ground truth" for a quality control material would generally refer to its known characteristics and stability, which are validated during manufacturing.

8. The sample size for the training set

This information is not provided and is not applicable for this type of device. Training sets are relevant for machine learning algorithms.

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

This information is not provided and is not applicable for this type of device.

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