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The QUANTA Plex™ ENA Profile 5 is a fluorescent immunosorbent assay for the semi-quantitative detection of Sm, RNP, SSA, SSB and Sc1-70 autoantibodies in human serum. The presence of these antibodies can be used in conjunction with clinical findings and other laboratory tests to aid in the diagnosis of systemic lupus erythematosus and related connective tissue diseases such as Sjögren's syndrome and scleroderma.

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This is an FDA Premarket Notification (510(k)) letter for an in vitro diagnostic device, not an AI/ML medical device. Therefore, the requested information regarding acceptance criteria, study details, ground truth, and comparison to human readers is not applicable in the context of an AI/ML device study.

The document describes the FDA's determination of substantial equivalence for the "QUANTA Plex™ ENA Profile 5" device to legally marketed predicate devices, allowing it to proceed to market. This process for in vitro diagnostics is different from the rigorous performance evaluation studies typically expected for AI/ML devices, which often involve comparing AI algorithms against established ground truths and human expert performance.

Here's why the specific questions are not applicable based on the provided text:

• Acceptance criteria table and device performance: The document does not provide specific performance metrics or acceptance criteria for an AI/ML algorithm. It's a regulatory clearance document, not a scientific performance study report.
• Sample size and data provenance: These details are not included as the submission is for a traditional IVD device, not an AI study.
• Number of experts, qualifications, and adjudication method: These pertain to establishing ground truth for AI model evaluation, which is not described here.
• MRMC comparative effectiveness study: This type of study is specifically designed for AI's impact on human reader performance, and is not relevant to this IVD device.
• Standalone performance: While the device has its own performance characteristics, it's not "standalone" in the AI sense (i.e., algorithm only without human-in-the-loop).
• Type of ground truth: The document indicates the device detects autoantibodies to aid in diagnosis, but does not detail how a specific "ground truth" (like pathology or outcomes data) was established for an AI algorithm's training or testing.
• Training set sample size and ground truth establishment (for training): These are AI/ML specific concepts and are not discussed in this 510(k) document.

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