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The InstaRead™ Lithium System is intended to measure lithium blood levels in whole blood (fingerstick or venous). Measurements of lithium are used to aid in the management of individuals taking lithium for the treatment of mental disturbances, such as manic-depressive illness (bipolar disorder).

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Here's the information about the acceptance criteria and the study for the InstaRead™ Lithium System, based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document does not contain specific acceptance criteria for performance metrics (like accuracy, precision, or comparison to a predicate device). It primarily focuses on the regulatory approval for marketing.

However, based on the context of a "Lithium test system," typical acceptance criteria would involve demonstrating equivalency to a legally marketed predicate device in terms of:

• Accuracy/Correlation: How well the device's measurements correlate with a reference method or predicate device.
• Precision/Reproducibility: The consistency of results when the same sample is tested multiple times.
• Linearity/Range: The ability of the device to accurately measure lithium across its claimed analytical range.

Since these specific criteria and their actual performance values are not detailed in the provided FDA letter, the table below reflects what would typically be expected in such a submission, but with "Not Specified" for the actual values. The document states a "substantial equivalence determination," implying these criteria were met.

2. Sample Size Used for the Test Set and the Data Provenance

The provided document does not specify the sample size used for the test set or the data provenance (e.g., country of origin, retrospective or prospective).

3. Number of Experts Used to Establish the Ground Truth for the Test Set and the Qualifications of Those Experts

The provided document does not specify the number or qualifications of experts used to establish ground truth for a test set. For an in vitro diagnostic device like a lithium test system, "ground truth" would typically be established by a reference laboratory method or a predicate device, rather than human expert opinion on images or clinical assessments.

4. Adjudication Method for the Test Set

The provided document does not specify any adjudication method for a test set. This is generally not applicable for a chemical assay device where comparisons are made to quantitative reference values.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

The provided document does not mention or imply that an MRMC comparative effectiveness study was done. This type of study is more relevant for diagnostic imaging systems where human readers interpret images, rather than for an in vitro diagnostic device that produces quantitative measurements directly.

6. Standalone (Algorithm Only) Performance Study

The provided document does not explicitly describe a standalone performance study as would be typically understood for an AI algorithm. However, the entire submission for an in vitro diagnostic device like the InstaRead™ Lithium System essentially is a "standalone" performance evaluation of the device itself (the "algorithm" being the chemical and optical measurement process) to determine its accuracy, precision, and other analytical characteristics against reference methods or predicate devices. There is no mention of a human-in-the-loop component for this specific measurement system.

7. Type of Ground Truth Used

The provided document does not explicitly state the type of ground truth used. For a lithium test system, the ground truth would almost certainly be established through:

• Reference Laboratory Methods: Highly accurate and precise laboratory methods (e.g., atomic absorption spectrometry, inductively coupled plasma mass spectrometry) to determine actual lithium concentrations.
• Predicate Device Comparison: Measurements by a legally marketed and established lithium test system used as a comparator.

8. Sample Size for the Training Set

The provided document does not specify the sample size for a training set. For a chemical assay device, there isn't typically a "training set" in the same way as there would be for an AI algorithm that learns from data. The device's calibration and internal algorithms are developed and validated during the device's engineering and manufacturing process, using controlled samples.

9. How the Ground Truth for the Training Set Was Established

The provided document does not specify how ground truth for a "training set" (as understood in machine learning) was established. If referring to the establishment of calibration curves or internal reference values for the device, this would typically involve:

• Certified Reference Materials (CRMs): Samples with known, accurately measured concentrations of lithium.
• Primary Calibrators: Solutions prepared with high purity lithium salts to establish the device's response curve.
• Comparison to Reference Methods: Using samples analyzed by highly accurate reference laboratory methods to "train" or validate the device's measurement system.

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