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For the calibration of the following tests: Prothrombin time (PT), Fibrinogen, Coagulation factors II, V, VII, VIII, VWF, IX, X, XI, XII and XIII*, Inhibitors: Antithrombin III, Protein C, Protein S, α2-antiplasmin, C1-inhibitor*, Total complement activity*, Plasminogen. (* Not available in the U.S.)

Standard Human Plasma is a lyophilized calibrator prepared from pooled citrated human plasma, stabilized with buffer solution and then lyophilized. It is assayed for the calibration of various coagulation and fibrinolysis tests

The provided document describes a 510(k) premarket notification for a medical device called "Standard Human Plasma." This device is a calibrator for in vitro coagulation and fibrinolysis studies.

Here's an analysis of the acceptance criteria and study information, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

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

The document states "In duplicate determinations," which indicates that stability testing was performed with at least two samples for each condition. However, the exact sample size beyond "duplicate" is not provided. The provenance of the data is not mentioned (e.g., country of origin, retrospective or prospective).

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

This information is not provided in the document. The "ground truth" for a calibrator like Standard Human Plasma would typically be established by comparing its performance against established reference materials or methods. The document only states that the device "recovered within the assigned values," implying a comparison to these established values, but it does not detail the process or experts involved in establishing those "assigned values."

4. Adjudication Method for the Test Set:

This information is not applicable and not provided. Adjudication methods (like 2+1, 3+1) are typically used in studies involving subjective interpretation of data (e.g., image analysis, clinical diagnoses) where multiple experts assess the same cases and a consensus or tie-breaking mechanism is needed. For a calibrator's stability testing, the outcome is quantitative (recovery within assigned values), thus not requiring an adjudication method.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done:

No, an MRMC comparative effectiveness study was not done. This type of study investigates how human readers' performance is affected by AI assistance, which is relevant for diagnostic AI tools. Standard Human Plasma is a calibrator, not a diagnostic AI tool, so an MRMC study is not applicable.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done:

Yes, in essence, standalone performance was assessed. The device itself (a lyophilized calibrator) performs its function independently of a human operator making interpretive decisions about the calibration itself. The stability testing described is a standalone performance evaluation of the calibrator's ability to maintain its assigned values over time. However, it's not an "algorithm-only" performance study in the context of AI, but rather a performance study of a physical product.

7. The Type of Ground Truth Used:

The ground truth used for the stability testing was referred to as "assigned values." These assigned values would typically be established through expert consensus or by comparison to reference methods/materials that are themselves considered the gold standard for coagulation and fibrinolysis measurements. The document does not explicitly state the specific method used to establish these assigned values, but it implies a pre-defined set of expected values for the calibrator.

8. The Sample Size for the Training Set:

This information is not applicable and not provided because this device is not an AI/machine learning algorithm that requires a training set. It is a physical calibrator.

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

This information is not applicable and not provided for the same reason as above (not an AI/ML algorithm).

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