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The Levitronix CentriMag Primary Console is indicated for use with the Levitronix CentriMag Extracorporeal Blood Pumping System. The Levitronix CentriMag Extracorporeal Blood Pumping System is indicated to pump blood through the extracorporeal bypass circuit for extracorporeal circulatory support for periods appropriate to cardiopulmonary bypass (up to six hours). It is also indicated for use in extracorporeal circulatory support systems (for periods up to six hours) not requiring complete cardiopulmonary bypass (e.g., valvuloplasty, circulatory support during mitral valve reoperation, surgery of the vena cava or aorta, liver transplants etc).

The CentriMag Primary Console is a microprocessor-based device. The microprocessor generates the primary Motor control signal, monitors system sensors, generates front display outputs, and provides alarm functions. The microprocessor acquires the sensor data for use in generating operator displays and alarms. An alphanumeric screen is used to display monitored data, system options, and menus. Operator adjustable alarms and parameters are accessible via the system menus.

Here's a breakdown of the acceptance criteria and study information for the Levitronix CentriMag Primary Console, based on the provided text:

It's important to note that the provided text is a 510(k) summary for a medical device and not a detailed clinical study report. Therefore, some information, particularly regarding specific statistical metrics and study designs common in AI/diagnostic device evaluations, is not present. This submission focuses on substantial equivalence to a predicate device for regulatory clearance.

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size for Test Set: Not explicitly stated. The document refers to "performance characteristics... were tested," but doesn't provide the number of tests, units, or specific data points.
• Data Provenance: Not explicitly stated. Given the nature of a 510(k) for a hardware console, the testing likely involved in-house engineering and laboratory validation, rather than patient data in the typical sense of a diagnostic or therapeutic device. The "comparison with the commercially available predicate device" suggests comparative bench testing.

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

• This information is not provided and is generally not applicable in the context of a 510(k) for a medical device console like the CentriMag, which is a hardware system for pumping blood rather than an AI/diagnostic tool requiring expert labeling of data. The "ground truth" would be the expected functional output and safety parameters confirmed by engineering specifications and testing.

4. Adjudication Method for the Test Set

• Not applicable. This typically refers to resolving discrepancies in expert labeling for ground truth in diagnostic tests. For a device like the CentriMag Console, "adjudication" would refer to engineering and quality control procedures for discrepancy resolution during testing, which are part of standard quality management systems but not detailed in this 510(k) summary.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of How Much Human Readers Improve with AI vs. Without AI Assistance

• No. An MRMC study is not applicable here. The Levitronix CentriMag Primary Console is a cardiopulmonary bypass pump console, not an AI or diagnostic imaging device that assists human readers.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

• No. This question is not applicable as the device is a hardware console for extracorporeal blood pumping, not an algorithm. Its operation inherently involves human interaction for setup, monitoring, and control. The "microprocessor-based" nature implies internal algorithmic control, but not as a standalone algorithm in the context of typical AI device evaluation.

7. The Type of Ground Truth Used

• Engineering Specifications and Predicate Device Performance: The "ground truth" for this device's performance would be against established engineering performance specifications (e.g., flow rate accuracy, alarm functionality, motor control stability) and the known, acceptable performance of the predicate CentriMag Console. Safety and functional reliability are key "truths" established through testing against these benchmarks.

8. The Sample Size for the Training Set

• Not applicable. The CentriMag Primary Console is a hardware device (with embedded software) for blood pumping, not a machine learning or AI model that requires a "training set" in the conventional sense. Its "training" would be analogous to the design, development, and validation of its hardware and software components.

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

• Not applicable. As established in point 8, there isn't a "training set" in the context of an AI model for this device. The "ground truth" for its development would be derived from medical and engineering requirements for safely and effectively performing cardiopulmonary bypass, informed by existing medical practice and the performance of previous or similar devices.

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