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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.

This document is a 510(k) summary for a medical device called the "Levitronix CentriMag Primary Console". It describes the device, its intended use, and its comparison to a predicate device to demonstrate substantial equivalence. However, it does not contain acceptance criteria for device performance or a study demonstrating the device meets those criteria in the way typically expected for an AI/software device that makes diagnostic or interpretive claims.

This device is a cardiopulmonary bypass pump console, which is hardware that controls a blood pumping system. The 510(k) is primarily focused on demonstrating that a new version of the console, specifically with "Software Version 3.00", is substantially equivalent to a previously cleared version (Software Version 2.02).

Therefore, I cannot extract the requested information as it is not present in the provided text. The questions posed relate to the evaluation of AI or diagnostic software, which this device is not.

Here's why the requested information isn't applicable or available in this document:

• Acceptance Criteria for Performance: For a mechanical device like this, acceptance criteria would typically involve engineering specifications (e.g., flow rate accuracy, pressure monitoring accuracy, alarm response times, battery life). These are not detailed in a way that can be presented in a performance table as if it were a diagnostic AI. The document only generally states: "The performance characteristics of the Levitronix CentriMag Primary Console were tested and compared with Levitronix performance specifications established for the device and with the commercially available predicate device." No specific performance metrics or their achieved values are reported in this summary.
• Study Proving Acceptance Criteria: The "study" mentioned is a comparison to a predicate device and internal performance specifications. This is not a study in the sense of a clinical trial or performance evaluation using a test set with ground truth as would be done for an AI algorithm.
• Sample Size for Test Set/Data Provenance/Experts/Adjudication/MRMC/Standalone/Ground Truth (for test set)/Training Set/Ground Truth (for training set): These are all concepts related to the validation of AI or diagnostic algorithms using clinical data. This document describes a medical device (a pump console) that does not make diagnostic interpretations or use AI in the way implied by these questions. The software mentioned (V3.00 Application Software) is for controlling the pump, monitoring sensors, and displaying data, not for making diagnostic decisions based on patient data.

In summary, the provided text is a regulatory submission for a hardware medical device with embedded software for control, not a diagnostic or AI-driven system. Therefore, the questions are largely not applicable to the content provided.

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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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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. Oneator adjustable alarms and parameters are accessible via the system menus.

The provided text is a 510(k) Summary for the Levitronix CentriMag Primary Console. This document focuses on demonstrating substantial equivalence to a predicate device for regulatory approval, rather than presenting a detailed clinical study with specific acceptance criteria and performance metrics typically associated with AI/software-as-a-medical-device (SaMD) clearances.

Therefore, much of the requested information (acceptance criteria table, sample sizes, expert qualifications, adjudication methods, MRMC study details, standalone performance, training set details) cannot be found in the provided text because the device is a hardware medical device (a cardiopulmonary bypass pump console), not an AI/SaMD product.

However, I can extract the relevant information from the document regarding its "performance data" in the context of a hardware device submission.

Here's a breakdown based on the provided text, indicating what is present and what is absent:

1. A table of acceptance criteria and the reported device performance

The document does not provide a formal table of acceptance criteria and reported device performance in the manner typically seen for SaMD or diagnostic devices (e.g., sensitivity, specificity, AUC). Instead, it makes a general statement about performance testing against established specifications.

• Acceptance Criteria (Implied): "Levitronix performance specifications established for the device" (Section H). These are not detailed in the summary.
• Reported Device Performance: "The performance characteristics of the Levitronix CentriMag Primary Console were tested and compared with Levitronix performance specifications established for the device and with the commercially available predicate device." (Section H). No specific quantitative performance metrics are provided in this summary document. The comparison confirms functional equivalency rather than specific diagnostic accuracy metrics.

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

• Sample Size: Not specified. Performance testing in this context typically refers to engineering bench testing and verification/validation activities of a hardware system, not a clinical test set with patient data.
• Data Provenance: Not applicable, as this refers to hardware performance testing, not patient data.

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)

• Not applicable. This device is a hardware pump console, and its "performance" would be assessed against engineering specifications and predicate device behavior, not by expert interpretation of clinical data.

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

• Not applicable. This is not a clinical study involving human readers or interpretation.

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

• No. This is a hardware device; no MRMC study involving human readers and AI assistance was conducted or is relevant for this type of device.

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

• Not applicable. This is a hardware device, not an algorithm. Its "standalone" performance would refer to its operational characteristics without external human intervention, which would be part of standard engineering testing.

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

• Ground Truth: For a hardware device like this, the "ground truth" would be established engineering specifications, design requirements, and the known performance/characteristics of the predicate device. It is not clinical "ground truth" like pathology or expert consensus.

8. The sample size for the training set

• Not applicable. This is a hardware device, not a machine learning model.

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

• Not applicable. This is a hardware device, not a machine learning model.

Summary of the Study that Proves the Device Meets Acceptance Criteria (based on the provided text):

The document states under "H. Summary of Performance Data":

"The performance characteristics of the Levitronix CentriMag Primary Console were tested and compared with Levitronix performance specifications established for the device and with the commercially available predicate device."

This indicates that:

• Study Type: This was a performance testing and comparison study (likely involving bench testing, verification, and validation activities common for hardware medical devices).
• Objective: To demonstrate that the new CentriMag Primary Console performs according to its internal Levitronix performance specifications and is functionally equivalent to the predicate device (Levitronix CentriMag Console, K020271).
• Key Finding: The submission implies that these tests confirmed the device meets its specifications and is substantially equivalent, raising "no new safety or effectiveness issues" (Section G).

However, specific details of these tests (e.g., number of test cycles, specific parameters measured, quantitative results, pass/fail criteria) are not included in this 510(k) summary document. These details would typically be found in the full 510(k) submission attachments, but not in the publicly available summary.

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