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The Anivia SG1000 Pump Console is intended to pump blood through the extracorporeal bypass circuit for extracorporeal support for periods appropriate to cardiopulmonary bypass (up to 6 hours).

The Anivia SG1000 Pump Console is a device for pumping blood without direct contact in an extracorporeal blood circulation circuit. The device is prescribed (Rx) by specialists to be used in Cardiopulmonary Bypass (CPB) procedures. The Anivia SG1000 Pump Console consists of the following modules: Display & Control Module, Pump Driver Module, Flow Bubble Sensor Module, Backup Battery Module, and Cart Module. It is intended to be used in conjunction with other previously 510(k)-cleared devices and sterile accessories such as cannulas, catheters, oxygenators, luer connectors and single use centrifugal pump heads, supplied by hospital users or other manufacturers.

Here's the information regarding the acceptance criteria and study proving the device meets them, based on the provided text:

Device Name: Anivia SG1000 Pump Console (K230698)
Regulation Name: Cardiopulmonary Bypass Pump Speed Control

1. Table of Acceptance Criteria and Reported Device Performance:

The provided document does not explicitly list "acceptance criteria" in a quantitative performance table format. Instead, it describes various non-clinical tests conducted and states that "All testing met predetermined acceptance criteria." The table below summarizes the types of tests performed and the general outcome.

2. Sample size used for the test set and the data provenance:

• Sample Size for Test Set: The document does not specify a distinct "test set" sample size in terms of number of patient cases or images, as this is a device for regulating pump speed in cardiopulmonary bypass, not an AI/imaging diagnostic device. The testing involved various engineering and systems-level tests.
• Data Provenance: Not applicable in the context of typical AI/imaging studies. The testing described is performance testing of the device itself (hardware, software, electrical, mechanical, reliability) against engineering standards and internal criteria. There is no mention of patient data.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

This information is not applicable. The device is a cardiopulmonary bypass pump console, not a diagnostic tool requiring expert interpretation of medical data (like images or clinical reports) to establish ground truth for a test set. The "ground truth" here is adherence to engineering specifications and performance standards, validated through bench testing, not expert consensus on clinical cases.

4. Adjudication method for the test set:

Not applicable, as there is no "test set" in the context of clinical interpretation subject to adjudication. The performance was assessed against predetermined engineering and functional criteria.

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:

Not applicable. This device is a cardiopulmonary bypass pump console, which is an electromechanical medical device, not an AI-assisted diagnostic or interpretation tool for human readers. No MRMC study was performed.

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

Not applicable. This is not an AI algorithm. The device operates with human involvement (physicians, perfusionists, etc.) for setup, monitoring, and control during cardiopulmonary bypass procedures. The "standalone" performance refers to the device's functional integrity as a machine.

7. The type of ground truth used:

The "ground truth" for this device's performance is established by:

• Engineering specifications and design requirements.
• International consensus standards (e.g., IEC 60601 series, ISO 14971).
• Internal predetermined acceptance criteria for functional, electrical, mechanical, software, reliability, and safety tests.

8. The sample size for the training set:

Not applicable. This device does not involve a "training set" in the context of machine learning or AI models. It's an electromechanical medical device.

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

Not applicable, as there is no training set for this type of device.

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The Anivia SG1000 Pump Console is intended to pump blood through the extracorporeal bypass circuit for extracorporeal support for periods appropriate to cardiopulmonary bypass (up to 6 hours).

The Anivia SG1000 Pump Console is a device for pumping blood without direct contact in an extracorporeal blood circulation circuit. The device is prescribed (Rx) by specialists to be used in Cardiopulmonary Bypass (CPB) procedures. The Anivia SG1000 Pump Console consists of the following modules: Display & Control Module, Pump Driver Module, Flow Bubble Sensor Module, and Backup Battery Module. It is intended to be used in conjunction with other previously 510(k)-cleared devices and sterile accessories such as cannulas, catheters, oxygenators, luer connectors and single use centrifugal pump heads, supplied by hospital users or other manufacturers.

The provided text describes the Anivia SG1000 Pump Console, a device intended to pump blood through an extracorporeal bypass circuit for cardiopulmonary bypass procedures (up to 6 hours). The 510(k) summary focuses on demonstrating substantial equivalence to a predicate device (Medtronic Bio-console® 560 Extracorporeal Blood Pumping Console, K131964).

Here's an analysis of the acceptance criteria and study information:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly list a table of acceptance criteria with specific numerical targets and corresponding reported device performance values for the Anivia SG1000 Pump Console. Instead, it broadly states that "All testing met predetermined acceptance criteria." The performance characteristics are described in comparison to the predicate and reference devices in the "Technological Characteristics" table, implying that the acceptance criteria for these characteristics are met by being "Same as predicate" or by having differences that "do not raise different questions of safety and effectiveness."

Here's a breakdown of the performance characteristics provided, and where the device's performance aligns with or is considered equivalent to the predicate:

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

The document does not specify a "test set" in the context of clinical data for algorithmic performance, as this device does not involve AI or machine learning that would typically use such a test set. The non-clinical tests involved "system bench testing, mechanical testing, electrical safety and electromagnetic interference and compatibility testing, software testing, reliability, and usability testing." The sample size for these engineering and performance tests is not quantified (e.g., number of devices tested, number of test runs).

Data provenance is not applicable since no clinical data or patient data was used to assess the device's performance in this 510(k) submission. All tests mentioned are non-clinical, benchtop, or simulated use.

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

Not applicable. This device does not involve a "ground truth" derived from expert review or clinical annotations for an algorithm. The evaluation relies on engineering tests and compliance with recognized standards.

4. Adjudication Method (e.g., 2+1, 3+1, none) for the Test Set

Not applicable, as there is no "test set" in the context of human-reviewed data where adjudication would be necessary.

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

Not applicable. This device is a cardiopulmonary bypass pump console, not an AI/ML-driven diagnostic or interpretative tool that would involve human readers or an MRMC study.

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

Not applicable. This device is electro-mechanical hardware with software controls, not a standalone algorithm.

7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)

Not applicable. For this type of medical device (a pump console), "ground truth" is established through engineering specifications, validated test methods (e.g., measuring pump speed, flow rate, alarm accuracy), and compliance with international consensus standards. There is no biological or imaging "ground truth" involved.

8. The Sample Size for the Training Set

Not applicable. This device does not involve machine learning or AI, and therefore does not have a "training set." The software embedded in the device undergoes traditional software verification and validation.

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

Not applicable, as there is no training set.

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