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510(k) Data Aggregation
(210 days)
The IMPELLA Controller is an extracorporeal bypass control unit intended to be used to provide circulatory support for periods up to 6 hours. It is also intended to be used to provide circulatory support (for periods up to 6 hours) during procedures not requiring cardiopulmonary bypass. The Impella Controller is intended to be used by trained healthcare professionals in healthcare facilities and medical transport (i.e. ambulance, helicopter, or fixed-wing aircraft) environments.
The IMPELLA Controller also displays pressure measurement readings, which are useful in determining intravascular pressure.
The IMPELLA Controller is a microprocessor-based pump motor driver and purge system. It is designed to operate on AC current (110-240 VAC, 47-63 Hz) or on an internal, rechargeable battery. The IMPELLA Controller generates the signals required to power the drive motor of one of ABIOMED's IMPELLA Percutaneous Support Catheters (the IMPELLA RECOVER LP 2.5 (cleared under K063723), the IMPELLA 5.0 LP and the IMPELLA 5.0 LD (cleared under K083111). The IMPELLA Controller also serves to deliver an infusate of the catheter's drive motor, and to provide useful information regarding the catheter's performance. It is intended to be used by trained healthcare professionals in hospital and medical transport environments. It is lightweight, portable and has an accompanying cart for ease of transport within the hospital.
The provided text describes the IMPELLA Controller's acceptance criteria and the study that proves it meets these criteria.
1. Table of Acceptance Criteria and Reported Device Performance:
The primary acceptance criteria for the IMPELLA Controller were its conformity to established international and internal performance standards, and its equivalence to the predicate device.
Acceptance Criteria | Reported Device Performance |
---|---|
International Standards Compliance | |
IEC 60601-1-2 (Electromagnetic Compatibility - EMC/EMI) | Conformed to IEC 60601-1-2, including pertinent IEC 61000-3-X and IEC 61000-4-X standards, and EN 55011. |
IEC 60601-1-Part 1 (Electrical Safety) | Conformed to IEC 60601-1 - Part 1. |
ISTA 2A and EN 868 (Packaging and Shipping) | Conformed to ISTA 2A and EN 868. |
RTCA/DO-160C (Altitude and Vibration during Operation) | Tested per RTCA/DO-160C. |
ISO 1135-4 (Transfusion equipment) | Applied. |
ISO 8536-4 (Infusion equipment) | Applied. |
EN ISO 10993-1:2003 and parts (Biocompatibility) | Conformed to EN ISO 10993-1:2003 and its parts, including EN ISO 10993-7. |
EN ISO 11135 (Sterility testing) | Conformed to EN ISO 11135. |
FDA Guidance for Software in Medical Devices | Complied with FDA 2005 document "Guidance for Industry and FDA Staff- Guidance for the Content of Pre-market Submissions for Software Contained in Medical Devices". |
Internal Performance Specifications | |
System Durability | Met. |
System Performance | Met. |
System Characterization | Met. |
System Flow Characterization | Met. |
Sensor System Response | Met. |
Equivalence to Predicate Device | Demonstrated equivalent performance characteristics to the predicate system (K063723) through in vitro testing. |
2. Sample size used for the test set and the data provenance:
The text does not specify a sample size for a "test set" in the context of patient data or clinical trials. The performance testing was conducted in vitro, meaning in a controlled laboratory environment, not on human subjects. Therefore, there is no direct patient data or provenance mentioned. The testing focused on the device's technical specifications and compliance with standards.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
This information is not provided in the document section related to performance data. As the tests were in vitro, the "ground truth" would be established by technical specifications and reference standards, rather than expert consensus on patient data.
4. Adjudication method for the test set:
An adjudication method for a "test set" in the context of reviewing clinical cases or images is not applicable here, as the study was in vitro and focused on engineering and functional performance, not clinical scenarios requiring expert interpretation.
5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, and if so, what was the effect size of how much human readers improve with AI vs without AI assistance:
An MRMC comparative effectiveness study was not performed. The IMPELLA Controller is a medical device for circulatory support and not an AI-assisted diagnostic tool that would typically involve human readers interpreting cases.
6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:
The performance testing described was primarily "standalone" in the sense that it evaluated the device's technical capabilities and compliance with standards without a human operator's variable input being a primary focus of the performance assessment (though it is intended for use by trained healthcare professionals). The tests focused on the device's inherent design and functionality, such as system durability, flow characterization, and sensor response.
7. The type of ground truth used:
The ground truth used for the in vitro testing was established based on:
- Established engineering design specifications (e.g., specific flow rates, pressure readings, durability benchmarks that the device was designed to meet).
- International and national standards for medical device safety, electromagnetic compatibility, electrical safety, biocompatibility, sterility, software design, packaging, and transport (e.g., IEC 60601 series, ISO 10993 series, FDA guidance documents).
- Performance characteristics of the predicate device, which served as a benchmark for equivalence in internal performance testing.
8. The sample size for the training set:
The concept of a "training set" is typically associated with machine learning or AI algorithm development. Since the IMPELLA Controller is a hardware-based medical device with microprocessor control, and the provided text does not mention any machine learning components, there is no training set in that context.
9. How the ground truth for the training set was established:
As there is no mention of a training set for machine learning in the provided document, the mechanism for establishing its ground truth is not applicable. The "ground truth" for the device's development and verification would stem from engineering principles, medical requirements for circulatory support, and regulatory standards.
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