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The Ipump™ Pain Management system is indicated for the controlled delivery (continuous, intermittent, and continuous plus intermittent) of analgesic, sedative, and anesthetic solutions through clinically acceptable routes of administration including intravenous, subcutaneous, and epidural, and for regional (local) analgesia applications.

Device Description

The Ipump™ Pain Management System is an external infusion pump offering three different modalities for the delivery of medications to a patient. The modalities include Patient Controlled Analgesia (PCA) mode, PCA plus basal (continuous) mode, and continuous mode.

PCA mode delivers a bolus of a medication at a fixed rate of 90 mL/hr at patient-controlled time intervals by pressing the PCA button. PCA plus basal (continuous) mode delivers medication at 90 mL/hr during patient-controlled time intervals in conjunction with the desired basal delivery of between 0.1 mL/hr and 19.9 mL/hr between PCA doses. In continuous mode, the pump delivers medication continuously at a rate adjustable between 0.1 mL/hr and 90.0 mL/hr.

The Ipump operates using a linear peristaltic pumping mechanism and a DC motor with either a 9 volt alkaline battery or an AC adapter power source. The pump's features include an air sensor, an upstream occlusion detector and a down stream occlusion detector. The disposables for the Ipump™ Pain Management System consist of numerous custom tubing sets and flexible non-vented reservoir bags of up to 500 ml.

AI/ML Overview

This KOS submission is for an Infusion Pump, which is a hardware device, not an AI/ML device. Therefore, the questions related to AI/ML specific criteria (such as sample sizes for test/training sets, ground truth establishment methods, expert involvement, and MRMC studies) are not applicable.

The submission focuses on demonstrating substantial equivalence to a predicate device through non-clinical performance data, primarily related to safety and effectiveness in its mechanical and electrical operation.

Here's an analysis of the provided text based on the nature of the device:

1. Table of Acceptance Criteria and Reported Device Performance

The submission discusses several performance evaluations against recognized standards. The "acceptance criteria" are implied by successful evaluation against these standards.

Acceptance Criteria (Implied Standard Compliance)	Reported Device Performance
Electrical Safety: Compliance with IEC 60601-1 requirements.	Ipump was evaluated against the applicable requirements contained within IEC 60601-1 with successful results.
Electromagnetic Compatibility (EMC): Compliance with IEC 60601-1-2 second edition, augmented by IEC 60601-2-24 clause 36 requirements.	The Ipump characteristics were evaluated against the applicable requirements contained within IEC 60601-1-2 second edition, augmented by the IEC 60601-2-24 clause 36 requirements, with successful results.
General Performance: Compliance with IEC 60601-2-24 requirements.	The performance characteristics of the Ipump were evaluated against the applicable requirements contained within IEC 60601-2-24 with successful results.
Software Performance: Software design changes satisfy various requirements; no adverse effects on unchanged parts of the system.	Software testing was performed at the system level, unit level and integration level to demonstrate that the design changes satisfy the various Ipump™ Pain Management System requirements. Regression testing was performed to demonstrate that the design changes have not adversely affected those parts of the system not changed. The data recorded from the software testing has been determined to meet its acceptance criteria.
Biocompatibility: Same patient-contact components, manufacturing methods, duration, and material type as predicate device.	A comparison of the predicate device with the subject Ipump shows that the same components come into direct and indirect contact with the patient. These components are processed by the same manufacturing methods, and are of the same patient contact duration and material type. Biocompatibility requirements are therefore satisfied.
Environmental Performance: Performance during environmental testing (e.g., temperature, humidity, vibration).	The Ipump performance during environmental testing, such as the (specific tests not detailed, but implied successful).

2. Sample Size for the Test Set and Data Provenance

As this is a mechanical/electrical device, the concept of a "test set" in the context of AI/ML (e.g., a set of medical images or patient records) does not apply. The "tests" here refer to engineering verification and validation activities.

Sample Size: Not explicitly stated in terms of "samples" for a specific dataset but rather describes the device being tested against standards. It implies testing was conducted on one or more units of the Ipump™ Pain Management System.
Data Provenance: Not applicable in the AI/ML sense. The testing was conducted internally by Baxter Healthcare Corporation for regulatory submission purposes. It's non-clinical, not from patient studies or retrospective/prospective medical data.

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

Not applicable. "Ground truth" in the AI/ML sense is not relevant for the testing of an infusion pump's mechanical and electrical performance. The "truth" is defined by compliance with engineering standards and specifications.

4. Adjudication Method for the Test Set

Not applicable. Adjudication methods (like 2+1, 3+1) are used for resolving disagreements in expert labeling of data, which is not relevant for this type of device submission.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No. This is not an AI/ML device, nor is it a device that requires human interpretation of outputs in a way that an MRMC study would be relevant. The pump's function is automated delivery of medication.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

No. Again, this is a hardware device. While it has software, its "performance" is assessed through engineering tests, not through an algorithm-only study in the context of an AI/ML diagnostic or predictive tool.

7. Type of Ground Truth Used

Not applicable in the AI/ML sense. The "ground truth" for this device's performance is established by engineering specifications, regulatory standards (e.g., IEC 60601 series), and the device's own design requirements. The tests verify that the device meets these pre-defined performance and safety criteria.

8. Sample Size for the Training Set

Not applicable. This is not an AI/ML device that requires a "training set."

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

Not applicable. As there is no training set for an AI/ML algorithm.

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