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510(k) Data Aggregation
(173 days)
The INOmax® DS delivery system delivers INOmax® (nitric oxide for inhalation) therapy gas into the inspiratory limb of the patient breathing circuit in a way that provides a constant concentration of nitric oxide (NO), as set by the user, to the patient throughout the inspired breath. It uses a specially designed injector module, which enables tracking of the ventilator waveforms and the delivery of a synchronized and proportional dose of NO. It may be used with most ventilators.
The INOmax® DS provides continuous integrated monitoring of inspired O2, NO2, and NO, and a comprehensive alarm system.
The INOmax® DS incorporates a battery that provides up to 6 hours of uninterrupted NO delivery in the absence of an external power source.
The INOmax® DS includes a backup NO delivery capability that provides a fixed flow of 250 mL/min of NO which along with user supplied 10 L/min of oxygen provides 20 ppm in the gas flow to a patients breathing circuit. It may also use the INOblender® for backup.
The target patient population is controlled by the drug labeling for INOmax® and is currently neonates. The primary targeted clinical setting is the Neonatal Intensive Care Unit (NICU) and secondary targeted clinical setting is the transport of neonates.
The INOmax DSIR® uses a "dual-channel" design to ensure the safe delivery of INOmax®. The first channel has the delivery CPU, the flow controller and the injector module to ensure the accurate delivery of NO. The second channel is the monitoring system, which includes a separate monitor CPU, the gas cells (NO, NO2, and O2 cells) and the user interface including the display and alarms. The dual-channel approach to delivery and monitoring permits INOmax® delivery independent of monitoring but also allows the monitoring system to shutdown INOmax delivery if it detects a fault in the delivery system such that the NO concentration could become greater than 100 ppm. The delivery system can also shut down delivery if it detects certain serious problems with the monitoring system.
1. Table of Acceptance Criteria and Reported Device Performance:
The document describes software and labeling modifications to the INOmax DSIR, focusing on alarm thresholds and compatibility with new respiratory care devices. The acceptance criteria are implicitly met by successful verification testing. The performance is described by how the modified alarms function and successful compatibility testing.
| Feature/Specification | Acceptance Criteria (Implied) | Reported Device Performance |
|---|---|---|
| Alarms/Alerts | ||
| Low Battery Alarm Threshold | Low Battery alarm to activate at 60 minutes remaining battery life (internally) | The Low Battery alarm threshold limit was changed from 30 minutes to 60 minutes in the software to provide additional margin to the system electronics. From the user perspective the alarm limit is still 30 minutes. Shutdown of the device when operating on battery is not dependent on the Low Battery alarm, therefore the length of runtime when operating on battery remains unchanged. |
| Delivery Failure (NO > 100 ppm) | Alarm and delivery shutdown when monitored NO > 100 ppm for 12 continuous seconds. | The NO > 100 ppm condition must be present for 12 continuous seconds at monitored NO > 100 ppm before alarm and delivery shutdown. The 12 second timer will be reset when a sampling blackout occurs. The change in time to 12 seconds, from zero seconds was made to prevent loss of delivery conditions during transient monitored NO values briefly exceeding 100 ppm. |
| Delivery Failure (NO > 2x setpoint) | Alarm and delivery shutdown when monitored NO > 2x setpoint for 12 continuous seconds. | To prevent loss of delivery during transient conditions, the overdelivery condition of NO > 2x setpoint must be present for 12 continuous seconds (versus 0 seconds in the prior software version) at monitored NO > 2x setpoint before alarm and delivery shutdown. |
| Delivery Failure (Under Delivery) | Under Delivery Alarm to trigger when under-delivery condition is present for 12 consecutive seconds. | Under Delivery Alarm added. To prevent loss of delivery during transient conditions, the under delivery condition must be present for 12 consecutive seconds to trigger the under delivery alarm. In the previous version, the system would immediately shut-down as soon as the under delivery condition was detected. |
| Delivery Failure (System Voltage) | Elimination of three system voltage conditions that previously triggered this alarm. | Three system voltage conditions during which this alarm was triggered have been eliminated. |
| Compatibility with Respiratory Devices | Maintain essential performance (O2 dilution, effect on device, delivery accuracy, NO2 generation) | Testing concluded four requirements necessary for operation of INOmax DSIR and the three respiratory care devices to be compatible: O2 dilution, Effect on respiratory care device, INOmax DSIR® delivery accuracy, NO2 generation. |
| Backup Delivery Function (Fisher & Paykal) | Proper function during backup delivery with Fisher & Paykal circuits. | Testing with the Fisher & Paykal circuits additionally concluded proper function during backup delivery. |
| INOmax DSIR® delivery accuracy | Accurate delivery of NO at various settings (0, 5, 20, 40, 80 ppm). | Performance testing (Verification) was conducted, using settings 0, 5, 20, 40, and 80 ppm for each setting and mode of ventilation. The measured values on the INOmax DSIR were recorded, and no anomalies were reported for delivery accuracy in the summary, implying satisfactory performance. |
| Software Compliance | Compliant with system-level requirements, new/modified alarms function as specified, data communication. | Software verification confirmed the INOmax DSIR® is compliant with its system level requirements, that the new/modified alarms function as specified and that data can be correctly communicated to third part data collection devices via the existing RS-232 port. |
| Control System Performance | Stability/sensitivity analysis demonstrates response handling disturbances and component failures. | Analysis incorporated stability/sensitivity analysis demonstrating the response of the control system using worst-case flow inputs and the handling of disturbances and component failures. Graphical presentation showing time-domain responses of overshoot and undershoot across various ventilator flow rates and flow profiles was also provided. |
2. Sample Size Used for the Test Set and Data Provenance:
- Test Set Sample Size: The document does not specify a numerical sample size for the "test set" in terms of cases or patients. Instead, it refers to testing conducted with:
- Five INOmax DSIR® settings: 0 (baseline), 5, 20, 40, and 80 ppm, "for each setting and mode of ventilation." This implies a systematic study across different operational parameters.
- Three new respiratory care devices: Fisher & Paykal Infant Circuit Nasal Cannula (K020332), Fisher and Paykal Optiflow Breathing Circuit (K983112), and A-Plus Medical Babi Plus Bubble CPAP (K110471).
- Data Provenance: The testing described is non-clinical and conducted by the manufacturer, INO Therapeutics/Ikaria. The data is thus prospective internal testing data. The country of origin is not explicitly stated for the testing, but the company is based in Madison, Wisconsin, USA.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of those Experts:
This information is not provided in the document. The testing described is non-clinical performance and compatibility testing of a medical device, not a diagnostic algorithm that relies on expert interpretation for ground truth establishment.
4. Adjudication Method for the Test Set:
This information is not provided and is not applicable to the type of non-clinical device testing described. Adjudication methods like 2+1 or 3+1 are typically used in clinical studies where multiple experts evaluate cases and a consensus or tie-breaking mechanism is needed for ground truth.
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, an MRMC comparative effectiveness study was not done. This document describes the premarket notification for a medical device (nitric oxide delivery system), not an AI-based diagnostic tool or system designed to assist human readers.
6. If a Standalone (i.e. algorithm only without human-in-the-loop performance) was done:
The device itself is a standalone system for delivering nitric oxide and monitoring gases. The document describes "software verification" and "performance testing" of the device, which inherently represents its standalone (without human intervention once settings are applied) functionality for its intended purpose. The modifications discussed pertain to the internal logic and alarm triggers of this standalone system.
7. The Type of Ground Truth Used:
The "ground truth" for this device's performance is established by:
- Technical Specifications/Requirements: The device is tested against its established system-level requirements and specifications, as well as recognized consensus standards (e.g., IEC 60601 series).
- Physical Measurements: For performance aspects like NO delivery accuracy, measured values from the INOmax DSIR® are recorded and compared against known input settings.
- Functional Verification: For alarms and compatibility, the "ground truth" is whether the alarm triggers as expected under specified conditions or if the integration with other devices functions without issues and meets predefined operational criteria (e.g., no detrimental O2 dilution, no adverse effect on respiratory care device).
8. The Sample Size for the Training Set:
The concept of a "training set" is not applicable to this document. The INOmax DSIR® is a hardware device with embedded software; it does not utilize machine learning or AI that requires a training set in the conventional sense. The "training" for the software's development would implicitly come from the extensive design, development, and iterative testing processes, but not from a distinct, labeled "training set" of data.
9. How the Ground Truth for the Training Set Was Established:
As there is no "training set" in the context of machine learning, the question of how its ground truth was established is not applicable. The "ground truth" for the device's design and functionality is derived from engineering specifications, medical device standards, risk analysis, and clinical requirements for patient safety and efficacy.
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