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The SA Ve II™ series are intended to provide short-term ventilatory support to adults during CPR or when Positive-Pressure Ventilation (PPV) is required to manage Acute Respiratory Failure (ARF). The SAVe 11™ series are appropriate for adults that weigh at least 45 kg. It is intended to be used in pre-hospital, field hospitals, and transport environments.

The SAVe II™ and SAVe II™ Basic ventilators are battery powered compressors to deliver automated, controlled positive pressure breaths with ambient air for up to 10 hours. It is designed to augment the capabilities of first responders by supplementing Bag Valve Mask (BVM) manual ventilation delivery with an automated solution that can be rapidly deployed by minimally skilled providers in environments where compressed oxygen is unavailable or ill-advised.

To support use in emergency situations, the SA Ve II™ is portable and easy to carry. Rapid initial setup is enabled by default ventilator settings based on adult patient's height, ranging from 4'6'' to 6'6" weighing at least 45 kg, organized in a circular-shaped graphic. To mitigate the risk of patient injury, airway pressure is monitored and users are alerted to potentially dangerous low and high pressure situations. Immediate patient injury due to high pressure is avoided by a pressure cut-off that triggers an exhalation if inspiratory pressure exceeds device settings. Rapid troubleshooting is enabled by visual alarm indicators located together at the bottom of the unit that identifies the most likely cause of the triggered alarm.

Here's a breakdown of the acceptance criteria and the study method for the AutoMedx SAVe II™ and SAVe II™ Basic devices, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The submission primarily focuses on demonstrating substantial equivalence to predicate devices rather than establishing novel performance criteria with specific acceptance thresholds. The "acceptance criteria" are implied by the features and performance characteristics of the predicate devices. The reported device performance aligns with these characteristics.

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

The document primarily describes bench testing rather than studies involving human subjects or real-world data.

• Sample Size: Not specified in terms of numerical units like "cases" or "patients." The testing involved "a complete set of performance testing to the device specifications" and "comparative bench testing to the predicate."
• Data Provenance: Not applicable in the traditional sense of clinical data. The data is generated from non-clinical bench testing performed by the manufacturer, AutoMedx, Inc. The nature of this testing does not involve country of origin in the context of patient data. It is prospective in the sense that the tests were conducted specifically for this submission.

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

Not applicable. The ground truth for bench testing is established by the device's technical specifications and the performance of the predicate device. It does not involve expert image interpretation or clinical diagnosis.

4. Adjudication Method for the Test Set

Not applicable. This is not a clinical study involving human readers or interpretation where adjudication would be necessary. Performance is measured against engineering specifications and comparison to the predicate's technical characteristics.

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 MRMC comparative effectiveness study was done. This medical device (a ventilator) is not an AI-assisted diagnostic or interpretive tool where human reader performance would be a primary metric.

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

Yes, the primary evaluation involved standalone bench testing of the device's performance against its specifications and comparison to predicate devices' technical characteristics. This is an "algorithm only" performance (referring to the device's internal software controlling ventilation parameters), without a human in the loop for interpreting the device's output in the way one would for an AI diagnostic tool. Instead, the device itself delivers the therapy.

7. The Type of Ground Truth Used

The "ground truth" for the non-clinical testing was based on:

• Device specifications: The SAVe II™ and SAVe II™ Basic were tested to ensure they met their own predefined performance requirements.
• Predicate device characteristics: The performance of the SAVe II™ models was compared against the known characteristics and performance of the predicate devices (Impact Instruments - Uni-Vent Model 754 - K931473 and AutoMedx - SAVe™ - K071221). Substantial equivalence was claimed if the device performed comparably or better (e.g., in terms of battery life or alarms).

8. The Sample Size for the Training Set

Not applicable. This is not a machine learning or AI device that requires a "training set" in the context of data-driven model development. The device's operation is based on pre-programmed logic and control algorithms.

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

Not applicable, as no training set was used.

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The SAVe is intended for use on adults that need ventilatory support. Specifically, the SAVe is intended to provide short term ventilatory support for individuals during CPR or when positive-pressure ventilation is required to manage acute respiratory failure. The SAVe device is appropriate for individuals that weigh at least 45 kilograms. It is intended to be used in field hospitals, transport and prehospital environments.

The SAVe is a time cycled ventilator that delivers a set tidal volume. If, at any point, an upper threshold pressure is reached, the device immediately triggers the exhale mode. The SAVe consists of an internal pump (blower), rechargeable sealed lead acid battery, circuit board, manifold, face plate, EMI shielded upper and lower enclosure, air intake port with debris filter, patient port, pressure port, supplemental air / oxygen port, electric port for recharging and / or running, charger / power supply, patient circuit, pressure tubing, oxygen tubing and an activation switch. The device has audio and visual alarms that trigger for low pressure, disconnect, blockage, low battery, high temperature or internal failure. The device not only alarms for stacked breaths but also cuts off the pump until adequate pressure has been released before triggering the next breath. The SAVe comes in three distinct models. Each has a set tidal volume and respiratory rate. Model 550x10 delivers 550 mL of air 10 times per minute. Model 600x10 delivers 600 mL of air 10 times per minute and Model 600x12 delivers 600 mL of air 12 times per minute.

The provided text describes a 510(k) submission for a medical device called the "Simplified Automated Ventilator - SAVe." The submission focuses on demonstrating substantial equivalence to a predicate device, the Impact Uni-Vent 754.

Acceptance Criteria and Device Performance:

The document does not explicitly state numerical "acceptance criteria" as would be found in a performance goal for a diagnostic device. Instead, the performance evaluation is based on demonstrating substantial equivalence to the predicate device, the Impact Uni-Vent 754.

The "reported device performance" is a qualitative statement of equivalence to the predicate device.

Study Details:

The provided text describes a substantial equivalence study for a medical device (ventilator), not a diagnostic algorithm. Therefore, many of the requested elements (like sample size for test set, data provenance, number of experts, adjudication method, MRMC study, standalone performance, ground truth types for test/training sets, and training set sample size) are not applicable or not detailed in this type of submission.

Here's an analysis based on the information provided:

1. Sample size used for the test set and the data provenance: Not explicitly stated. The evaluation was primarily based on bench tests and potentially external third-party tests. The provenance of this test data is implied to be from the manufacturer (Automedx) and external testing agencies.
2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. For a ventilator, ground truth isn't established by experts in the same way as for a diagnostic imaging algorithm. Performance is assessed against engineering specifications, simulated physiological conditions, and comparison to a predicate device.
3. Adjudication method for the test set: Not applicable. Performance is measured against physical parameters and predicate device performance.
4. 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 is a ventilator, not a diagnostic AI algorithm for human readers.
5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: The device is a "Simplified Automated Ventilator," implying it operates autonomously in its core function of delivering ventilation. Performance data was generated from bench tests, which would assess its standalone mechanical and electronic function.
6. The type of ground truth used:
   • Engineering specifications/performance metrics: The device's ability to deliver preset tidal volumes and respiratory rates, trigger exhale mode at an upper threshold pressure, and its alarm functions.
   • Predicate device performance: Comparative data showing the SAVe performs "as safe and effective as the Uni-Vent 754" at the prescribed settings.
   • Compliance with standards: Functioning as intended according to standards for electromagnetic compatibility and air quality.
7. The sample size for the training set: Not applicable. Ventilators are typically designed and calibrated based on engineering principles and preclinical testing, not "trained" on a dataset in the way a machine learning algorithm is.
8. How the ground truth for the training set was established: Not applicable for this type of device. The design specifications and performance parameters derive from medical requirements for ventilation and the characteristics of the predicate device.

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