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The AVEA is intended to provide continuous respiratory support in an institutional health care environment. It may be used on adult, pediatric, and neonatal patients. Properly trained clinical personnel, under the direction of a physician should only operate it.

The AVEA is a servo-controlled, software-driven ventilator. It has a dynamic range of breathing gas delivery that provides for neonatal through adult patients. Its user interface module provides maximum flexibility with simple operator interaction. It has a flat panel color LCD with real time charting and digital monitoring capabilities, a touch screen for interaction, membrane keys and a dial for changing settings and operating parameters. It also has an internal gas delivery system with servo controlled active inhalation and exhalation functions. The AVEA may be configured as a conventional ventilator or non-invasive positive pressure ventilator (NPPV). It has been designed to function using most commonly available accessories.

The provided text is a 510(k) summary for the AVEA Ventilator. It describes the device, its intended use, and states that performance testing and analysis verified the device meets its requirements and is substantially equivalent to legally marketed predicate devices. However, it does not contain the specific details required to complete your request: acceptance criteria, reported device performance metrics, and the specifics of a study proving those criteria were met.

Therefore, I cannot provide a table of acceptance criteria and reported device performance or details about the study, as that information is not present in the provided document.

Here's a breakdown of what can be extracted and what cannot:

A. Information NOT present in the document:

1. A table of acceptance criteria and the reported device performance: The document states "Performance testing and analysis will have verified that the AVEA Ventilator meets its performance requirements," but it does not list these specific requirements or the results.
2. Sample size used for the test set and the data provenance: Not mentioned.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable as there's no mention of a diagnostic AI component requiring ground truth from experts. The device is a ventilator.
4. Adjudication method: Not applicable.
5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done: Not mentioned, and generally not applicable for a device like a ventilator.
6. If a standalone study (i.e. algorithm only without human-in-the-loop performance) was done: Not mentioned, and not a typical study for a ventilator.
7. The type of ground truth used: Not applicable in the context of a ventilator's performance validation.
8. The sample size for the training set: Not applicable as no AI/algorithm training is explicitly described for a diagnostic purpose.
9. How the ground truth for the training set was established: Not applicable.

B. Information that can be inferred or stated from the document:

• Study type: The document generally refers to "Performance testing and analysis" and "Validation" which are typical for medical device clearance processes to ensure the device performs as intended and is safe and effective. It's not a diagnostic AI study.
• Purpose of the study: To demonstrate that the AVEA Ventilator meets its performance requirements and is substantially equivalent to predicate devices.
• Predicate Devices: A list of 7 predicate ventilators from Puritan Bennett, Drager, SIEMENS, Bear Medical Systems, Bird Products Corporation, and DATEX-OHMEDA is provided.

In summary, the provided 510(k) summary for the AVEA Ventilator does not contain the detailed study results, acceptance criteria, or methodological specifics typically found in a clinical study report for an AI/diagnostic device that would allow me to populate your request. It primarily focuses on the regulatory submission process and substantial equivalence to existing devices.

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The 840 Ventilator System with BiLevel Option is used to provide continuous ventilation to patient's requiring respiratory support. This device is used for a wide range of patients from infant to adult and for a wide variety of clinical conditions.

The 840 Ventilator System is a Class II device, "Continuous Ventilator", per 21 CFR Part 868.5895. This device is designated a Class I Type B equipment per IEC 601-1. The 840 Ventilator's gas delivery system consists of two proportional solenoid valves (PSOLs) and an active expiratory valve. Previosly cleared modes of ventilation include Assist Control (AC), Synchronized Intermittent Mandatory Ventilation (SIMV), and Spontaneous (SPONT). The 840 Ventilator System supplies mandatory or spontaneous breaths with a preset level of positive end expiratory pressure (PEEP), trigger sensitivity, and oxygen concentration. A mandatory breath can be pressure- or volume-controlled, except in the optional BiLevel mode, when it is always pressure-controlled. A spontaneous breath mode allows the patient inspiratory flows of up to 200 L/min, with or without pressure support. The 840 Ventilator modification is the addition of two new features for this device, the BiLevel Option and Inspiratory Pause. The BiLevel mode and Inspiratory Pause features are implemented on the 840 Ventilator through additional functionality in software and by using the existing User Interface panel. "BiLevel" has been added as a mode choice in the touch screen MODE menu. The INSP PAUSE key on the user interface, is activated to perform the inspiratory pause function. The pneumatic design and the electrical circuitry (apart from the User Interface printed circuit board) has remained unchanged functionally.

This document describes a 510(k) premarket notification for the Puritan-Bennett 840 Ventilator System with a new BiLevel Option and Inspiratory Pause features. The submission focuses on demonstrating substantial equivalence to previously cleared devices rather than providing a detailed study proving the device meets specific acceptance criteria with quantifiable performance metrics.

Therefore, many of the requested sections (Table of acceptance criteria, sample size, number of experts, adjudication method, MRMC study, standalone performance, sample size for training, ground truth for training) cannot be extracted from the provided text as they are not present in this type of regulatory submission for a modification to an existing device.

Here's what can be extracted and inferred based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

This information is not explicitly provided in the document as it is a 510(k) submission for a modification to an existing device, focusing on substantial equivalence rather than primary functional performance testing against novel acceptance criteria.

The submission states: "Puritan-Bennett Corp. asserts that a) the intended use of the 840 Ventilator with BiLevel Option, as described in its labeling, has not changed from that of the cleared device, the 840 Ventilator, and b) the fundamental scientific technology of the 840 Ventilator with BiLevel Option has not changed from that of the 840 Ventilator."

It also mentions that "The BiLevel mode and Inspiratory Pause features are currently included in cleared predicate devices, providing justification for substantial equivalence." This implies that the 'acceptance criteria' are implicitly met if the device functions equivalently to these predicate devices for the new features.

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

This information is not provided in the document. The submission references "verification and validation testing, test and software quality procedures" but does not detail the size or nature of the test sets used for these activities, nor the provenance of data. This type of detail is typically internal to the company's design control documentation rather than explicitly stated in a 510(k) summary.

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

This information is not provided in the document. The assessment described is based on engineering verification and validation against design specifications and comparison to predicate devices, not typically through expert-adjudicated ground truth as would be common for diagnostic AI algorithms.

4. Adjudication Method for the Test Set

This information is not provided in the document.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No, an MRMC comparative effectiveness study was not mentioned or relevant to this 510(k) submission. This type of study is more common for diagnostic imaging or AI devices where human reader performance is augmented or compared. The 840 Ventilator is medical equipment; the submission focuses on its functional equivalence and safety.

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

This concept is not directly applicable to a ventilator. While the device contains software algorithms, the "standalone performance" is integrated into the device's overall function and directly assessed as part of its verification and validation. The submission does not describe a separate "algorithm only" performance study in the context of typical AI device evaluations.

7. The Type of Ground Truth Used

The "ground truth" for this device's performance is based on engineering specifications, functional testing against those specifications, and demonstrated equivalence to previously cleared predicate devices. For example, the device must accurately deliver a preset tidal volume or maintain a target pressure. This would be verified through direct measurement with calibrated equipment during testing, rather than through expert consensus, pathology, or outcomes data in the way these terms are typically used for diagnostic devices.

8. The Sample Size for the Training Set

This information is not provided in the document. The device's operation is based on deterministic algorithms and control systems, not learning models that require a "training set" in the machine learning sense.

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

This information is not provided in the document, as it doesn't describe a machine learning model with a training set. The "ground truth" for its development would be the fundamental principles of respiratory mechanics, engineering design standards, and pre-defined performance parameters derived from clinical requirements for ventilators.

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The Siemens Servo Ventilator 300 is intended for general and critical ventilatory care for use with neonatal, infant, pediatric, and adult patients The unit is designed to be used at the bedside and for in-hospital transport. It is not intended for transport use in ambulances or helicopters in the U.S. market.

The intended use of the Computer Interface Board Version 2 is the same as for the Computer Interface Board Version 1. The CI board stores and transmits information about the ventilator to external digital devices via optically isolated serial interfaces.

The Servo Ventilator 300 and Computer Interface Version 2 is a modification of the Servo Ventilator 300 and Computer Interface Version 1 which was found Substantially Equivalent on June 26, 1991 (Premarket Notification K902859). These modifications are being made to update the hardware design and to make additional software features available, while retaining the original functionality.

The Servo Ventilator 300 Alarm and Monitoring Module has been modified to eliminate false or otherwise unnecessary alarms by eliminating the "Leakage Alarm" feature, and miscellaneous minor improvements to other alarm functions. This improves ease of use, and has the additional benefit of improving user vigilance when real alarms occur.

The Computer Interface, CI, is an accessory circuit board that interfaces the ventilator to an external information-gathering system, such as a personal computer, via asynchronous serial lines. Information, such as trend data, real time parameter values, and technical information, is transferred to the external system via different commands. The modifications in the Version 2 hardware improve reliability and manufacturing efficiency. The modifications in the Version 2 software allow the user to select from a wider variety of data channels and add the transmission of checksums to ensure data integrity.

This 510(k) summary describes a ventilator and computer interface, not an AI/ML device, therefore, the requested information elements related to AI/ML device performance (e.g., sample size for test set, number of experts, MRMC studies, standalone performance, training set details) are not applicable.

Here's an analysis based on the provided text, focusing on the acceptance criteria and the study proving the device meets them for this traditional medical device:

1. Table of Acceptance Criteria and Reported Device Performance

2. Reduced risk of ventilator shutdown due to component failures on the Computer Interface Board. | 1. The two circumstances triggering the predicate device's leakage alarm (gross leaks, malfunctioning flow transducer) will also trigger the expired minute volume alarm, thus "no reduction in patient safety from removing this alarm function."
3. Hardware improvements to the Computer Interface Board "affect the safety and effectiveness of the Servo Ventilator 300 by reducing the risk of ventilator shutdown as a result of component failures on the Computer Interface Board." |
   | Effectiveness/Functionality | 1. Retain original functionality despite hardware/software modifications.
4. Improve ease of use (related to alarm logic).
5. Computer Interface to store and transmit information about the ventilator to external digital devices.
6. Computer Interface to provide an expanded list of data items. | 1. Modifications made "while retaining the original functionality."
7. Alarm logic modifications "improves ease of use."
8. Computer Interface (CI) "stores and transmits information about the ventilator to external digital devices via optically isolated serial interfaces."
9. Software modifications "introduce new functions which provide the external data gathering system with an expanded list of data items that can be queried from the Servo Ventilator." |
   | Performance (Technical) | 1. Reliability improvements for both Servo Ventilator 300 and Computer Interface.
10. Manufacturing efficiency improvements.
11. Immunity to interference (for CI).
12. Data integrity (for CI, via checksums).
13. All alarm conditions simulated and output channels tested; tests passed according to criteria equal to or more stringent than predicate device. | 1. Servo Ventilator 300 hardware modifications "improve reliability." CI hardware design changes "improve reliability."
14. CI hardware design changes "simplify manufacturing."
15. CI hardware design changes "increase immunity to interference."
16. CI software modifications "add the transmission of checksums to ensure data integrity."
17. "All alarm conditions were simulated and all output channels were tested... All tests were passed according to criteria that are equal or more stringent than the test criteria which were applied to the predicate device." |
    | Substantial Equivalence | Device is "as safe and effective, and performs as well as or better than the predicate device." | "Analysis and testing have shown that... the modified device is as safe and effective, and performs as well as or better than the predicate device." |

Study Proving Device Meets Acceptance Criteria

The study described is a non-clinical verification and validation study of the modified device, performed at the unit, integration, and system levels.

1. Sample size used for the test set and the data provenance: Not applicable in the context of an AI/ML device. For this traditional device, the "test set" consisted of various operational states and parameters of the ventilator itself. The data provenance refers to the simulated conditions and outputs generated within a controlled test environment.

   • Data Provenance: The tests involved simulating "all alarm conditions" and a "range of ventilator operating states." This indicates a controlled, artificial generation of conditions within a lab setting to test the device's responses.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. The "ground truth" for a mechanical/electronic device like a ventilator is its designed functionality and expected operational responses per engineering specifications, alarm thresholds, and data transmission protocols. These are established by engineering design and regulatory standards, not by expert consensus in the diagnostic sense.

3. Adjudication method for the test set: Not applicable. The testing described is objective and based on comparison of actual device outputs/behavior against predefined engineering specifications and the predicate device's 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 traditional medical device, not an AI-assisted diagnostic tool.

5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. The device is a ventilator, a physical system interacting with a patient, with software components. "Standalone performance" in the AI sense is not relevant. The "standalone" performance here refers to the device's inherent functionality without external systems, which was tested.

6. The type of ground truth used:

   • Engineering Specifications/Design Requirements: The primary ground truth was the device's design specifications for functionality (e.g., alarm logic, data transmission), safety (e.g., no reduction in patient safety), and performance (e.g., reliability, immunity to interference, data integrity via checksums).
   • Predicate Device Performance: The predicate device served as a baseline for "as safe and effective, and performs as well as or better than." The criteria for passing new tests were "equal or more stringent than the test criteria which were applied to the predicate device."

7. The sample size for the training set: Not applicable. This is a traditional medical device, not an AI/ML device that requires a training set.

8. How the ground truth for the training set was established: Not applicable.

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