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When used in NIV mode:
The Airvo 3 NV provides non-invasive ventilator support for non-ventilator dependent, spontaneously breathing adult patients (66 lb/30 kg and above) with respiratory insufficiency. It is intended to be used in hospitals. It is not intended for life support.

When used in High Flow mode:
The Airvo 3 NIV is intended to provide high flow warmed and humidified respiratory gases for administration to spontaneously breathing infant, child, adolescent and adult patients in hospitals. It adds heat and moisture to the flow of air, or blended air/medical oxygen mixture, and assures the user of the air/oxygen mixture using an integrated oxygen analyzer and visual display. The flow may be from 2 to 70 L/min depending on the patient interface. The Airvo 3 NVV provides high flow gases with simultaneous oxygen delivery to spontaneously breathing patients with or without bypassed upper airways in hospitals.

The Airvo 3 NIV provides high flow gases with simultaneous oxygen delivery through nasal cannula interfaces to augment the breathing of spontaneously breathing patients suffering from respiratory distress and/or hypoxemia in the hospital setting. The Airvo 3 NIV is not intended to provide total ventilatory requirements and is not intended for use during field transport.

AirSpiral NIV tube and chamber kit (900PT573):
For use with noninvasive ventilator support for non-ventilator dependent, spontaneously breathing adult patients (66 lbs./30 kg and above) with respiratory insufficiency. It is intended to be used in hospitals. It is not intended for life support.

The subject device, F&P Airvo 3 NIV is a respiratory support device for the delivery of High Flow and NIV (Non-Invasive Ventilation) therapy intended to treat spontaneously breathing patients who would benefit from receiving High Flow or respiratory pressure support. The Airvo 3 NIV is NOT to be used for life-supporting or life-sustaining purposes.

The Airvo 3 NIV is a non-implantable, prescription-only device, provided in a non-sterile state, and intended to be used by healthcare professionals, namely respiratory therapists, doctors and nurses in hospitals. When used in High Flow mode, the Airvo 3 NIV delivers gas at flow rates of between 2-70 L/min. The Airvo 3 NIV also has three non-invasive ventilation therapy modes: CPAP, Bi-Level S/T and Bi-Level PCV.

The AirSpiral NIV Tube and Chamber Kit is a single limb circuit kit designed for use with the Airvo 3 NIV device, for non- ventilator dependent, spontaneously breathing adult patients with respiratory insufficiency.

The provided text is a 510(k) Summary for the F&P Airvo 3 NIV device. It focuses on demonstrating substantial equivalence to predicate devices, rather than a detailed study proving the device meets specific acceptance criteria in the context of an AI/ML algorithm.

Therefore, many of the requested items (e.g., sample size for test set, data provenance, number of experts for ground truth, adjudication method, MRMC study, standalone performance, training set size, ground truth for training set) are not applicable to this document as it does not describe an AI/ML device or a study of its clinical performance against specific acceptance criteria for such an algorithm.

However, I can extract information related to performance testing from the "PERFORMANCE DATA VII." section, which includes "Bench / Performance Testing."

Here's an attempt to answer your request based on the provided document, noting the limitations due to the nature of the submission:

Acceptance Criteria and Study for F&P Airvo 3 NIV (K233643)

The F&P Airvo 3 NIV is a respiratory support device and not an AI/ML driven diagnostic or therapeutic device. The "acceptance criteria" and "study that proves the device meets the acceptance criteria" in this context refer to the non-clinical testing performed to establish substantial equivalence to predicate devices and ensure general safety and effectiveness in line with recognized medical device standards.

1. Table of Acceptance Criteria and Reported Device Performance

The document lists performance testing conducted but does not explicitly state numerical acceptance criteria or reported device performance values in a table format. Instead, it states that the testing "demonstrated the appropriate electrical safety and electromagnetic compatibility profile for the device" and that "The testing demonstrated the appropriate biocompatibility profile for the device" and "The system complies with ANSI AAMI ES 60601-1:2005/(R)2012 and A1:2012, IEC 60601-1-2:2014 and AIM Standard 7351731 Rev. 3.00 2017-02-23" as well as "Alarms testing was performed in accordance with ANSI AAMI IEC 60601-1-8:2006 and A1:2012." For reprocessing, "The acceptance criteria and endpoints used are based on the following standard: AAMI TIR30:2011". For comparative performance, it states "Comparative performance testing was performed to demonstrate substantial equivalence."

Given the information, a table with specific numerical acceptance criteria and performance values cannot be fully populated as requested for items like blending accuracy, flow rate accuracy, etc. The document implies compliance with relevant standards as the "acceptance criteria."

2. Sample size used for the test set and the data provenance:

• Not applicable for an AI/ML context. This device is hardware with embedded software, thus performance testing involves engineering verification and validation, not a test set of patient data for an algorithm. The testing described focuses on functional aspects of the device, not an algorithm's performance on a dataset.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

• Not applicable for an AI/ML context. Ground truth, in the sense of clinical expert assessment of data, is not mentioned in relation to the device's technical performance testing.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

• Not applicable for an AI/ML context. This type of adjudication is relevant for resolving discrepancies in expert interpretations of clinical data, which is not described here.

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:

• Not applicable. This device is not an AI-assisted tool for human readers.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

• Not applicable. This device does not feature a standalone algorithm performing a diagnostic or therapeutic task.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

• For engineering and performance testing described (electrical safety, EMC, flow rate accuracy, etc.), the "ground truth" would be established physical and engineering principles, international standards, and measurements from calibrated reference instruments. It is not clinical "ground truth" as typically defined for AI/ML performance.

8. The sample size for the training set:

• Not applicable. There is no mention of an AI/ML training set. Software verification and validation refer to standard software engineering practices.

9. How the ground truth for the training set was established:

• Not applicable. There is no mention of an AI/ML training set or its associated ground truth establishment.

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the Carina home is a pressure controlled and volume controlled (pressure regulated) ventilator. The device is intended for use with patients with a tidal volume of 100 mL upwards. It is used for patients with respiratory insufficiency, using room air (also with additional oxygen). Federal law restricts this device to sale by or on the order of a physician.

the Carina home is a pressure controlled and volume controlled (pressure regulated) ventilator. The device is intended for use with patients with a tidal volume of 100 mL upwards. It is used for patients with respiratory insufficiency, using room air (also with additional oxygen).

The provided document is a 510(k) summary for the Carina™ home ventilator. It describes the device, its intended use, and its substantial equivalence to predicate devices, but it does not contain the detailed performance study results, acceptance criteria, or ground truth information typically found in a clinical study report.

The document states: "The results of all verification and validation testing demonstrate that all system and design requirements for the Carina home device have been met. Qualification included hazard analysis, system level qualification and verification / validation tests." However, it does not provide the specifics of these tests in terms of performance metrics, acceptance criteria, sample sizes, or ground truth methods.

Therefore, many of the requested details cannot be extracted from this specific 510(k) summary. I can only provide information that is explicitly stated or can be inferred from the provided text.

Here's an attempt to answer based on the available information:

1. Table of acceptance criteria and the reported device performance

The document states that "The results of all verification and validation testing demonstrate that all system and design requirements for the Carina home device have been met." However, no specific acceptance criteria or quantitative performance metrics are reported in this summary. For example, it does not provide specific ranges for delivered tidal volume accuracy, respiratory rate accuracy, or pressure control stability that would typically be associated with a ventilator's performance and its acceptance criteria.

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

This information is not provided in the 510(k) summary. The document mentions "verification and validation testing," but it does not specify the sample size of any test sets (e.g., number of patients, test conditions, etc.) or the provenance of the data.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

This information is not applicable and therefore not provided in the 510(k) summary. This document pertains to a medical device (ventilator) engineering and regulatory submission, not a diagnostic algorithm that requires expert interpretation for ground truth establishment. The "ground truth" for a ventilator would typically relate to its physical performance measurements against established standards, not expert consensus on images or clinical data.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

This information is not applicable and therefore not provided in the 510(k) summary. As stated above, this is not a diagnostic study requiring adjudication of expert opinions.

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

This information is not applicable and therefore not provided in the 510(k) summary. MRMC studies are used for evaluating diagnostic imaging systems or AI algorithms that assist human readers. The Carina home is a ventilator, not a diagnostic imaging or AI-assisted diagnostic device.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

This information is not explicitly stated or applicable as described. The device itself is a ventilator, which operates an algorithm for controlling ventilation. Its performance is evaluated intrinsically, not as a standalone diagnostic algorithm in the context of human-in-the-loop performance. The document only mentions "system level qualification and verification / validation tests," which would inherently evaluate the device's algorithmic performance in controlling ventilation.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

For a ventilator, the "ground truth" would typically be derived from established engineering standards, calibration measurements against highly accurate reference devices, and physiological models. The document does not specify the exact methods for ground truth establishment but implies these through references to "safety testing" and compliance with standards like IEC60601-1, IEC60601-1-2, and ASTM F1246. These standards define the acceptable performance characteristics and testing methodologies for medical devices.

8. The sample size for the training set

This information is not provided and is likely not applicable in the context of this device. Clinical studies for ventilator performance typically involve testing the device on a range of simulated lung models or, in later stages, on a limited number of patients to demonstrate safety and effectiveness. The term "training set" is generally used for machine learning algorithms, which is not the primary focus of this 510(k) for a ventilator.

9. How the ground truth for the training set was established

This information is not provided and is not applicable. As mentioned above, the concept of a "training set" with established ground truth is typically associated with machine learning models, which is not the direct subject of this ventilator 510(k) summary. The ventilator's underlying control logic and algorithms are designed based on established physiological principles and engineering requirements, not "trained" on a dataset in the machine learning sense.

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Filtration of exhaled gases in the ventilator circuit.

Model 3000/06 to be placed in the exhalation pathway of the ventilator circuit where filtration of the expired gases is desired. Filter is reusable up to 100 times, extended use as determined by the increase in airflow resistance, which is determined during self testing (SST) mode of the ventilator. For use with the Series 700 and 7200 NPB ventilators.

Cleaning method -- autoclaved -- 30 minutes with 3 minutes at 134°C.

Environment of Use --Hospital, Sub-acute Institutions

The Air Safety Model 3000/06 HEPA filter is a multi-use, reusable ventilator in-line filter which The An Bareey Indust side of the PB 700 series and 7200 ventilators. It can be cleaned by steam ecomeets in the ennation are 1 year service life. It has standard 22 mm tubing connectors and it has a clear housing. It contains the Air Safety standard Multipleat media which has been HEPA tested for enting performance according to BS 3928 Sodium Flame for Air filters and in accordance to DOE 3202-97 and ASTM D2986 - DOP. In addition BFE and VFE testing has been performed by 1902 5202 77 and in the substantial equivalence to the predicate devices.

This response describes the acceptance criteria and the study that indicates the device meets the acceptance criteria.

1. Table of Acceptance Criteria and Reported Device Performance

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

The document does not explicitly state a specific "test set" sample size in terms of the number of devices or units tested for each performance characteristic. Instead, it refers to the performance of the predicate devices and implies that the Air Safety Model 3000/06 HEPA Filter matches these established performance characteristics.

The provenance of the data is primarily from Nelson Lab for the Bacterial Filtration Efficiency (BFE) and Viral Filtration Efficiency (VFE) testing. The document also refers to testing performed according to BS 3928 Sodium Flame for Air filters and in accordance with DOE 3202-97 and ASTM D2986 - DOP. The context suggests these are retrospective references to established standards and predicate device performance, rather than a prospective, independently designed clinical trial specifically for the 3000/06 model.

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

The document does not specify the number or qualifications of experts used to establish a "ground truth" for a specific test set. The data presented is engineering and laboratory performance data (e.g., filtration efficiency, resistance to flow) measured against established industry standards and specifications, rather than clinical outcomes requiring expert consensus on a patient-level "ground truth."

4. Adjudication Method for the Test Set

Not applicable. The evaluation relies on direct measurements against predefined technical specifications and standards, not on subjective assessments requiring adjudication.

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

No, a multi-reader multi-case (MRMC) comparative effectiveness study was not performed. This type of study is typically used for diagnostic imaging devices where human readers interpret patient cases, and the AI's impact on their performance is evaluated. The Air Safety Model 3000/06 is a physical filter, not a diagnostic tool that involves human interpretation of cases.

6. Standalone Performance Study

Yes, a standalone (algorithm only without human-in-the-loop performance) study was effectively done. The performance metrics listed (e.g., BFE, VFE, resistance to flow, dead space) are inherent properties of the device itself, measured independently of human interaction in typical clinical use. The "study" here refers to the laboratory testing conducted to ascertain these physical and filtration properties against established standards.

7. Type of Ground Truth Used

The "ground truth" for the performance claims is based on established engineering and laboratory standards and predicate device specifications. For example:

• Bacterial and Viral Filtration Efficiency: Determined by testing performed by Nelson Lab, likely against a standardized challenge (e.g., specific bacterial/viral aerosols) under controlled laboratory conditions.
• Resistance to Flow: Measured using standardized methodologies relevant to ventilator circuits (e.g., flow rates of 60 lpm and 100 lpm).
• HEPA testing: Performance according to BS 3928 Sodium Flame for Air filters and DOE 3202-97 and ASTM D2986 - DOP, which specify testing procedures and filtration efficiency requirements for particulate matter.

8. Sample Size for the Training Set

Not applicable. This device is a physical filter being evaluated against quantifiable performance metrics, not an AI model that requires a "training set" for machine learning.

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

Not applicable, as there is no training set for this device.

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