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The Hi-Ox® High FiO2 Mask with the Aerosol Adapter is intended as an accessory for compatible nebulizers. The mask with adaptor is intended to enable the delivery of nebulized drugs to patients who also require elevated inspired oxygen concentrations.

The Aerosol Adapter for the Hi-Ox® is an adapter that enables standard small-volume nebulizers (use only cup type, gas driven nebulizers without tee-fittings or air entrainment ports) with either 18 mm OD or 22 mm ID outlet ports to be adapted to the Hi-Ox®. This will enable patients to be treated with nebulized products while receiving high concentrations of oxygen at moderate flow rates of 8 -10 lpm. The valves in the Hi-Ox® have been tested and found to function normally after nebulization of some commonly nebulized drugs in aqueous formulations. However, the valves could malfunction if the prescribed drug creates a sticky residue on the valves. The practitioner should observe the patient's respiration and the function of the Hi-Ox valves during and after nebulization of drugs via the Hi-Ox80. The Aerosol Adapter is a simple right angle fitting made of Santoprene, a medical grade thermoplastic elastomer material. The adapter can be snapped into a normally plugged port on the Hi-Ox® just below the mask and between the inhalation-exhalation valves. This location for the adapter places nothing between the nebulizer and the patient's airway so as to not impact any of the particles produced by the nebulizer. The qas driving the nebulizer can supplement the normal oxygen supply for the Hi-Ox®, and any flow in excess of what is required by the patient can exit the mask via the normal exhalation pathway. There is no risk of pressure buildup beyond that of the cracking pressure and flow resistance of the exhalation valve (~ 1 cmH2O/L/sec). This enables the patient to receive their nebulizer treatments while maintaining an elevated FiO2.

This document describes the Hi-Ox® High FiO2 Oxygen Mask with the Aerosol Adapter, a Class II medical device. The information provided focuses on its safety and effectiveness, leading to its clearance by the FDA. As such, the "study" referenced in the prompt may not be a traditional clinical trial but rather a series of non-clinical tests and a comparison to predicate devices, which is common for 510(k) clearances.

Here's the breakdown of the requested information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present acceptance criteria in a table format with corresponding device performance metrics. Instead, it describes a "design target" for flow resistance and the results of nebulization tests.

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The Infant Flow Plus System consisting of a Driver and Generator plus NCPAP Prongs and Masks, is intended for the provision of Bi-Level CPAP (SiPAP) to produce a sigh. The system is for use in Hospitals, Hospital-type facilities and intra-Hospital transport environments and is indicated for the treatment of Newborn and Infant patients.

The Infant Flow Plus System is a factory-installed modification to the Infant Flow Plus System. It uses the existing manually operated air / oxygen mixer and CPAP flow control. An ancillary manual flow control with electronic control solenoid valve allows timed delivery of augmented flow and pressure. The modification is housed in a robust enclosure that is designed to "piggy back" on to the existing Infant Flow Driver Unit.

The provided text describes a 510(k) premarket notification for the Infant Flow Plus System. This is a medical device and the performance data presented is related to its compliance with safety and electrical standards, not the clinical performance of an AI/ML algorithm.

Therefore, many of the requested categories in the prompt (e.g., acceptance criteria for an AI algorithm, sample size for test/training sets, number of experts for ground truth, adjudication methods, MRMC studies, standalone algorithm performance, type of ground truth for AI, etc.) are not applicable to this document. This document outlines the regulatory approval for a physical medical device.

However, I can extract the information relevant to the device's performance based on the standards it complies with.

Here's a summary of the available information:

1. A table of acceptance criteria and the reported device performance:

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

• Not applicable. This document describes compliance with device safety and functional standards, not a clinical study involving a test set of patient data.

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

• Not applicable. Ground truth in the context of AI/ML is not relevant here. The "ground truth" for these standards would be the specifications and requirements defined by the standards themselves, validated through engineering tests.

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

• Not applicable. No adjudication method for a test set of patient data is mentioned as it's not a clinical study. Compliance with standards is typically verified through documented testing and review processes by qualified engineers and regulatory bodies.

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 an Infant Flow Plus System, a bi-level CPAP system, not an AI diagnostic tool. No MRMC study or AI assistance is mentioned.

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

• Not applicable. This refers to an AI/ML algorithm's performance. The Infant Flow Plus System is a physical medical device.

7. The type of ground truth used:

• Not applicable in the AI/ML sense. For the device itself, the "ground truth" for its performance is its adherence to the technical specifications and safety requirements outlined in the cited IEC and UL standards.

8. The sample size for the training set:

• Not applicable. There is no AI/ML training set mentioned in this document.

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

• Not applicable. There is no AI/ML training set mentioned in this document.

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The Lyra™ Nasal Mask is intended for use with devices that deliver Continuous Positive Airway Pressure (CPAP) and bi-level positive airway pressure in treating adult patients.

The Lyra™Nasal Mask is intended for the delivery of air from either a CPAP or bi-level instrument (delivery device). The breathing circuit consists of the Lyra, which directly interfaces with the patient, and a pair of tubes, which connect the Lyra to the delivery device. The delivery device provides positive pressure air to the patient via the tubes and the Lyra™. Exhalation ports on the Lyra™ allows patient-exhaled gases to exhaust to the atmosphere.

The Lyra™ consists of the following:

• two nasal prongs, which are easily removed or installed into a mask body for the interchange of different sizes, and for easy cleaning of the device;
• adjustable head gear, which keeps the nasal mask in place during use;
• a pair of tubings, with one end of the tubings attached to the mask body;
• a standard 22-mm swivel which attached to the other end of the tubings.

The delivery device interfaces with the swivel via corrugated tubing, with a standard 22mm fitting.

The Lyra™ nasal prongs, made from a soft, flexible silicone, form a seal with the patient's nares. The nasal prongs come in different sizes for better and more comfortable fit for patients with varying nares sizes.

The Lyra™ is packaged, along with instructions for use and recommended cleaning instructions, in a poly bag. The Lyra™ can be completely disassembled for cleaning. Mild soap and water may be used to clean the device.

The provided text describes a medical device, the Lyra™ Nasal Mask, and its 510(k) submission for market clearance. While it discusses the device's description, intended use, and a comparison to a predicate device, it does not contain detailed information about a clinical study with specific acceptance criteria and performance metrics in the way that would typically be presented for an AI/ML device.

This submission is for a physical medical device (a nasal mask), and the "performance testing" described is much simpler and focuses on physical characteristics compared to a software-based diagnostic or prognostic device.

However, I can extract the information that is present and highlight what is missing based on your request.

Here's a breakdown based on the provided text:

Acceptance Criteria and Device Performance (Based on "LACK OF" detailed clinical study)

Missing Information (Not provided in the document for the Lyra™ Nasal Mask):

Many of your requested points relate heavily to the evaluation of AI/ML-based medical devices or more extensive clinical trials, which are not detailed in this 510(k) summary for a physical medical accessory.

1. Sample size used for the test set and the data provenance: Not applicable in the context of this device's "bench testing." The "test set" here refers to the actual physical devices tested, not patient data.
2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth for physical device parameters (like leak rates) in bench testing does not involve medical experts in the same way an AI diagnostic would.
3. Adjudication method: Not applicable for bench testing of a physical device.
4. If a multi-reader multi-case (MRMC) comparative effectiveness study was done: No, this is not mentioned. Such studies are typically for diagnostic AI systems.
5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable, as this is a physical device, not an algorithm.
6. The type of ground truth used: For physical parameters like leak rates and dead space, the "ground truth" would be objective measurements obtained through standardized bench testing methods, not expert consensus, pathology, or outcomes data.
7. The sample size for the training set: Not applicable, as this is not an AI/ML device that requires a training set.
8. How the ground truth for the training set was established: Not applicable for the same reason.

In summary: The provided text details a 510(k) submission for a physical nasal mask. The "study" proving it meets "acceptance criteria" is a comparative bench testing against a predicate device, focusing on physical parameters like leak rates, dead space, environmental performance, and cleaning. The primary "acceptance criterion" for 510(k) clearance in this context is demonstrating substantial equivalence to a legally marketed predicate device. The document explicitly states: "There are no known mandatory or voluntary performance standards applicable to this device classification."

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The Pegasus™ Nasal CPAP System is intended for treatment of Adult Obstructive Sleep Apnea (OSA). The Pegasus™ Nasal CPAP System is intended only for spontaneously breathing patients.

The Pegasus™ Nasal CPAP System is intended to provide a requlated and continuous positive airway pressure for the treatment of adult individuals suffering from obstructive sleep apnea (OSA). The positive pressure is clinicianadiustable within the designed operating range, as is enabling of the bar graph pressure indicator mode. User controls are On/Off switch, selecting the physician-enabled bar graph, viewing the real-time clock and setting of the real-time clock. The Pegasus™ is designed to be used with a 22-millimeter, smooth-bore air delivery hose and user- or physician-selected nasal or face mask. The Pegasus™ consists of a plastic enclosure that surrounds a power supply, impeller and motor, microprocessor, motor controller, display and switch inputs.

Acceptance Criteria and Device Performance Study

The provided document describes the Pegasus™ Nasal CPAP System and its safety and effectiveness summary for 510(k) clearance.

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state numerical acceptance criteria in a table format. However, it implicitly defines acceptance based on compliance with device specifications and internationally accepted standards.

2. Sample Size and Data Provenance

The document states "Performance testing was conducted in the laboratory." It does not specify a distinct "test set" in terms of subject or patient data. The testing appears to be based on evaluating the device's functional performance against its specifications and relevant standards.

• Sample Size for Test Set: Not applicable as the testing described is functional and compliance-based, not involving a patient test set.
• Data Provenance: Not applicable. The testing was laboratory-based.

3. Number and Qualifications of Experts for Ground Truth

• Number of Experts: Not applicable. The ground truth for this type of device (functional performance, electrical safety, EMC) is established through engineering and regulatory standards, not expert clinical consensus on patient data.
• Qualifications of Experts: The testing was performed by a "Nationally Recognized Testing Laboratory (NRTL)," implying qualified engineers and technicians experienced in electrical safety and EMC testing conducted the evaluation.

4. Adjudication Method

• Adjudication Method: Not applicable. The nature of the performance testing (functional compliance, electrical/EMC standards) does not involve adjudication of expert opinions.

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

• MRMC Study: No, a multi-reader multi-case comparative effectiveness study was not done. This device is a therapeutic device (CPAP system), not an diagnostic imaging or AI-driven interpretive system that would typically involve human readers.

6. Standalone (Algorithm Only) Performance

• Standalone Performance: Not applicable. The Pegasus™ Nasal CPAP System is a hardware device with embedded software for control, not a standalone algorithm/AI system in the sense of predictive or interpretive software. Its "performance" refers to its physical functioning and adherence to engineering specifications.

7. Type of Ground Truth Used

• Type of Ground Truth: The ground truth used was based on device specifications and internationally accepted standards for electrical safety and electro-magnetic compatibility.

8. Sample Size for Training Set

The document does not mention a "training set" as it is typically understood in the context of machine learning or AI models. This device is a hardware-based medical device.

• Sample Size for Training Set: Not applicable.

9. How Ground Truth for Training Set Was Established

• How Ground Truth for Training Set Was Established: Not applicable.

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The Hi-Ox® High FiO2 Mask is intended to deliver high inspired oxygen concentrations to patients who require elevated inspired oxygen.

The HI-Ox80 is an oxygen mask to enable patients to inhale high concentrations of oxygen at moderate flow rates of 8 -10 |pm. It is a simple device consisting of a central manifold section where the patient mask, oxygen tubing and an oxygen reservoir bag attach. The triple valving in the manifold directs the oxygen to the patient and acts as an anti-asphyxiation valve removing the need for ventilation holes in the mask itself, thus allowing for delivery of high FiO2's.

Oxygen from the supply is either delivered to the patient via a one-way valve (inhalation valve) or stored temporarily in the oxygen reservoir bag. During exhalation, expired gas is directed to the atmosphere via another one-way valve (exhalation valve). In the event the patient's minute ventilation exceeds the oxygen supply flow rate, a third sequential dilution valve allows ambient air to get drawn into the inspired limb of the manifold eliminating the potential for asphyxiation.

The inhalation and exhalation one way valves are designed to have very low flow resistance (less than 1,5 cmH,O, typically ~ 1.07 cmH2O at flow rates of 60 lpm) to minimize the work of breathing. The sequential dilution valve is specified to be less than 3 cmH2O/U/sec. The oxygen mask is made of a soft material for conformance to the patient's facial contours. Positioning of the manifold connection on the mask minimizes the effective deadspace.

Here's an analysis of the provided text regarding the Hi-Ox® High FiO2 Mask, focusing on acceptance criteria and the study used to demonstrate compliance.

Hi-Ox® High FiO2 Mask - Acceptance Criteria and Supporting Study

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 the sample size for the tests performed. It mentions "experiments conducted using a SensorMedics 229 metabolic measurement system." It does not specify the number of subjects or runs.

The data provenance is not explicitly stated regarding country of origin. The company is SensorMedics Corporation, located in Yorba Linda, CA, USA. This suggests the tests were likely conducted in the USA. The study design appears to be prospective as it describes direct experimentation to measure product performance.

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

There is no mention of experts being used to establish a ground truth with regard to the performance metrics (FiO2, flow resistance). The measurements for these criteria seem to be objective, instrument-based readings. For the "work of breathing," subjective testing was performed, but the number or qualifications of individuals providing this feedback are not specified.

4. Adjudication Method for the Test Set

No adjudication method is mentioned as the reported performance seems to be based on direct measurements and objective criteria, not on expert consensus or interpretation requiring adjudication.

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 device is not an AI-powered diagnostic or interpretive tool. Therefore, an MRMC comparative effectiveness study involving human readers and AI assistance is not applicable and was not performed.

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

This device is a physical medical device (oxygen mask), not an algorithm or software. Therefore, a standalone algorithm-only performance study is not applicable and was not performed.

7. The Type of Ground Truth Used

The ground truth for the performance criteria (FiO2, flow resistance) was based on objective, instrument-based measurements. For the "work of breathing," it was based on subjective patient feedback.

8. The Sample Size for the Training Set

This device does not involve machine learning or AI, so there is no training set and therefore no sample size for such a set.

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

As there is no training set, this question is not applicable.

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The SomnoStar a Series Sleep System is intended to assist the user in diagnosing patients with sleep disorders by collecting physiological data from a sleeping patient, assisting the user in performing analysis of sleep data, and printing a hard-copy report of these data.

The SomnoStar a Series Sleep System is indicated for use to assist the user(s) In diagnosing patients with sloep disorders; by collecting physiological data from a sleeping patient, assisting the user(s) in performing analysis of sleep data and printing a hard copy of these data. The data is collected, staged and scored with a computerassisted program.

The SomnoStar a Sleep System receive Input from bio-physical amplifiers, analyze these data according to software programs designed for use on computer systems included in the system configuration and output data in the form of reports generated by the printer option to the systems. Various components of the systems can be designed into already-existing sleep laboratories. A more detailed description is contained in the Operator's Manual.

In use, the SomnoStar a Series Sleep System receives input from optional bloghysical amplifiers, up to 32 channels in each, which is converted from analog to digital data and stored in a computer storage medium.

The provided document is a 510(k) premarket notification for the SomnoStar Alpha Series Sleep System. It mainly focuses on demonstrating substantial equivalence to a predicate device and does not contain detailed information on specific acceptance criteria and a study proving those criteria.

However, based on the provided text, here's what can be inferred and what is explicitly stated:

1. A table of acceptance criteria and the reported device performance

The document does not provide a table of acceptance criteria or specific performance metrics. The primary claim is substantial equivalence to the SensorMedics 4000 Series Sleep System (K915856). The key difference mentioned is the inclusion of an optional bio-physical amplifier, the Cephalo Pro, which replaces either the AmpStar or Dynagraph II bio-physical amplifiers.

Reported Device Performance:
"Because there are no performance differences caused by using the Caphalo Pro, no additional clinical or non-clinical tests were performed or submitted in the premarket notification."
This implies that the performance of the new device (SomnoStar Alpha Series with Cephalo Pro) is considered to be the same as the predicate device (SensorMedics 4000 Series Sleep System). Therefore, the "reported device performance" is essentially that it functions equivalently to the established predicate.

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

Not applicable. The document explicitly states: "Because there are no performance differences caused by using the Caphalo Pro, no additional clinical or non-clinical tests were performed or submitted in the premarket notification." This means there was no new test set generated for this 510(k) submission. The equivalence relies on the established performance of the predicate device.

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)

Not applicable, as no new test set was generated or evaluated. The ground truth would have been established for the predicate device, but details are not provided here.

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

Not applicable, as no new test set was generated or evaluated.

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 a sleep analysis system, not an AI-assisted diagnostic tool for human readers in the context of an MRMC study. It collects and assists in analyzing physiological data.

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

This refers to the device's ability to collect and display data, and "assisting the user in performing analysis of sleep data." The device itself is a "Sleep Analysis System." The claim of "no performance differences" implies that its standalone function (data collection, analysis assistance, reporting) is equivalent to the predicate device. However, a dedicated standalone study proving this for the new iteration is stated as not performed since the change was a component swap with no performance impact.

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

For the predicate device, the implied "ground truth" would likely involve expert consensus among sleep specialists (polysomnographers) for the proper staging and scoring of sleep data, validated by clinical use and potentially comparisons to established sleep disorder diagnoses. However, for this 510(k), no new ground truth was established as no new tests were performed.

8. The sample size for the training set

Not applicable. This is not a machine learning or AI-driven device in the sense of needing a "training set" for an algorithm to learn from data. It's a system for collecting and analyzing pre-defined physiological signals.

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

Not applicable, as there is no "training set" in the context of this device.

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The SensorMedics SiPAP Infant Nasal CPAP Circuit, consisting of a pressure generator, Nasal CPAP Prongs and Masks, is intended to provide CPAP for use in hospitals to treat newborns and infants with RDS or who are recovering from RDS.

Detailed description of the device circuit is contained in the SiPAP Infant Nasal CPAP Operator's Instructions.

This document describes a 510(k) submission for the SiPAP Infant Nasal CPAP Circuit. The submission claims substantial equivalence to previously cleared devices.

Here's an analysis of the provided information regarding acceptance criteria and the study that proves the device meets them:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: The document explicitly states: "no additional clinical or non-clinical tests were performed or submitted in the premarket notification." This means there was no new test set for this specific 510(k) submission. The evaluation relies on data from the predicate devices.
• Data Provenance: The data provenance is from the studies conducted for the predicate devices (K960359, K945740, K974303, K984254, and K991972). The document instructs to "Refer to 510(k) numbers s K960359 and K945740 for this data," implying that the original testing for those devices established the safety and effectiveness. The nature of these original studies (retrospective or prospective, country of origin) is not detailed in this document.

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

• Not Applicable. Since no new clinical or non-clinical tests were conducted for this submission, there was no new test set requiring new ground truth establishment or expert involvement for this specific 510(k) submission. The original predicate device studies would have had such experts, but their details are not provided here.

4. Adjudication Method for the Test Set

• Not Applicable. As no new test set was used, no new adjudication method was employed for this submission.

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

• No. A MRMC comparative effectiveness study was not conducted for this 510(k) submission. The basis for clearance is substantial equivalence, not a new comparative effectiveness trial demonstrating improvement with or without AI assistance (which is not relevant for this device type).

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

• No. This device is a mechanical CPAP circuit, not an AI algorithm. Therefore, a standalone algorithm performance study is not applicable and was not performed.

7. Type of Ground Truth Used

• The implicit "ground truth" for the substantial equivalence claim comes from the established safety and effectiveness of the predicate devices. This would have been based on performance data and potentially clinical outcomes from the studies supporting the original predicate device clearances. The specific type of ground truth (e.g., direct patient outcomes, expert clinical assessment of device function, etc.) from those prior studies is not detailed in this document.

8. Sample Size for the Training Set

• Not Applicable. This device is a mechanical medical device, not an AI/ML algorithm 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 this type of device, ground truth establishment for a training set is not relevant.

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The SensorMedics Infant Flow System, consisting of a Driver and NCPAP Prongs, is intended to provide CPAP for use in hospitals to treat newborns and infants with RDS or who are recovering from RDS.

Infant Flow System, consisting of a Driver and NCPAP Prongs

I am sorry, but the provided text does not contain the information requested in the prompt. The document is a 510(k) clearance letter from the FDA for the "Infant Flow System" and an "Indications for Use" statement. It does not include details about acceptance criteria, device performance studies, sample sizes, expert qualifications, adjudication methods, or ground truth establishment.

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The SensorMedics Infant Flow Nasal CPAP Mask is intended for use with the SensorMedics Infant Flow System, consisting of a Driver and NCPAP Generator. It is intended to provide CPAP with a nasal mask for use in hospitals to treat newborns and infants with RDS or who are recovering from RDS.

The SensorMedics Infant Flow Nasal CPAP Mask is a silicone mask that fits into the generator of the Infant Flow System in place of the standard nasal prongs.

The provided text refers to a 510(k) premarket notification for the "Infant Flow Nasal CPAP Masks." This is a medical device submission seeking clearance based on substantial equivalence to predicate devices, rather than a de novo submission requiring extensive clinical trials to prove efficacy. Therefore, much of the requested information (like acceptance criteria, specific device performance metrics, large-scale clinical study details, MRMC studies, ground truth establishment for training, etc.) is not present in the provided document.

Here's an analysis based on the available information:

Key Takeaway: The submission leverages the existing clearances of similar CPAP systems and states that no additional clinical tests were performed because the mask's function is the same as the already cleared prongs in the Infant Flow System, with only differences in facial mounting and labeling. The core argument for equivalency relies on non-clinical testing demonstrating no differences in safety or effectiveness when using the mask compared to the prongs.

1. Table of Acceptance Criteria and Reported Device Performance

No specific quantitative acceptance criteria or detailed performance metrics are provided in the document. The basis for clearance is substantial equivalence, primarily supported by the argument that the mask functions identically to already cleared components within the same system.

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

• Sample Size: Not applicable in the context of a clinical test set as described in the prompt. The document explicitly states: "Because there are no differences other than facial mounting and labeling between the SensorMedics Infant Flow System prongs and the SensorMedics Infant Flow Mask, no additional clinical tests were performed or submitted in the premarket notification."
• Data Provenance: The "non-clinical testing" mentioned is not detailed, so its provenance (country of origin, retrospective/prospective) is unknown. It's likely internal lab testing.

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

• Not applicable. No clinical test set with ground truth established by experts is described for this specific device (the mask). The determination of safety and effectiveness relied on "non-clinical testing" and a claim of functional equivalence to previously cleared devices/components.

4. Adjudication Method for the Test Set

• Not applicable. No clinical test set requiring expert adjudication is described for this device.

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 a nasal CPAP mask, not an AI diagnostic or assistive technology for human readers. No MRMC study was conducted or is relevant.

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

• Not applicable. This device is a physical medical device (mask), not an algorithm or AI system.

7. The Type of Ground Truth Used (Expert Consensus, Pathology, Outcomes Data, etc.)

• Not applicable for this specific device's clearance. The "ground truth" for the clearance of the mask was the established safety and effectiveness of the predicate devices and the existing prongs within the Infant Flow System, as determined by previous FDA clearances (K962848, K974303, K960359, K945740). The current submission relies on non-clinical testing to demonstrate the mask's equivalence to those established components.

8. The Sample Size for the Training Set

• Not applicable. This device is a physical medical device, not an AI system that requires a training set.

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

• Not applicable. As above, no training set for an AI system is involved.

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The indications for use are the same as the Vmax Series to which this product is an option. Quotation from the Indications for Use section of the Vmax premarket notification: "Basically, this involves performing physicianprescribed pulmonary function and metabolic testing. More-specific intended uses are shown in the table below, along with the predicate SensorMedics product model with the same intended-use labeling."

The Static and Dynamic Compliance option is indicated specifically for Evaluation of medication effects, Pulmonary Function testing in adults & children, Pulmonary disability evaluation, Industrial surveillance and Bedside lung function.

The Static and Dynamic Compliance software product option is identical in safety and effectiveness to the predicate devices listed in the last section. The technique of placing an esophageal balloon and derived measurements are also the same as the predicate devices.

Static and dynamic compliance are measurements of pulmonary function. also commonly referred to as Respiratory Mechanics. The mechanical properties of the respiratory system are important to breathing effectively. In healthy people, the elastic recoil and compliance of the lung are easily managed by the respiratory muscles allowing normal breathing. In some common respiratory diseases, there are changes in recoil and compliance. Static and dynamic compliance are easily measured and can be valuable in determining the effects of lung disease on breathing.

Static and dynamic compliance are performed by having the patient swallow an esophageal balloon that is connected to a calibrated pressure transducer, The patient breathes quietly on a mouthpiece connected to a flow meter. while mouth pressure, esophageal pressure, flow rate and volume changes are measured. The balloon is placed in the esophagus just above the diaphragm. This position is determined by having the patient breath through a flow meter, while the operator views a display of esophageal pressure, inspiratory flow and expiratory flow on a computer monitor. The operator looks for a negative pressure-tracing concomitant to a positive flow tracing. If the pressure tracing is positive, the balloon has passed the level of the diaphragm and needs to be pulled back until a positive tracing is displayed.

When measurements are made under no-airflow conditions, Static Compliance is calculated. When the measurements are made under flow conditions, Dynamic Compliance is calculated.

The provided text describes the Static and Dynamic Compliance software product option and states it is "identical in safety and effectiveness to the predicate devices listed in the last section." It also notes that "The technique of placing an esophageal balloon and derived measurements are also the same as the predicate devices."

However, the document does not describe a study to prove the device meets acceptance criteria. Instead, it relies on substantial equivalence to predicate devices. Therefore, I cannot generate a table of acceptance criteria with reported device performance or information about a specific study for this device.

Here's what I can extract based on the provided text, highlighting the absence of a study and related details:

1. A table of acceptance criteria and the reported device performance: Not available. The document asserts identity to predicate devices rather than presenting specific acceptance criteria and performance data for the device itself.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective): Not applicable. No new study testing the device's performance is described.

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): Not applicable. No new study testing the device's performance is described.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable. No new study testing the device's performance is described.

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 diagnostic tool; it's software for pulmonary function measurements. No MRMC study is mentioned.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. No standalone performance study details are provided.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc): Not applicable. No new study testing the device's performance is described.

8. The sample size for the training set: Not applicable. This is not an AI/ML device that requires a training set in the conventional sense. Its functionality is based on established physiological measurements and calculations.

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

In summary, the document does not contain details of a de novo study or performance data for this specific device. It establishes substantial equivalence to predicate devices, inferring that its performance matches those established devices.

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