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NuvoAir Air Next is intended to test lung function and spirometry in adults and children 5 years of age and older.

It can be used in hospitals, in the clinical setting, and at home.

The Air Next is not intended for use in an operating room.

The user is not intended to interpret or take clinical action based on the device output without consultation of a qualified healthcare professional.

Air Next is intended to perform basic lung function and spirometry testing. It measures parameters such as the forced expiratory volume in 1 sec (FEV1) and the forced vital capacity (FVC) in a forced expiratory maneuver. These measures can be used for detection, assessment and monitoring of diseases affecting the lung function, such as bronchial Asthma, COPD and Cystic Fibrosis.

Air Next is a hand-held spirometer, weighing 75g and it is powered by 2 AAA alkaline 1.5V batteries. It consists of 3 main components: the Air Next device, the NuvoAir disposable turbine (delivered in one package) and the Air Next mobile application downloadable from Apple's and Google's Play Stores.

The provided text describes the 510(k) premarket notification for the "Air Next" diagnostic spirometer. While it extensively details the device's characteristics, comparison to a predicate device, and compliance with various standards (electrical safety, EMC, usability, biocompatibility), it does not contain a specific section detailing acceptance criteria for performance, nor a study report proving the device meets these criteria with quantitative results from a test set.

The document states that the device "Meets ATS accuracy requirements" and "Air Next complies with the currently recognized safety and EMC standards," but it does not provide the measured performance data or the specific acceptance criteria in a quantifiable table as requested.

However, based on the information provided, we can infer some criteria and the general approach:

Inferred Acceptance Criteria based on Comparison to Predicate and Standards:

The document repeatedly references compliance with ISO 26782:2009 for spirometers and the Standardization of Spirometry 2019 Update (ATS/ERS guidelines). These standards and guidelines define accuracy requirements for spirometry parameters.

From the "SUMMARY OF TECHNOLOGICAL CHARACTERISTICS AND COMPARISON TO PREDICATE DEVICE" table, we can infer the acceptance criteria are likely to match or exceed the predicate device's performance and meet the relevant standards for the following parameters:

• Volume accuracy: ±3% of reading or ±0.050 L, whichever is greater
• Flow accuracy: ±5% or 200 mL/s (likely for PEF)
• Flow resistance: <0.5 cmH2O/L/s
• Volume range: Up to 10 L
• Flow range: 0-15L/s (for Air Next, predicate 0-16 L/s)

Regarding the Study Proving Device Meets Acceptance Criteria:

The document mentions that the device "Meets ATS accuracy requirements" and "Air Next complies with the currently recognized safety and EMC standards." This implies that testing was performed against these standards. However, the specific details of the performance study (methodology, results, sample size of test set, ground truth derivation, expert involvement, etc.) are not explicitly provided in the given text.

Therefore, many parts of your request cannot be answered from the provided document.

Here's a breakdown of what can be extracted or inferred, and what is missing:

1. Table of Acceptance Criteria and Reported Device Performance:

Missing: Specific quantitative results (e.g., actual measured accuracy values, standard deviations, confidence intervals) from a dedicated performance study. The table above only re-states the specifications it claims to meet.

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

• Sample Size: Not specified in the provided text.
• Data Provenance: Not specified (e.g., country of origin, retrospective/prospective). The testing would likely be bench testing against calibrated flow/volume simulators rather than human subject data for primary accuracy claims, but specifics are missing.

3. Number of Experts and Qualifications for Ground Truth:

• Not Applicable / Not Specified: For spirometers, primary accuracy testing is typically done using mechanical test lungs and known volume/flow outputs, calibrated against highly accurate reference devices, rather than human experts establishing "ground truth" for each measurement in a test set. This type of device does not involve expert interpretation of images or signals in the same way an AI-powered diagnostic device would.

4. Adjudication Method for the Test Set:

• Not Applicable / Not Specified: Adjudication is typically for subjective expert evaluations (e.g., image review), which does not directly apply to the objective, quantitative measurements of a spirometer's mechanical accuracy.

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

• No: The document does not describe an MRMC study. This type of study is more common for diagnostic AI systems where human reader performance is a key variable. The Air Next is a measurement device.

6. Standalone Performance (Algorithm Only without Human-in-the-Loop):

• Yes, implied for Device Accuracy: The core performance measurements (volume, flow accuracy) are inherent to the device and its algorithms, independent of human interaction beyond operating it. The device itself (Air Next) calculates the spirometry parameters (FEV1, FVC, etc.) based on the turbine's readings. The stated compliance with ISO 26782 implies standalone algorithmic performance testing.
• Missing: Details of this standalone performance test.

7. Type of Ground Truth Used:

• Inferred: Reference Standards/Calibrated Outputs: For spirometers, the ground truth is established by using highly accurate, calibrated flow and volume generators (e.g., syringes or flow controllers) that produce known, precise airflows and volumes. These are the gold standard for verifying spirometer accuracy according to ISO 26782 and ATS/ERS guidelines.
• Not: Expert consensus, pathology, or outcomes data, as these are not relevant to the primary function of a spirometer.

8. Sample Size for the Training Set:

• Not Applicable / Not Specified: This device measures physical parameters (airflow, volume) using a turbine and a digital infrared interruption sensor, not a machine learning model that requires a "training set" of data in the common sense. Its "algorithm" is a conversion from rotations to airflow. If there is any internal calibration or minor adjustment based on manufacturing tolerances, it would be done during production, not through a "training set" in the AI/ML context.

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

• Not Applicable / Not Specified: As explained above, there's no "training set" in the typical AI/ML sense for this device. The physical principle of operation and conversion algorithms are based on established physics and engineering, and then verified against calibrated standards.

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Air Next is intended to be used by:

Healthcare professionals trained to perform spirometry tests on patients of age ≥ 5 years old, > 10 kg and > 110 cm.

Air Next is intended to perform basic lung function and spirometry testing. The actual diagnosis shall be done by a healthcare professional in hospital and clinical settings.

Air Next is intended to perform basic lung function and spirometry testing. It measures parameters such as the forced expiratory volume in 1 sec (FEV1) and the forced vital capacity (FVC) in a forced expiratory maneuver. These measures can be used for detection, assessment and monitoring of diseases affecting the lung function, such as bronchial Asthma, COPD and Cystic Fibrosis.

Air Next is a hand-held spirometer, weighing only 75g and it is powered by 2 AAA alkaline 1.5V batteries. lt consists of 3 main components: the Air Next device, the NuvoAir disposable turbine (delivered in one package) and the Air Next mobile application downloadable from Apple's and Google's Play Stores. The package includes one Air Next device, one NuvoAir disposable turbine through which the user can start using the Air Next, two AAA 1.5V alkaline batteries, one user manual and one cotton bag to carry the device. Dimensions of the Air Next are 98 x 62 x 26 mm, which can be seen in the engineering drawing in the attachments.

Here's an analysis of the provided text regarding the acceptance criteria and supporting studies for the Air Next spirometer, structured according to your request:

1. Table of Acceptance Criteria and Reported Device Performance

The document states that the Air Next spirometer meets ATS/ERS 2005 guidelines and ISO standards for spirometers. The performance of the Air Next related to specific technical specifications is compared directly to the predicate device, implying these represent the acceptance criteria derived from industry standards.

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

The document does not explicitly state a sample size for the test set for the spirometry performance characteristics (volume, flow accuracy, etc.). The performance testing described primarily refers to adherence to international standards and direct comparison of specifications with a predicate device.

The data provenance is not specified in terms of country of origin or whether it was retrospective or prospective. The testing appears to be primarily lab-based performance verification against established standards rather than clinical data from human subjects.

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

This information is not provided in the document. The ground truth for the device's technical performance metrics (volume, flow accuracy, etc.) is established by recognized international standards (ATS/ERS 2005, ISO 26782, ISO 23747) and likely verified using calibrated testing equipment. There's no mention of human experts defining ground truth for these quantitative measurements.

4. Adjudication Method for the Test Set

Adjudication methods (e.g., 2+1, 3+1) are typically used in studies involving human interpretation or subjective assessments. Since the performance testing focuses on objective technical measurements verified against standards, an adjudication method for a "test set" in this context is not applicable and not mentioned.

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

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done or reported. The device is a diagnostic spirometer for basic lung function testing, not an AI-assisted diagnostic imaging device that would typically involve MRMC studies to assess human reader improvement with AI.

6. Standalone Performance Study

Yes, a standalone performance assessment was conducted. The "Performance Testing" section describes various tests against international standards (IEC 60601-1, IEC 60601-1-6, IEC 62366, IEC 60601-1-2) and the ATS/ERS 2005 guidelines. It also explicitly states that the device was tested against B.T.P.S. conditions and that "results are well within range."

The technical specifications for volume and flow accuracy are presented as direct measurements or capabilities of the device itself. While there is a comparison to a predicate device, the Air Next's own performance against these metrics constitutes standalone testing.

7. Type of Ground Truth Used

The ground truth used for the device's performance is based on established international standards and guidelines for spirometry. Specifically, the ATS/ERS 2005 guideline, EN ISO 26782:2009 (Anesthetic and respiratory equipment – Spirometers), and EN ISO 23747:2015 (Peak expiratory flowmeters) are cited. These standards define the acceptable ranges and methodologies for measuring spirometry parameters accurately.

8. Sample Size for the Training Set

This document does not describe any machine learning or AI components that would require a "training set". The Air Next is a hardware device with firmware that converts rotations into airflow measurements. Therefore, a training set sample size is not applicable in the context described.

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

As there is no mention of a training set for machine learning/AI, the method for establishing its ground truth is not applicable. The device's functionality relies on physical principles and standard conversion algorithms, not learning from data.

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The Comarch e-Care Platform is intended to connect with physiological measurement devices (weight scales, blood pressure meters, pulse oximeters, peak flow meters, thermometers, glucometers) intended to use at home and send the measurement results to central server. Comarch e-Care Platform serves as Software as a Medical Device and can be used only with FDA cleared measurement devices.

Comarch e-Care Platform displays the collected measurements on the Web application and securely stores them in a database server, where the caregiver can view them, leave comments and contact patient if necessary. Caregivers are able to set thresholds individually for each patient. Measurement results sent to e-Care Platform from connected devices are analyzed and if result is beyond the threshold, caregiver gets the notification.

The Comarch e-Care Platform is not interpretive, nor is it intended for diagnosis or as a substitute for medical care, and it is not intended to provide real time data. It is made available to patients when time-critical care is not required.

The Comarch e-Care Platform is contraindicated for patients requiring direct - medical supervision or emergency intervention. It is intended for patients who are willing and capable of managing its use. Clinical judgment and experience by a caregiver are required to check and interpret the information delivered.

Comarch e-Care Platform is a software intended for use in remote patient monitoring outside of traditional healthcare settings (e.g. at home). Components of Comarch e-Care Platform are: Comarch SMA application, Comarch e-Care application, application server, database server.

Comarch SMA is a software application intended to use by patients. It is designed to collect, display and transmit vital sign measurements captured from commercially available home monitoring devices.

The following vital signs are collected: temperature, glucose, noninvasive blood pressure, pulse oximetry, weight and spirometry.

The Comarch e-Care Platform is a software intended for use in remote patient monitoring outside of traditional healthcare settings (e.g. at home). It connects with physiological measurement devices (weight scales, blood pressure meters, pulse oximeters, peak flow meters, thermometers, spirometers, glucometers) and sends the measurement results to a central server. The platform displays collected measurements on a web application, securely stores them, and allows caregivers to view and analyze them, leave comments, and contact patients. Caregivers can set individual thresholds for each patient, and the platform notifies the caregiver if a measurement result is beyond the set threshold. The device is not interpretive, not intended for diagnosis or as a substitute for medical care, and does not provide real-time data. It is for patients who are able and willing to manage its use, and clinical judgment by a caregiver is required to interpret the information.

Here's an analysis of the acceptance criteria and supporting study information:

1. Table of Acceptance Criteria and Reported Device Performance:

The provided document does not explicitly present a table of quantitative acceptance criteria for device performance. Instead, the substantial equivalence determination for the Comarch e-Care Platform is based on similarities to predicate devices in terms of:

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

The document states that "no clinical tests were conducted." Therefore, there is no specific test set or data provenance mentioned for clinical performance evaluation. The evaluation was based on non-clinical verification and validation.

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)

Since no clinical tests were conducted and no specific test set-based ground truth was established, this information is not applicable and not provided in the document.

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

Since no clinical tests were conducted and no test set ground truth was established by experts, this information is not applicable and not provided.

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

The document explicitly states "no clinical tests were conducted." Therefore, no MRMC comparative effectiveness study was done, and no effect size regarding human reader improvement with/without AI assistance is provided.

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

The substantial equivalence is based on the device's functional similarities to predicate devices in remote patient monitoring, data transmission, storage, and caregiver notification, rather than a standalone performance evaluation of a diagnostic algorithm. The device itself is described as "not interpretive" and "not intended for diagnosis." The non-clinical verification and validation focused on the software's functionality and adherence to design specifications. Therefore, a standalone performance study in the context of diagnostic accuracy was not performed for this device.

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

As no clinical tests were performed, there was no "ground truth" derived from patient data, expert consensus, pathology, or outcomes data for the purpose of validating diagnostic or interpretive accuracy. The "ground truth" for the non-clinical verification and validation would have been the design specifications and requirements of the software.

8. The sample size for the training set

The document states "no clinical tests were conducted." This implies that the device did not undergo a process involving a "training set" for machine learning model development in the context of clinical performance. The platform's functionality is about data handling and alerts based on pre-set thresholds, not on learning from a dataset to perform interpretations. Therefore, this information is not applicable and not provided.

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

As no training set was used for clinical performance evaluation, this information is not applicable and not provided.

In summary, the Comarch e-Care Platform's acceptance was based on a demonstration of substantial equivalence to existing predicate devices through comprehensive non-clinical verification and validation testing, ensuring the software's functionality, adherence to design specifications, and addressing identified risks. No clinical studies or performance evaluations requiring test sets, ground truth establishment, or expert adjudication were conducted, as the device is not interpretive and does not provide diagnostic insights.

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