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The intended use of the Apieron INSIGHT™ eNO System is to quantitatively measure exhaled nitric oxide (eNO) in expired human breath as a marker of inflammation in persons with asthma. Measurement of eNO in expired human breath by the Apieron INSIGHT eNO System is a non-invasive, simple and safe method to measure a decrease in eNO in asthma patients that often occurs after treatment with anti-inflammatory pharmacological therapy as an indication of the therapeutic effects in patients with elevated eNO levels. The Apieron INSIGHT eNO System is suitable for use in children ages 8 to 17 years of age, and in adults 18 years of age and older. eNO measurements, as an adjunct to established clinical assessments, provide the physician an objective marker to evaluate the patient's response to anti-inflammatory therapy. The Apieron INSIGHT eNO System can be used by trained operators in a physician's office laboratory setting. The Apieron INSIGHT eNO System should not be used in critical care, emergency care or in anesthesiology.

The proposed Apieron INSIGHT™ eNO System consists of a Monitor, a multi-use disposable Sensor Cartridge and the same disposable test supplies as the cleared device. The only difference between the proposed devices and the cleared device is that the single-use disposable eNO Sensor Cartridge of the INSIGHT System has been tested and proven to support up to 10 patient uses and 5 QC tests. A modification has been made to the software which will allow for counting the uses of the Sensor Cartridge and prevention of uses beyond the specified limits. Two sensors are being proposed for clearance one for 10 patient uses and 5 QC tests and one for 5 patient uses and 5 QC tests. The Monitor functions the same and contains the same measurement and breath sampling hardware to provide for a user-friendly interface guiding the operator through the test sequence and the patient through the breath sampling maneuver. The 10-use and the 5-use disposable Sensor Cartridges contain the same Biosensor as in the cleared device which changes its optical transmission properties when it reacts with the nitric oxide in the breath sample. Apart for some software changes to deal with the number of sensor uses, and the addition of more air purges between tests to clear the sensor of nitric oxide from the previous test, the proposed Apieron INSIGHT eNO System is unchanged. It is transportable, operated by an AC outlet and designed for use with the Sensor Cartridge. The proposed Apieron INSIGHT eNO System has the same indication for use as the predicate device, the Apieron INSIGHT eNO System (K073265).

This document describes the Apieron INSIGHT™ eNO System, a device for quantitatively measuring exhaled nitric oxide (eNO) in human breath as a marker of inflammation in persons with asthma. The submission is a 510(k) for a modified version of an already cleared device (K073265), with the primary change being that the disposable sensor cartridge can now support multiple uses (10 patient uses and 5 QC tests, or 5 patient uses and 5 QC tests).

Here's the information regarding acceptance criteria and the study:

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not provide a specific table of acceptance criteria with numerical targets for device performance (e.g., accuracy, precision, limits of detection). Instead, the submission focuses on establishing substantial equivalence to a predicate device.

The reported device performance is implicitly that the modified device, with its multi-use sensor cartridge and minor software changes, performs equivalently to the predicate device.

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

The document explicitly states: "All necessary bench testing was conducted on the proposed Apieron INSIGHT™ eNO System to support a determination of substantial equivalence to the predicate device."

• Sample Size for Test Set: The specific number of samples (e.g., breath measurements, sensor cartridges) used in the bench testing is not provided in this summary.
• Data Provenance: The document does not specify the country of origin of the data or whether the testing was retrospective or prospective. Given it is "bench testing," it implies controlled laboratory conditions rather than clinical data from human subjects in a real-world setting.

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

This information is not provided in the document. The testing described is bench testing focusing on comparing the modified device's technical performance to its predicate, rather than clinical performance requiring expert ground truth for patient outcomes.

4. Adjudication Method for the Test Set:

This information is not provided. The nature of "bench testing" for substantial equivalence typically involves direct comparison of measurements and functionalities, rather than adjudication of interpretations that would be required in clinical studies.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size:

No, an MRMC comparative effectiveness study was not done. The submission focuses on establishing substantial equivalence through bench testing of the modified device's components and functionality against its own predicate device. There is no mention of human readers or AI assistance in this context.

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

The device is a "Breath Nitric Oxide Test System" which quantifies eNO. It's a measurement device, not an algorithm that makes diagnostic interpretations. Therefore, the concept of "standalone performance" in the context of an algorithm's diagnostic accuracy is not applicable here. The device's performance is its ability to accurately measure eNO, which is assessed through bench testing, not through an algorithm's diagnostic output.

7. The Type of Ground Truth Used:

For this type of device (a measurement system demonstrating substantial equivalence), the "ground truth" for bench testing would typically involve:

• Known concentrations: For accuracy testing, the device would be challenged with known, controlled concentrations of nitric oxide.
• Predicate device measurements: For equivalency, the modified device's measurements would be compared directly to the predicate device's measurements under controlled conditions.
• Functional specifications: Verification that software correctly counts uses, and that the sensor still changes optical properties as expected.

The document does not explicitly detail the specific "ground truth" used, but these are typical in such bench testing scenarios. It is not based on expert consensus, pathology, or outcomes data in the clinical sense, as it’s a technical equivalency claim.

8. The Sample Size for the Training Set:

This information is not applicable/not provided. The device is a measurement system; it does not appear to involve machine learning or AI algorithms that require a "training set" in the conventional sense. The software modification mentioned ("counting the uses of the Sensor Cartridge and prevention of uses beyond the specified limits") is a functional modification, not a data-driven learning algorithm.

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

This information is not applicable/not provided for the same reason as point 8.

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The intended use of the Apieron INSIGHT™ eNO System is to quantitatively measure exhaled nitric oxide (eNO) in expired human breath as a marker of inflammation in persons with asthma. Measurement of eNO in expired human breath by the Apieron INSIGHT eNO System is a non-invasive, simple and safe method to measure a decrease in eNO in asthma patients that often occurs after treatment with anti-inflammatory pharmacological therapy as an indication of the therapeutic effects in patients with elevated eNO levels. The Apieron INSIGHT eNO System is suitable for use in children ages 8 to 17 years of age, and in adults 18 years of age and older. eNO measurements, as an adjunct to established clinical assessments, provide the physician an objective marker to evaluate the patient's response to anti-inflammatory therapy. The Apieron INSIGHT eNO System can be used by trained operators in a physician's office laboratory setting. The Apieron INSIGHT eNO System should not be used in critical care, emergency care or in anesthesiology.

The Apieron INSIGHT™ eNO System consists of a Monitor, a single-use disposable Sensor Cartridge and other disposable test supplies. The Monitor contains the measurement and breath sampling hardware and provides a user-friendly interface to guide the operator through the test sequence and guide the patient through the breath sampling maneuver. The disposable Sensor Cartridge contains a Biosensor that changes its optical transmission properties when it reacts with the nitric oxide in the breath sample. The Apieron INSIGHT eNO System is transportable, operated by an AC outlet and designed for use with the disposable Sensor Cartridge.

The provided text does not contain detailed information regarding specific acceptance criteria, performance metrics, or the study design with the level of detail requested for each point. The document is a 510(k) summary, which generally focuses on establishing substantial equivalence to a predicate device rather than providing exhaustive clinical study results.

Here's an analysis based on the available information:

1. Table of Acceptance Criteria and Reported Device Performance:

The document explicitly states: "All necessary bench and clinical testing was conducted on the Apieron eNO System to support a determination of substantial equivalence to the predicate device." However, specific quantitative acceptance criteria (e.g., accuracy, precision limits) or the detailed reported performance values for these criteria are not provided in the given text.

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

This information is not provided in the document. The text mentions "clinical testing" but does not specify the sample size, country of origin, or if the data was retrospective or prospective.

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

This information is not provided. The device measures exhaled nitric oxide (eNO) as a marker of inflammation in asthma. Ground truth in this context would likely refer to a reference method for eNO measurement or clinical diagnosis of asthma/inflammation. The number and qualifications of experts for establishing such ground truth are not mentioned.

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

This information is 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:

This device is not an AI-assisted diagnostic imaging tool that would typically involve human readers interpreting images. It is a system for quantitatively measuring exhaled nitric oxide. Therefore, an MRMC comparative effectiveness study in the context of human readers improving with AI assistance is not applicable and not mentioned.

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

The Apieron INSIGHT™ eNO System is described as a "Breath Nitric Oxide Test System" that measures eNO. This implies a "standalone" performance in terms of the device's ability to accurately quantify eNO from a breath sample. However, specific standalone performance metrics (e.g., accuracy against a reference standard) and the study details for this are not provided. The text states it "quantitatively measure exhaled nitric oxide (eNO)," which implies a standalone function.

7. The type of ground truth used:

The ground truth for a device measuring eNO would typically be a reference method for nitric oxide measurement. While the text refers to the device measuring a "decrease in eNO...as an indication of the therapeutic effects," the specific ground truth used for validating the device's measurement accuracy is not explicitly stated. It can be inferred that the device's measurements would be compared against a recognized standard for eNO measurement.

8. The sample size for the training set:

As this is a 510(k) for a medical device that quantifies a biomarker, it is unlikely to involve a "training set" in the machine learning sense. The device has a "Biosensor that changes its optical transmission properties when it reacts with the nitric oxide." The performance evaluation would likely focus on the accuracy and precision of this sensor and the overall system. Therefore, a "training set" as commonly understood in AI/ML is not applicable and not mentioned.

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

Given that there is no mention of a training set in the AI/ML context, this question is not applicable.

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