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Ascent Cardiorespiratory Diagnostic Software is intended to be used for measurements, data collection and analysis of lung function (PFT) parameters, and cardiopulmonary testing (CPET) parameters, aiding in the diagnosis of related conditions.

All the measurements are performed via a mouthpiece or a mask.

The results of the test can be viewed on-line with the help of a computer screen and can be printed after the test. The test results can be saved for further referral or report generation purposes.

For use of the Bronchial Challenge option, the medical director of the laboratory, physician, or person appropriately trained to treat acute bronchoconstriction, including appropriate use of resuscitation equipment, must be close enough to respond quickly to an emergency.

The product can be utilized for patients from 4 years old and older as long as they can cooperate in the performance -- no special limit to patient's sex or height.

Measurements will be performed under the direction of a physician in a hospital environment, physician's office or similar settings.

Ascent™ Cardiorespiratory Diagnostic Software ("Ascent") is a stand-alone software application which can be used with several hardware devices in the Medical Graphics Corporation product line.

The core purpose of the software for measurement, data collection and analysis of testing in patients who may be suffering from pulmonary illnesses like chronic obstructive pulmonary disease (COPD), asthma, exercise intolerance, heart failure and/or cardiorespiratory concerns where diagnosis and prognosis needs to be determined.

In conjunction with diagnostic hardware, Ascent is used to collect data pertaining to the patient's degree of obstruction, lung volumes, and diffusing capacity. It is also used to present the collected lung diagnostic information so that it can be checked for quality and interpreted by a qualified physician, often a pulmonologist or cardiologist.

All the measurements are performed via a mouthpiece or a face mask.

The provided text is a 510(k) summary from the FDA, which outlines the substantial equivalence determination for a medical device. This type of document focuses on comparing a new device to existing legally marketed predicate devices rather than providing detailed acceptance criteria and the results of a specific clinical study with granular performance metrics. As such, the document does not contain the specific information needed to fulfill all aspects of your request, particularly regarding detailed performance metrics, sample sizes for test sets (beyond general validation statements), expert qualifications, ground truth establishment methods for test sets, MRMC studies, or training set details.

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

Missing Information:

• Detailed Acceptance Criteria Table with Specific Performance Metrics: The document states that the software was "extensively validated per medical device software standards and guidance" and that "Testing results support that Ascent fulfills its intended use/indications for use." It also mentions "Performance tests included FEV1, MVV, FRC, SVC, DLCO, VA, TGV, VO2, VCO2, and VE." However, it does not provide specific quantitative acceptance criteria (e.g., "FEV1 must be within X% of ground truth") or the reported performance for these metrics.
• Sample Size for Test Set and Data Provenance: The document does not specify the sample size for the test data used for performance validation, nor does it detail the provenance (country, retrospective/prospective) of this data.
• Number of Experts and Qualifications for Ground Truth: The document does not describe how ground truth for the test set was established, including the number or specific qualifications of experts involved.
• Adjudication Method for Test Set: No information is provided regarding adjudication methods (e.g., 2+1, 3+1).
• Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study: The document does not indicate that an MRMC study was performed or provide any effect size for human reader improvement with AI assistance.
• Standalone Performance (Algorithm Only): While the document states "Ascent Cardiorespiratory Diagnostic Software is a stand-alone software application," it describes validation as "Performance validation testing was done with the subject software device and recommended hardware devices working together." It does not provide specific performance metrics for the algorithm only without human interaction in a diagnostic capacity beyond its intended function of measuring, collecting, and analyzing parameters. The software aids diagnosis, implying human interpretation.
• Type of Ground Truth Used (for Test Set): The document implicitly refers to "performance tests" for various physiological parameters (FEV1, DLCO, etc.), suggesting comparison to a reference standard for these measurements. However, it does not explicitly state the nature of this "ground truth" (e.g., expert consensus, pathology, outcome data) beyond reference to ATS/ERS guidelines for standardization.
• Sample Size for Training Set: No information on training data or its size is provided. This is typical for a 510(k) for software that calculates and analyzes data from hardware, rather than an AI/ML model that learns from large datasets.
• How Ground Truth for Training Set was Established: Not applicable as training data details are not provided.

Information that can be extracted from the document:

The provided document is a 510(k) summary for the "Ascent Cardiorespiratory Diagnostic Software" (K242809). It details the device's substantial equivalence to predicate devices, focusing on its intended use, technological characteristics, and conformity to relevant standards and guidelines.

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

As noted above, specific quantitative acceptance criteria and reported performance metrics are NOT provided in this document. The document generally states that "Ascent Cardiorespiratory Diagnostic Software was extensively validated per medical device software standards and guidance. Testing results support that Ascent fulfills its intended use/indications for use..."

It mentions that "Performance tests included FEV1, MVV, FRC, SVC, DLCO, VA, TGV, VO2, VCO2, and VE." However, no numerical results or thresholds are given. The validation was done referencing the following guidelines/standards for "acceptability and repeatability":

• ATS/ ERS Standardisation of Spirometry (2019)
• ERS/ ATS Standardisation of the Measurements of Lung Volumes (2023)
• 2017 ERS/ ATS Standards for Single-Breath Carbon Monoxide Uptake in the Lung
• ERS Technical Standard on Bronchial Challenge Testing (2017)
• 2017 ATS Guidelines for a Standardized PF Report
• ATS/ ACCP Statement on Cardiopulmonary Exercise Testing (2003)

Summary of available information for a table format (conceptual, as specific numerical data is missing):

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

• Sample Size: Not specified. The document only states "Software validation testing involved system level tests, performance tests and safety testing based on hazard analysis. Performance validation testing was done with the subject software device and recommended hardware devices working together."
• Data Provenance: Not specified (e.g., country of origin, 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 in the document.

4. Adjudication method (e.g. 2+1, 3+1, none) 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, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

• No MRMC study is mentioned or implied. The software is described as
  "aiding in the diagnosis of related conditions" and presenting "diagnostic information so that it can be checked for quality and interpreted by a qualified physician." This device is a "Predictive Pulmonary-Function Value Calculator" and performs measurements and analysis, but it is not described as an AI system assisting human readers in image interpretation or diagnosis in a comparative effectiveness study context.

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

• The device is indeed described as a "stand-alone software application." However, the performance validation was done "with the subject software device and recommended hardware devices working together." Its output (measurements and analysis) is intended to be "displayed to the user" and "interpreted by a qualified physician."
• The document does not provide performance metrics for the algorithm only in a way that suggests a diagnostic output without human interpretation or hardware interaction. It's a software that processes data from hardware to provide measurements and analysis, not, for example, a diagnostic image analysis AI.

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

• The document implies that the ground truth for the performance tests (FEV1, DLCO, etc.) would be established by the standardized measurement techniques defined by governing bodies like ATS/ERS/ACCP. These typically involve comparing the device's calculated values against accepted reference methods for deriving those physiological parameters, often involving highly calibrated equipment and expert technicians following strict protocols. However, the exact nature of this "ground truth" (e.g., what gold standard was used for comparison) is not explicitly detailed beyond referencing the standards themselves.

8. The sample size for the training set:

• This information is not provided in the document. This type of device (a calculator/analyzer) is typically engineered based on established physiological formulas and algorithms, rather than being "trained" on large datasets in the way a deep learning AI model would be.

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

• Not applicable, as training set details are not provided and the device functions as a calculator based on established science, not a machine learning model that learns from a labeled training set.

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Ascent Cardiorespiratory Diagnostic Software is intended to be used for measurements, data collection and analysis of lung function (PFT) parameters, aiding in the diagnosis of related conditions. All the measurements are performed via a mouthpiece or a mask. The test can be viewed on-line with the help of a computer screen and can be printed after the test results can be saved for further referral or report generation purposes.

For use of the Bronchial Challenge option, the medical director of the laboratory, physician, or person appropriately trained to treat acute bronchoconstriction, including appropriate use of resuscitation equipment, must be close enough to respond quickly to an emergency.

The product can be utilized for patients from 4 years old and older as long as they can cooperate in the performance -- no special limit to patient's sex or height.

Measurements will be performed under the direction of a physician in a hospital environment, physician's office or similar settings.

In conjunction with pulmonary diagnostic hardware, Ascent software, a Windows desktop application developed using Microsoft's NET Framework, is used to collect data pertaining to the patient's degree of obstruction, lung volumes, and diffusing capacity. It is also used to present the collected lung diagnostic information so that it can be checked for quality and interpreted by a qualified physician, usually a pulmonologist.

The core purpose of the software is to facilitate pulmonary function testing in patients who may be suffering from pulmonary illnesses like Chronic Obstructive Pulmonary Disease and asthma. The software will interact with connected Medical Graphics Corporation diagnostic devices to perform the desired pulmonary function tests on the patient by a professional pulmonary function technologist. The application will display both actual and derived test variables to the user after a test is performed for purposes of data review.

Here's a breakdown of the acceptance criteria and study information for the Ascent Cardiorespiratory Diagnostic Software, based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't explicitly list "acceptance criteria" in a typical quantitative pass/fail format within a table. Instead, it describes general validation and performance testing. However, we can infer the performance objectives and how they were met.

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

• Sample Size for Test Set: 38 test sessions.
• Data Provenance: The subjects for these test sessions were "from seven to sixty-three years old." The document does not specify the country of origin of the data or whether it was retrospective or prospective.

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

The document does not specify the number of experts or their qualifications used to establish ground truth for the test set. It mentions that the software presents data to a "qualified physician, usually a pulmonologist, for diagnostic interpretation," but this refers to the intended use, not the ground truth establishment for the validation study itself.

4. Adjudication Method for the Test Set:

The document does not describe any specific adjudication method (e.g., 2+1, 3+1). The "physiologic performance validation testing" implies direct measurement comparison rather than expert consensus on interpretive tasks.

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

No, an MRMC comparative effectiveness study was not explicitly mentioned or described as being performed. The study focused on the performance of the software and integrated hardware, not on the impact of the software on human reader performance.

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

Yes, the "physiologic performance validation testing" and "software validation testing" described seem to represent a standalone assessment of the device's ability to measure and process pulmonary function parameters. The device's core function is data collection and analysis, which occurs without direct human interpretation assistance during the measurement phase. The overall intention is for a "qualified physician" to interpret the results generated by the algorithm.

7. The Type of Ground Truth Used:

The document doesn't explicitly state "ground truth" in the context of reference standards. However, the nature of the device (pulmonary function software) implies that the ground truth for "physiologic performance validation testing" would be the physical measurements obtained from the connected hardware devices for various pulmonary function parameters (e.g., airflow, volume, gas concentrations). The accuracy of these measurements would be compared against expected values or highly accurate reference standards, though these specific reference standards are not detailed in the provided text.

8. The Sample Size for the Training Set:

The document does not mention any training set sample size or details about a training set. This is likely because the device, as described, is not an AI/machine learning model that typically requires a discrete training phase with labeled data. It appears to be a software system for data acquisition, processing, and display based on established physiological algorithms and hardware interaction.

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

As no training set is discussed, there is no information on how its ground truth might have been established.

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The Resmon PRO FULL is intended to measure respiratory system impedance using the Forced Oscillation Technique (FOT). Resmon PRO FULL is intended for use with pediatric and adult patients 4 years of age or older. The device is designed to be used by pulmonologists, general practitioners, nurses, respiratory therapists, laboratory technologists, medical researchers and similarly trained personnel in hospitals, clinics. and private physician offices.

Resmon PRO FULL is a device for the assessment of the mechanical impedance based on the Forced Oscillation Technique (FOT).

FOT is a non-invasive lung function test for measuring the mechanical properties of the respiratory system. It consists in applying very small pressure oscillations (1-3 cmH2O peak-to-peak) of a given frequency/frequencies (usually below 40Hz) at the patient's mouth while she/he is breathing normally. During the test, the device measures pressure at the mouth and airflow to calculate respiratory impedance in real-time. Impedance is the complex ratio between pressure and airflow estimated at the frequency of the stimulating waveform. Common stimulating waveforms range from a simple sinusoid wave to a composite of different frequencies or impulses. The first approach is utilized for tracking swift changes in respiratory impedance. Examples of this include breath changes in lung mechanics or outcome measurements of specific interventions. The latter is used to assess the frequency dependency of impedance (related to the degree of lung heterogeneity) and identify the parameters of mathematical models of the respiratory system.

FOT allows for measurement during a patient's normal breathing pattern, with no forced effort required, making it suitable for monitoring non-cooperative patients, such as elderly patients, children or very severely ill patients with limited forced capacity. The test is usually performed with the subject seated, wearing a nose-clip (to prevent airflow leaks from the nose during normal breathing) and with hands on cheeks (to prevent the shunt of the pressure stimulus in the upper airways). The device is not intended to be used as a stand-alone diagnostic device.

Resmon PRO FULL consists of a main unit which has been designed to be used stand-alone, without the need of any personal computer, and an adjustable holder with a clamp to fix such unit to a table/desk and to regulate its height and orientation to the patient during an FOT test.

The provided text describes the regulatory clearance of the Resmon PRO FULL device. However, it does not include detailed information regarding specific acceptance criteria for performance metrics (such as sensitivity, specificity, or accuracy) or a study that rigorously proves the device meets these criteria in the typical sense of a clinical performance study for an AI/ML powered device.

Instead, the document focuses on demonstrating substantial equivalence to a predicate device (Carefusion MasterScreen IOS K101873) through technological comparison and non-clinical performance testing. The "performance testing" described is primarily about reproducibility, repeatability, and a comparative analysis of measured parameters against the predicate, rather than a clinical effectiveness study.

Based on the provided text, here's what can be extracted and what is missing:

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

The document does not state explicit acceptance criteria in the form of thresholds for performance metrics like sensitivity or specificity. Instead, the acceptance is based on demonstrating "substantial equivalence" to a predicate device. The performance is assessed through reproducibility, repeatability, and comparison of measured parameters.

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

The document mentions "Comparative testing was done with the subject device and the predicate across the range of parameters and performance specifications."

• Sample Size: Not specified. It only mentions "Multiple units were tested" for reproducibility/repeatability. There is no information on the number of subjects or types of data used for the comparative testing with the predicate.
• Data Provenance: Not specified (country of origin, retrospective/prospective).

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. This device is a measurement device for physiological parameters (respiratory impedance). Its performance is evaluated against physical standards and comparison with another device, not against expert-labeled ground truth for diagnosis/interpretation.

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

Not applicable, as there is no expert adjudication mentioned or required for this type of device evaluation.

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

No. This device is a diagnostic spirometer using the Forced Oscillation Technique (FOT) to measure respiratory impedance. It is not an AI-assisted diagnostic imaging device or an AI application with a "human-in-the-loop" for interpretation that would typically undergo an MRMC study. It is stated that "The device is not intended to be used as a stand-alone diagnostic device."

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

Yes, in a sense. The performance tests ("Hardware Verification," "Software and System Verification and Validation," "Reproducibility and Repeatability," "Comparative testing") evaluate the device's ability to accurately measure and report physiological parameters according to its specifications and in comparison to a predicate device. This is the "standalone" performance of the measurement system itself. There are no algorithms described beyond the calculation of respiratory impedance from pressure and airflow.

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

The "ground truth" for this device's performance evaluation would be:

• Physical calibration standards/simulators: Used to verify accuracy, resolution, and range of flow, pressure, and volume measurements.
• Predicate device measurements: For comparative testing, the predicate's measurements serve as a reference point for demonstrating statistical equivalence in measured parameters.
• Established scientific principles: The device's operation based on the Forced Oscillation Technique (FOT) adheres to these principles.

8. The sample size for the training set

Not applicable. This document does not describe the development of an AI/ML algorithm that requires a training set. The device appears to be a hardware-based measurement system with embedded software for calculations, not a learnable model.

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

Not applicable (as above).

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The Express Series uses the direct measurement of oxygen uptake to objectively and noninvasively assess cardiac and pulmonary function during exercise. The system can be used to screen for early signs of cardiac and pulmonary dysfunction; differentiate heart and lung disease; assess dyspnea complaints; classify patients according to severity of disease as a guide for patient management; establish an optimal exercise prescription and training program; evaluate the efficiency of prescribed therapy.

The Express Series uses the direct measurement of oxygen uptake and carbon dioxide production to provide nutritional assessment, to optimize nutritional supplements and quantify substrate utilization.

The Express Series can also provide direct Fick determination of cardiac output using real time oxygen uptake measurements.

The Express Series is a cardiopulmonary exercise or resting metabolic measurement system with an integrated touch screen computer that provides breath by breath measurements of flow, oxygen uptake and carbon dioxide production.

The provided text is a 510(k) Special Summary for the Medgraphics Express Series, an Oxygen Uptake Computer. This type of regulatory submission typically focuses on demonstrating substantial equivalence to a predicate device rather than presenting detailed clinical study results with specific acceptance criteria and performance metrics in the way a novel AI device might.

Based on the provided text, here's an analysis of the information requested. Many fields will be marked "Not Applicable" or "Not Provided" because the document is a summary for a traditional medical device (an oxygen uptake computer) and not an AI/ML device, and thus doesn't include the type of detailed study information typically found in submissions for AI products.

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size for Test Set: 10 systems (for laboratory and clinical testing).
• Data Provenance: Not specified (e.g., country of origin, retrospective/prospective). The testing appears to be internal "Laboratory and clinical testing."

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

• Number of Experts: Not applicable/Not provided. The ground truth appears to be established by comparison to the predicate device's output, not by expert interpretation.
• Qualifications of Experts: Not applicable/Not provided.

4. Adjudication method for the test set

• Adjudication Method: Not applicable/Not provided. The study compares a new device's measurements to a predicate device's measurements, not human interpretations 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

• MRMC Study: No. This is not an AI device, and the study design is not an MRMC study.

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

• Standalone Performance: Yes, in the sense that the device itself (the Express Series) was tested against the predicate device (Ultima System) in a "tandem gas exchange system validator studies." This evaluates the device's measurement capabilities directly.

7. The type of ground truth used

• Type of Ground Truth: The "ground truth" for this substantial equivalence study is the performance and data output of the predicate device, the Medgraphics Ultima System (K061731). The study aimed to show that the new device's measurements (VO2, VCO2, tidal volume) had less than 5% variability when compared to the predicate device.

8. The sample size for the training set

• Sample Size for Training Set: Not applicable/Not provided. This is not an AI/ML device, so there isn't a "training set" in that sense. The device is a measurement system.

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

• Ground Truth for Training Set Establishment: Not applicable/Not provided.

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The Ultima system uses the direct measurement of oxygen uptake to objectively and noninvasively assess cardiac and pulmonary function during exercise. The system can be used to screen for early signs of cardiac and pulmonary dysfunction; differentiate heart and lung disease; assess dyspnea complaints; classify patients according to severity of disease as a guide for patient management; establish an optimal exercise prescription and training program; evaluate the efficiency of prescribed therapy.

The Ultima system uses the direct measurement of oxygen uptake and carbon dioxide production to provide nutritional assessment, to optimize nutritional supplements and quantify substrate utilization.

The Ultima system can also provide direct Fick determination of cardiac output using real time oxygen uptake measurements.

The Ultima system is a cardiopulmonary exercise system that provides breath by breath measurements of flow, oxygen uptake and carbon dioxide production.

The Medgraphics Ultima System, categorized as an Oxygen Uptake Computer, has been found substantially equivalent to its predicate device, the Medgraphics Desktop Diagnostic System with 15% CO2 Analyzer (K955432).

Here's an analysis of the acceptance criteria and the study that supports the device's performance:

1. Table of Acceptance Criteria and Reported Device Performance:

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

• Sample Size for Test Set: 11 Ultima systems were used for laboratory testing.
• Data Provenance: The document does not explicitly state the country of origin. It is implied to be internal laboratory testing conducted by Medical Graphics Corporation. The study is retrospective, as it compares the new Ultima system to a previously marketed predicate device.

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

• The document does not specify the number of experts or their qualifications used to establish ground truth for the test set. The study relies on direct comparison to the predicate device's output and internal laboratory testing.

4. Adjudication Method for the Test Set:

• The document does not describe an adjudication method for the test set. The evaluation focuses on the direct comparison of performance metrics (VO2, VCO2, tidal volume) between the Ultima system and the predicate device.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, and the effect size of how much human readers improve with AI vs without AI assistance:

• A Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not conducted as this is a device for physiological measurement (Oxygen Uptake Computer), not an imaging or diagnostic AI system requiring human interpretation comparison. This device provides quantitative data, not interpretations that would be compared to human readers.

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

• Yes, the study primarily represents standalone algorithm/device performance. The laboratory testing assessed the device's output and precision independently, comparing it to a predicate device. While a human operates the device, the performance evaluation itself is based on the device's measured outputs compared to established benchmarks or the predicate.

7. The Type of Ground Truth Used:

• The ground truth in this study is based on the performance and output of the legally marketed predicate device (Medgraphics Desktop Diagnostic System with 15% CO2 Analyzer, K955432), as well as the inherent physiological measurements (VO2, VCO2, tidal volume) for which the device is designed to accurately measure. The "less than 3% variability" indicates an acceptable deviation from the predicate's established measurements.

8. The Sample Size for the Training Set:

• The document does not mention a separate "training set" in the context of machine learning or AI development. For a physiological measurement device like this, the "training" would typically refer to the calibration, design, and internal validation processes during its development, which are not detailed as a distinct "training set" here.

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

• As a "training set" is not explicitly mentioned, the method for establishing its ground truth is not provided. For a device of this nature, the "ground truth" during development and calibration would likely rely on established physiological models, controlled gas mixtures, and comparison to highly accurate reference instruments.

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