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Epiphany Cardio Server Mobile is a software application used for accessing and displaying ECG data and related patient information previously stored, analyzed or received by the Cardio Server ECG Management System. The Epiphany Cardio Server Mobile software application is intended to be used from a mobile device to perform the following:

· View ECG test results, such as waveforms, measurements and diagnosis statements as well as other relevant current or historical patient information originally stored, analyzed or received by the Cardio Server ECG Management System.

· View the ECG lead traces using different display settings.

· Compare the results of current ECG tests with the patient's previous ECG test results stored on the Cardio Server ECG Management System.

· Perform manual ECG-related measurements using the electronic caliper tool.

· Communicate information with the Cardio Server ECG Management System such as login credentials and user settings.

Epiphany Cardio Server Mobile application is intended to be used under the direct supervision of a licensed healthcare practitioner and by trained operators. Epiphany Cardio Server Mobile is not intended for real time monitoring.

The Epiphany Cardio Server Mobile provides secure access to ECG records and related information contained on the Cardio Server ECG Management System. The Epiphany Cardio Server Mobile software functions as an accessory to the Cardio Server ECG Management System, and requires a WIFI or cellular connection to a pre-installed and properly configured Cardio Server ECG Management System. Through providing remote access to the ECG data stored on the Cardio Server ECG Management System, the user is able to review current and previous ECG tests, results, and perform measurements on the ECG waveforms. Cardio Server Mobile does not store ECG or patient related information on the mobile device, does not directly communicate with cardiographs or other waveform acquisition devices, and does not use any automatic electronic data processing and pattern recognition methods to derive measurements (e.g. intervals and amplitudes) or provide diagnostic statements from the ECG data. The device does not allow modification of the original ECG traces (waveforms) stored on the Cardio Server ECG Management System.

The Epiphany Cardio Server Mobile application is not intended to replace the functionalities provided by the Cardio Server ECG Management System desktop client but to extend those to make selected functionalities described above available via mobile devices.

The Epiphany Cardio Server Mobile functions as a non-real time system and is not intended for real time monitoring.

The Epiphany Cardio Server Mobile can be used both inside and outside of medical facilities except in areas where cellular phone or wireless device use is prohibited.

The Epiphany Cardio Server Mobile is intended to operate on Apple iPad and iPhone running iOS mobile operating system from Apple Inc.

The document is a 510(k) Summary for the Epiphany Cardio Server Mobile. It describes the device, its intended use, and a comparison to a predicate device.

However, the provided text does not contain specific acceptance criteria or the details of a study that proves the device meets those criteria in the way a clinical study for an AI/ML algorithm might.

Instead, it focuses on non-clinical performance testing to demonstrate substantial equivalence to a predicate device for a mobile application that displays ECG data and allows for manual measurements, rather than performing automated analysis or diagnosis itself.

Therefore, for aspects like "Number of experts," "Adjudication method," "MRMC study," "Standalone performance," "Effect size," and "Ground truth," the document indicates these types of rigorous clinical validation studies were not performed because the device's function does not involve AI/ML for automated analysis or diagnosis.

Here's a breakdown based on the information provided and what is not present:

1. Table of Acceptance Criteria and Reported Device Performance:

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

• Sample Size: The document mentions "sample cases" for bench testing and "simulated user test environment" but does not provide a specific numerical sample size (e.g., number of ECGs or users) for the test set.
• Data Provenance: Not specified. The data used for testing were likely internal, simulated, or pre-existing "sample cases" rather than a collected clinical dataset. The device receives data from the "Cardio Server ECG Management System" which would hold the actual patient data, but the testing described here is on the display and measurement tools of the mobile app, not the diagnostic content itself.

3. Number of Experts Used to Establish Ground Truth and Qualifications:

• Not applicable in the context of an AI/ML ground truth study. The device's function is to display data and allow manual measurements, not to perform automated analysis or diagnosis that would require expert-established ground truth for algorithm performance. The testing was verification of display capabilities and accuracy against the source system.

4. Adjudication Method for the Test Set:

• Not applicable. As the device does not perform automated analysis requiring diagnostic ground truth, no adjudication method (like 2+1 or 3+1 consensus) was conducted.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, and its effect size:

• No, an MRMC comparative effectiveness study was not done. The device (Epiphany Cardio Server Mobile) is a display and manual measurement tool for existing ECG data, not an AI/ML diagnostic aid. The testing focused on software functionality and display accuracy, not on how human readers' diagnostic accuracy changes with or without this specific mobile application. Therefore, there's no reported effect size regarding human reader improvement with AI assistance.

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

• No, not in the context of an AI/ML algorithm. The device is a "software application" that functions as an accessory to an ECG management system. It "does not use any automatic electronic data processing and pattern recognition methods to derive measurements (e.g. intervals and amplitudes) or provide diagnostic statements from the ECG data." Therefore, there is no "algorithm only" performance to report as it's not an AI/ML diagnostic tool. Its "standalone" performance relates to its ability to display and allow manual measurements accurately, which was verified through "bench testing."

7. The Type of Ground Truth Used:

• Reference data from the Cardio Server ECG Management System. The "ground truth" for display accuracy and manual caliper measurements was the "original data as presented by Cardio Server ECG Management System." For functional aspects, the "design requirements" serve as the standard. This is not a clinical ground truth like pathology or outcomes data, but rather a functional and display accuracy ground truth.

8. The Sample Size for the Training Set:

• Not applicable. This device is not an AI/ML algorithm that undergoes a "training" phase with a dataset. It's a software application designed for data display and manual measurement.

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

• Not applicable. As no AI/ML training set was used, no ground truth needed to be established for such a set.

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The MobileECG System is intended to provide an interpretation of the resting 12 lead ECG in all situations, whether in a hospital or primary care setting. It is capable of diagnosing all commonly recognized ECG abnormalities such as myocardial infarction (MI), including acute MI, ventricular hypertrophy, abnormal ST-T changes and common abnormalities of rhythm.

The MobileECG System is intended for use in adults and children of any age from birth upwards.

The MobileECG System's interpretation software is not intended as sole means of diagnosis and is offered to physicians and clinicians on an advisory basis only in conjunction with the physician's knowledge of ECG.

The MobileECG System is an electrocardiograph consisting of Model 950-12LR HHC module and CardioVu interpretation software.

The Model 950-12LR HHC module is a small, light weight, single battery, wireless module designed to transmit 12Lead electrical heart activity of a patient to a computer. This module will transmit a patient's ECG wirelessly to a laptop, netbook, tablet, or desktop computer containing the CardioVu interpretation software from up to 100 feet away.

Elimination of the cable reduces a source of artifact resulting in high-quality ECG tracings. Wireless dedicated and secure communication links the Model 950-12LR HHC module to CardioVu interpretation software.

The CardioVu software receives, displays, and stores the patients ECG data wirelessly on a laptop, netbook, tablet, or desktop computer in "real time". The software also has the data using ECG algorithms for review by a physician or other qualified medical professional as an advisory basis only in conjunction with the physician's knowledge of ECG. The wireless feature allows the patient not to be tethered to the computer or a bulky box thus reducing motion artifacts caused by movement of the connecting cables and providing comfort to the patient.

The provided 510(k) summary for the Memtec Corporation's MobileECG System (K103427) does not describe an extensive study (clinical or analytical) with specific acceptance criteria and performance metrics for the device's diagnostic capabilities. Instead, it focuses on non-clinical testing for substantial equivalence to predicate devices based on applicable standards.

Therefore, many of the requested details about acceptance criteria, study sizes, expert qualifications, and ground truth establishment cannot be extracted from this document as such a study is not presented.

Here's a breakdown of what can be inferred from the document regarding comparative effectiveness and analytical performance:

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not explicitly state acceptance criteria in terms of diagnostic accuracy (e.g., sensitivity, specificity) for its ECG interpretation software. The assessment is based on demonstrating equivalence to predicate devices through compliance with technical standards.

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

No clinical test set is described. The "non-clinical tests" focused on standards compliance, not diagnostic performance on a patient dataset.

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

Not applicable, as no clinical test set with expert-established ground truth is described. The software's interpretation is "an advisory basis only in conjunction with the physician's knowledge of ECG."

4. Adjudication Method for the Test Set:

Not applicable, as no clinical test set for diagnostic 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:

No MRMC study is mentioned. The device's software is described as providing "interpretation software... on an advisory basis only," suggesting it's an aid, but no study on human performance improvement with this aid is presented.

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

The document states, "The software also has the data using ECG algorithms for review by a physician or other qualified medical professional as an advisory basis only." While algorithms are present, a formal standalone performance study (e.g., sensitivity/specificity of the algorithm alone against a gold standard) is not described or quantified in this 510(k) summary.

7. The Type of Ground Truth Used:

Not applicable, as a study requiring ground truth for diagnostic performance is not described.

8. The Sample Size for the Training Set:

The document does not provide any information about a training set for the ECG interpretation algorithms.

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

Not applicable, as no training set or its ground truth establishment is described.

Summary of what the 510(k) does convey:

The document primarily demonstrates substantial equivalence to predicate devices through non-clinical testing against relevant industry standards (e.g., electrical safety, electromagnetic compatibility, ECG performance requirements like filtering and lead accuracy). It asserts that the device's technical specifications and intended use are similar to those of previously cleared devices, making it equally safe and effective from a manufacturing and functional standpoint, rather than providing a detailed clinical validation of its diagnostic algorithm's accuracy.

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