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The eMurmur ID software system is a decision support device for the healthcare provider (the user) in the evaluation of patient heart sounds. eMurmur ID is used to record, display, analyze, and store the acoustic signal of the heart, recorded by means of an electronic stethoscope. The automated analysis will identify specific heart sounds that may be present, including S1, S2, physiological heart murmurs, pathological heart murmurs and absence of a heart murmur.

eMurmur ID is indicated for use in a setting where auscultation would typically be performed by a healthcare provider. It is not intended as a sole means of diagnosis. The heart sound interpretations offered by eMurmur ID are only significant when considered in conjunction with healthcare provider over-read and including all other relevant patient data.

eMurmur ID is a software system comprised of the following components:

1. The eMurmur ID Backend, running on a server environment, hosts the eMurmur ID Heart Sound Analysis Algorithm, an encrypted database for archiving patient and user information, and an application programming interface (API) for communication with the web portal and mobile application.
2. The eMurmur ID Mobile App, which runs on a mobile device. The app permits the following activities:
   a. Electronic recording of heart sound signals via a compatible electronic stethoscope, the Littmann 3200
   b. Visual and acoustic playback of heart and lung sounds
   c. Capturing patient information
   d. Transferring data to and from the eMurmur ID backend through a secure connection
   e. Displaying heart sound analysis results
3. The eMurmur ID Web Portal, which provides the following functionalities:
   a. Capturing and editing patient information
   b. Displaying and editing patient encounters including heart sound analysis results
   c. Visual and acoustic playback of heart and lung sounds
   d. Downloading reports (PDF) and heart and lung sound recordings
   e. Transferring data to and from the eMurmur ID backend through a secure connection

The acquisition of the acoustic data is carried out by the FDA-cleared off-the-shelf electronic stethoscope Littmann 3200 by 3M (MN, USA) (K083903).

For heart sounds to be analyzed by the heart sound analysis algorithm, a 20 second digital recording of the patient's heart sounds and the patient's date of birth are required. Heart sounds are recorded using the compatible, FDA-cleared, off-the-shelf electronic stethoscope Littmann 3200. The heart sounds are transmitted via Bluetooth to a mobile device running the eMurmur ID mobile app. The app then stores and sends the recorded data to the eMurmur ID backend for analysis. The results of the heart sound analysis are returned to the app within a few seconds, where they are displayed to the user together with the heart sound recording. The user can utilize the heart sound analysis results and the acoustic and visual representation of the heart sound recordings as decision support data in their decision-making process regarding the presence and type of a heart murmur.

Here's a detailed breakdown of the acceptance criteria and study information for the eMurmur ID device, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria for eMurmur ID were defined relative to a predicate device (SensiCardiac, the predecessor to SensiCardiac Mobi). The primary hypothesis was that eMurmur ID would perform "not worse than" the predicate device in distinguishing between AHA Class I (pathologic murmurs) and AHA Class III heart sounds (innocent murmurs and/or no murmurs) with respect to sensitivity and specificity.

*Note: The "not worse than" criteria are inferred from the predicate's performance in the same study, as the text states the hypothesis was "not worse than that of the predicate device." The study explicitly showed eMurmur ID was significantly better than the predicate.

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

• Sample Size: 120 subjects.
  • 50% (60 subjects) had a confirmed pathological murmur (AHA Class I).
  • 50% (60 subjects) had a confirmed innocent or no murmur (AHA Class III).
• Data Provenance: The study was a prospective clinical investigation. The country of origin of the data is not explicitly stated, but the sponsor company is CSD Labs GmbH in Graz, Austria, which might suggest a European origin for the clinical study, though this is not confirmed.

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

• The ground truth was established by an expert physician's auscultation-based diagnosis.
• This diagnosis was independently verified by cardiac echocardiography.
• The number of expert physicians is not specified (e.g., whether it was one physician or multiple in consensus for the initial diagnosis). The qualification is generally described as an "expert physician."

4. Adjudication Method for the Test Set

The provided text describes the ground truth as the "expert physician's auscultation-based diagnosis, independently verified by cardiac echocardiography." This suggests a two-step process where the physician's assessment is cross-referenced with objective imaging data. It doesn't explicitly mention a consensus or multi-reader adjudication process for the physician's diagnosis itself beyond the single "expert physician" mentioned.

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

• No, an MRMC comparative effectiveness study involving human readers with vs. without AI assistance was not explicitly described in this context.
• The study described was a standalone performance comparison between the eMurmur ID algorithm and the predicate device's algorithm, both compared against a clinical gold standard. The device is a "decision support device for the user," but the study evaluated the algorithm's performance, not human-in-the-loop improvement.

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

• Yes, a standalone performance study was done. The study's results (sensitivity, specificity, accuracy for eMurmur ID vs. SensiCardiac) directly reflect the performance of the algorithms in distinguishing heart murmurs against a clinical gold standard. The output of eMurmur ID's algorithm was directly compared to the predicate's algorithm output.

7. The Type of Ground Truth Used

• The ground truth used was a combination of expert clinical assessment and objective imaging data: "expert physician's auscultation-based diagnosis, independently verified by cardiac echocardiography."

8. The Sample Size for the Training Set

• The sample size for the training set is not provided in the document. The text focuses solely on the pivotal clinical study used for validation.

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

• The method for establishing the ground truth for the training set is not provided in the document.

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