Background: As only a small proportion of patients with chest pain suffers from myocardial infarction (MI), safe rule-out of MI is of immense importance. Recently an ultrasensitive microphone performing diastolic heart sound analysis (CADScorSystem) for rule-out of coronary artery disease (CAD) has emerged. In this explorational study, we aimed to evaluate the feasibility of the CADScorSystem for diagnosis of MI in the setting of a large emergency department.
Methods: Patients presenting to the emergency department with suspected MI were included. Acoustic heart sound analysis was performed in all patients and automated CAD-score values were calculated via a device-embedded algorithm, which also requires inclusion of three clinical variables: age, sex and presence of hypertension. Patients additionally received serial high-sensitive troponin T measurement measurements to assess the final diagnosis according to third Universal Definition of Myocardial Infarction applying the European Society of Cardiology 0 hour/3 hours algorithm. Diagnostic parameters for MI, considering different CAD-score cut-offs, were computed.
Results: Of 167 patients, CAD-scores were available in 61.1%. A total of eight patients were diagnosed with MI. At a cut-off value of <20, CAD-score had a negative predictive value (NPV) of 90.7 (78.4-96.3). The corresponding positive predictive value (PPV) was 6.8 (2.7-16.2). For the adjusted CAD-score (age, sex, hypertension), at a cut-off value of <20, NPV was 90.0 (59.6-99.5) with a PPV of 10.8 (5.3-20.6).
Conclusion: In this explorative analysis, a transcutaneous ultrasensitive microphone for heart sound analysis resulted in a high NPV analogous to the findings in rule-out of stable CAD in elective patients yet inferior to serial high-sensitivity cardiac troponin measurements and does not seem feasible for application in an emergency setting for rule-out of MI.
Trial Registration Number: NCT02355457.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9980326 | PMC |
http://dx.doi.org/10.1136/openhrt-2022-002090 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!