RESUMO
During the first few months of the global Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) pandemic, the medical research community had to expeditiously develop, select, and deploy novel diagnostic methods and tools to address the numerous testing challenges presented by the novel virus. Integrating a systematic approach to diagnostic selection with a rapid validation protocol in a clinical setting can shorten the timeline to bring new technologies to practice. In response to the urgent need to provide tools for identifying SARS-CoV-2-positive individuals, we developed a framework for assessing technologies against a set of prioritized performance metrics to guide device selection. We also developed and proposed clinical validation frameworks for the rapid screening of new technologies. The rubric described here represents a versatile approach that can be extended to future technology assessments and can be implemented in preparation for future emerging pathogens.
RESUMO
Repolarization alternans (RA) has been implicated in the pathogenesis of ventricular arrhythmias and sudden cardiac death. We developed a 12-lead, blue-tooth/Smart-Phone (Android) based electrocardiogram (ECG) acquisition and monitoring system (cvrPhone), and an application to estimate RA, in real-time. In in-vivo swine studies (N = 17), 12-lead ECG signals were recorded at baseline and following coronary artery occlusion. RA was estimated using the Fast Fourier Transform (FFT) method using a custom developed algorithm in JAVA. Underlying ischemia was detected using a custom developed ischemic index. RA from each lead showed a significant (p < 0.05) increase within 1 min of occlusion compared to baseline (n = 29). Following myocardial infarction, spontaneous ventricular tachycardia episodes (n = 4) were preceded by significant (p < 0.05) increase of RA prior to the onset of the tachy-arrhythmias. Similarly, the ischemic index exhibited a significant increase following myocardial infarction (p < 0.05) and preceding a tachy-arrhythmic event. In conclusion, RA can be effectively estimated using surface lead electrocardiograms by analyzing beat-to-beat variability in ECG morphology using a smartphone based platform. cvrPhone can be used to detect myocardial ischemia and arrhythmia susceptibility using a user-friendly, clinically acceptable, mobile platform.