Interpretable Fuzzy Rule-Based System for Fatal Ventricular Arrhythmia Risk Level Estimation due to QT-Prolonging Treatments

This COVID-19 pandemic is impacting the world in health and economic terms since 2020 with more than 200 million confirmed infected people and more than 4 million deaths across 190 countries. Treatment used against COVID-19 disease has initially been based on the combination of several medicaments, such as hydroxychloroquine/chloroquine, azithromycin and kaletra, each of which can individually delay the ventricular depolarization and repolarization processes through morphological changes in the patient’s electrocardiogram. These changes can produce serious arrhythmias that lead to the sudden death of the patient.This paper presents an interpretable fuzzy rule-based system for fatal ventricular arrhythmia risk level estimation due to COVID-19 treatment, whose decisions are made on the basis of the evolution of electrocardiogram morphology and certain patient’s clinical information. For the risk level estimation, the proposed fuzzy rule-based system considers three different risk levels (High, Moderate and Low) which are indicated by means of three different colors (Red, Orange and Green). Decisions made by the fuzzy rule-based system present a reliable behavior in comparison with cardiologist’s decision. To be precise, the obtained accuracy, when comparing both decisions, reaches the 96.43%, which, joint to the high measured interpretability of the decision making system, result in a powerful tool in order to avoid death in patients, even in health centers without specialized clinical staff, and to reduce the stress in medical centers by reducing reaction times in critical patient situations.