INTRODUCTION: The electrocardiogram is the most widely used and effective method of detecting possibly fatal heart rhythm disturbances. Acquiring skills in electrocardiographic interpretation not only enriches nurses' cultural and professional backgrounds but is crucial for ensuring quality and time-dependent patient care. The study's main objective is to survey nursing knowledge/skills in interpreting and reading electrocardiographic tracing. MATERIALS AND METHODS: A Cross-Sectional Study was conducted by administering an online survey to a sample of 100 nurses belonging to different operating units and with different degrees of seniority and education. The survey was structured with a first part investigating the socio-demographic characteristics of the sample and a second part consisting of eight questions on various cardiac pathologies. RESULTS: The analysis of the socio-demographic characteristics of the sample of 100 nurses showed that 75% of the sample had a bachelor's degree in nursing. Of these, 49.5% have more than ten years of work experience, and 51% work in a critical care unit. A significant finding is that concerning post-graduate training, only 35% of the participants had attended advanced training courses for reading and analysing electrocardiographic tracing, thus increasing their cultural and professional background. The most significant finding was that only 11% answered all the questions correctly, of whom 9% had attended an advanced electrocardiographic interpretation and analysis training course (Tab1). CONCLUSIONS: This study emphasizes the importance of promoting education and training to integrate methods that can facilitate the reading and analysis of electrocardiographic tracing. With the increasing incidence of cardiovascular disease, good knowledge of malignant cardiac rhythms is essential to provide quality nursing care that can also include early recognition of life-threatening conditions and the implementation of useful manoeuvres to support basic vital functions, so that everyone can be able to quickly identify the main and most frequent arrhythmias so that they can intervene as quickly as possible in this type of time-dependent disease.