A viewpoint on evaluating ECG findings to assess heart issues: A clinical nursing review

Abstract

The 12-lead EKG is a useful first-line diagnostic tool for detecting cardiovascular diseases, including arrhythmias, conduction abnormalities, and myocardial ischemia or infarction. This scoping review aims to discuss the ECG perspective for detecting heart problems. This study was conducted by following the narrative review and development framework. The literature search used ScienceDirect, Scopus, ProQuest, ClinicalKey, and SpringerLink data. The keywords used were "criteria" or "guidelines" and "ECG" or "ECG" or "electrocardiography" or "electrocardiogram" and "detection" and "heart problem" or "heart disease" or "heart problem" or "heart problem." The method uses a narrative review through eight articles spanning 2017–2022. The lighting method uses the PICO analysis framework. The results found four components, namely: 1) automatic diagnosis; 2) 3-D ECG with artificial intelligence (AI) classification; 3) use of the LSTM deep-learning model; and 4) leads using Tpeak-End (Tp-e). In patients with heart problems, the initial examination is an EKG. Thus, the ECG, with the addition of the automatic diagnosis feature, EKG-3D, and the use of a 12-lead ECG with a deep-learning LSTM model, also followed by high sensitivity and specificity, can be used as a tool to perform examinations on patients who require serial ECG examinations.

 Keywords: Electrocardiogram; nursing care; nursing review; clinical symptoms; nursing assessment