Mirtajaddini Marzieh
Cardiovascular Research Center, Kerman University of Medical Sciences, Kerman, Iran.
J Electrocardiol. 2017 Sep-Oct;50(5):634-639. doi: 10.1016/j.jelectrocard.2017.05.007. Epub 2017 May 18.
Electrocardiogram (ECG) is an essential tool used to diagnose serious heart disease but its interpretation is challenging for undergraduate students and junior practitioners despite numerous methods that have been suggested to aid ECG interpretation. This paper aims to present a new algorithm for arrhythmia interpretation that is superior to current methods to be used as a supplement to lecture materials for medical students.
A new systematic algorithm is introduced in this paper. To evaluate the effectiveness of the proposed algorithm, a study was carried out in a medical university. Two groups of medical interns were educated via lecture and teaching rounds, either using the proposed algorithm or without using the algorithm. At the end of 1 month training, students of both groups were blindly evaluated.
The group trained using the algorithm scored an average of 93% on the evaluation, while the group trained without it averaged 62%. This was found to be a statistically significant difference (p<0.01).
The proposed method for education of arrhythmia interpretation can improve physicians' competency in ECG interpretation.
心电图(ECG)是诊断严重心脏病的重要工具,但尽管已有多种辅助心电图解读的方法,但对本科生和初级从业者来说,其解读仍具有挑战性。本文旨在提出一种心律失常解读的新算法,该算法优于现有方法,可作为医学生教材的补充。
本文引入了一种新的系统算法。为评估该算法的有效性,在一所医科大学开展了一项研究。两组医学实习生分别通过讲座和教学查房接受培训,一组使用该算法,另一组不使用。在1个月的培训结束时,对两组学生进行盲评。
使用该算法培训的组在评估中平均得分93%,而未使用该算法培训的组平均得分62%。发现这具有统计学显著差异(p<0.01)。
所提出的心律失常解读教学方法可提高医生解读心电图的能力。