TY - JOUR
T1 - In-Hospital Prognostic Value of Electrocardiographic Parameters Other Than ST-Segment Changes in Acute Myocardial Infarction
T2 - Literature Review and Future Perspectives
AU - Hayıroğlu, Mert İlker
AU - Lakhani, Ishan
AU - Tse, Gary
AU - Çınar, Tufan
AU - Çinier, Göksel
AU - Tekkeşin, Ahmet İlker
N1 - Publisher Copyright:
© 2020 Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) and the Cardiac Society of Australia and New Zealand (CSANZ)
PY - 2020/11
Y1 - 2020/11
N2 - Electrocardiography (ECG) remains an irreplaceable tool in the management of the patients with myocardial infarction, with evaluation of the QRS and ST segment being the present major focus. Several ECG parameters have already been proposed to have prognostic value with regard to both in-hospital and long-term follow-up of patients. In this review, we discuss various ECG parameters other than ST segment changes, particularly with regard to their in-hospital prognostic importance. Our review not only evaluates the prognostic segments and parts of ECG, but also highlights the need for an integrative approach in big data to re-assess the parameters reported to predict in-hospital prognosis. The evolving importance of artificial intelligence in evaluation of ECG, particularly with regard to predicting prognosis, and the potential integration with other patient characteristics to predict prognosis, are discussed.
AB - Electrocardiography (ECG) remains an irreplaceable tool in the management of the patients with myocardial infarction, with evaluation of the QRS and ST segment being the present major focus. Several ECG parameters have already been proposed to have prognostic value with regard to both in-hospital and long-term follow-up of patients. In this review, we discuss various ECG parameters other than ST segment changes, particularly with regard to their in-hospital prognostic importance. Our review not only evaluates the prognostic segments and parts of ECG, but also highlights the need for an integrative approach in big data to re-assess the parameters reported to predict in-hospital prognosis. The evolving importance of artificial intelligence in evaluation of ECG, particularly with regard to predicting prognosis, and the potential integration with other patient characteristics to predict prognosis, are discussed.
KW - Electrocardiography
KW - In-hospital mortality
KW - P wave
KW - QRS morphology
KW - QT interval
KW - T wave
UR - http://www.scopus.com/inward/record.url?scp=85087292499&partnerID=8YFLogxK
U2 - 10.1016/j.hlc.2020.04.011
DO - 10.1016/j.hlc.2020.04.011
M3 - Review article
C2 - 32624331
AN - SCOPUS:85087292499
SN - 1443-9506
VL - 29
SP - 1603
EP - 1612
JO - Heart Lung and Circulation
JF - Heart Lung and Circulation
IS - 11
ER -