AUTHOR=Su Xiao-Feng , Fan Na , Yang Xue-Mei , Song Jun-Mei , Peng Qiong-Hui , Liu Xin 

TITLE=A Novel Electrocardiography Model for the Diagnosis of Acute Pulmonary Embolism

JOURNAL=Frontiers in Cardiovascular Medicine

VOLUME=Volume 9 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/cardiovascular-medicine/articles/10.3389/fcvm.2022.825561

DOI=10.3389/fcvm.2022.825561

ISSN=2297-055X

ABSTRACT=Acute pulmonary embolism (acPE) is a severe disease that is often misdiagnosed as it is difficult to detect quickly and accurately. In the current study, a novel electrocardiogram (ECG) model was used to estimate the probability of acPE rapidly via analysis of ECG characteristics. A total of 327 patients with acPE that were diagnosed in Sichuan Provincial People’s Hospital between 2018 and 2021 were retrospectively studied. A total of 331 patients were randomly selected as the control group and this group included patients hospitalized during the same time period. The control group included patients who presented with characteristic symptoms of acPE, but this diagnosis was ruled out following further diagnostic testing The present study compared the diagnostic value of the ECG model with those of another ECG scoring model (Daniel-ECG-score) and of the most common prediction models (Wells score and Geneva score). The current study established a ECG predictive model using analysis of the ECG abnormalities in patients with acPE. The final ECG model included certain novel ECG signs that had not been incorporated in the patients previous ECG score, and thus when compared to the previous ECG score, exhibited a more favorable area under the receiver operating characteristic curve (AUC) value (0.8741). The model developed in this study was named the SPPH-ECG-model. Furthermore, the current study compared the SPPH-ECG-model with Daniel-ECG-score, Wells score and Geneva score, and the SPPH-ECG-model was demonstrated to exhibit a superior AUC value (0.8741), sensitivity (79.08%), negative predictive value (79.52%) and test accuracy (79.42%), while the Geneva score presented superior specificity (100%) and positive predictive value (100%) compared with the SPPH-ECG-model. In conclusion, the SPPH-ECG-model may serve a role in ruling out acPE in patients during diagnostic testing and may diagnose acPE rapidly and accurately in combination with the Geneva scoring system.