The vectorcardiogram in dorsal or posterior myocardial infarction

Tranchesi, J; Teixeira, Vitor; Ebaid, Munir; Boccalandro, I.; Bocanegra, José; Pileggi, F

doi:10.1016/0002-9149(61)90507-0

Cited by 23 publications

(5 citation statements)

References 3 publications

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“…Textbooks of electrocardiography, with few exceptions,7' contain little or no reference to this category. '-6 Although some authors have commented upon individual changes that might occur in right precordial leads,8' [10][11][12][13][14][15] others have stated that diagnostic signs do not appear in the electrocardiogram as a rule. ' cepted.9 11,13,[15][16][17][18][19][20] This study was undertaken in order to determine whether the diagnosis of strictly posterior infarction could be established by conventional scalar electrocardiography.…”

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confidence: 99%

The Recognition of Strictly Posterior Myocardial Infarction by Conventional Scalar Electrocardiography

Perloff

1964

Circulation

177

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This study was undertaken in order to determine whether the standard scalar electrocardiogram contains sufficient information to permit the recognition of strictly posterior myocardial infarction. Sixteen patients were selected on the basis of vectorcardiographic evidence and four on the basis of autopsy evidence. One hundred normal adult electrocardiograms served as controls. The data indicate that strictly posterior infarction causes (1) R waves of 0.04 second in V 1 and in contiguous right anterior chest leads with upright T waves and, in the acute phase, ST-segment depressions, (2) Q waves of 0.04 second in an area posteriorly between the spine and the left scapula, (3) R/S ratios equal to or greater than one in V 1 and V 2 , (4) slurring of the descending limb of the R wave in lead V 1 due to abrupt change in QRS direction, and (5) no pathologic Q waves in the standard 12 leads unless diaphragmatic or lateral infarction coexists. Extra chest leads derived from the right anterior and left posterior thorax serve principally to corroborate the diagnoses. R waves of 0.04 second or R/S ratios equal to or greater than one in lead V 1 were also found in the normal child, complete right bundle-branch block, the Wolff-Parkinson-White syndrome with an anteriorly directed delta wave, right ventricular hypertrophy, and an occasional normal adult especially with vertical frontal plane electrical axis. Attention to these differential diagnoses and to the foregoing manifestations of strictly posterior infarction facilitate its recognition by conventional scalar electrocardiography.

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confidence: 99%

The Recognition of Strictly Posterior Myocardial Infarction by Conventional Scalar Electrocardiography

Perloff

1964

Circulation

177

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“…Another report showed that almost half of the patients with posterior MI-as detected by autopsy or ECG-had upright T wave [17]. It should be noted that the capability of ECG for predicting the presence of CAD in the absence of apparent ischemia or myocardial damage is limited [7,18,19].…”

Section: Discussionmentioning

confidence: 99%

Upright T Wave in Lead V1 as an Important Predictor of Significant Coronary Artery Disease in Patients with Chest Pain

Amirzadegan

Hosseini

Moghaddam³

et al. 2017

Zahedan J Res Med Sci

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Background: Cardiovascular disease is a worldwide great burden on the health care syste early diagnosis and treatment of CAD can reduce the mortality and morbidity. We aimed to determine the association between upright T wave in lead V1 and coronary artery disease (CAD) in patients who presented with chest pain or positive non-invasive tests in emergency department. Methods: In this retrospective cross sectional design we reviewed the clinical and coronary angiography data of patients who had normal ECG. Presence of coronary artery disease was compared between patients with and without upright T waves in V1. Results: Data of 100 patients with upright T wave more than 1.5 mm in V1 was compared with 100 patients with completely normal ECG. Male patients with coronary artery disease (CAD) were dominant in upright T wave group. However, other traditional cardiovascular risk factors were not statistically different between groups. Based on the multivariate logistic regression model and after adjustment for confounding factors (i.e. gender, dyslipidemia and smoking), presence of upright T wave in the V1 and male gender were still associated with greater risk of coronary artery disease, Odds ratio 4.6 CI 95% (3.1 -6.3) and 3.4 CI 95% (2.2 -4.8), respectively. Conclusions: In patients with chest pain and unremarkable ECG, presence of upright T wave in lead V1, is an early diagnostic tool for CAD. Male patients with chest pain and upright T wave in lead V1 probably have significant CAD.

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“…For instance, a combination of lead V1, V2, V3, and V4 provides suggestive information concerning anterior MI (AMI), whereas a combination of lead II, III, and aVF can indicate inferior MI. However, the 12lead ECG has difficulty in localizing the posterior MI (12,13). Gupta et al (14) quantified the contributions of each of 15 leads ECG signal from the PTB database individually and observed that the five leads: V5, V6, Vx, Vz, and II contain the most useful information, then they were quantified in pairs using the five best channels and results indicated that lead V6 and lead Vz can induce the best performance of the model.…”

Section: Introductionmentioning

confidence: 99%

Deep Learning for Detecting and Locating Myocardial Infarction by Electrocardiogram: A Literature Review

Xiong

Lee

Chan

2022

Front. Cardiovasc. Med.

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Myocardial infarction is a common cardiovascular disorder caused by prolonged ischemia, and early diagnosis of myocardial infarction (MI) is critical for lifesaving. ECG is a simple and non-invasive approach in MI detection, localization, diagnosis, and prognosis. Population-based screening with ECG can detect MI early and help prevent it but this method is too labor-intensive and time-consuming to carry out in practice unless artificial intelligence (AI) would be able to reduce the workload. Recent advances in using deep learning (DL) for ECG screening might rekindle this hope. This review aims to take stock of 59 major DL studies applied to the ECG for MI detection and localization published in recent 5 years, covering convolutional neural network (CNN), long short-term memory (LSTM), convolutional recurrent neural network (CRNN), gated recurrent unit (GRU), residual neural network (ResNet), and autoencoder (AE). In this period, CNN obtained the best popularity in both MI detection and localization, and the highest performance has been obtained from CNN and ResNet model. The reported maximum accuracies of the six different methods are all beyond 97%. Considering the usage of different datasets and ECG leads, the network that trained on 12 leads ECG data of PTB database has obtained higher accuracy than that on smaller number leads data of other datasets. In addition, some limitations and challenges of the DL techniques are also discussed in this review.

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The vectorcardiogram in dorsal or posterior myocardial infarction

Cited by 23 publications

References 3 publications

The Recognition of Strictly Posterior Myocardial Infarction by Conventional Scalar Electrocardiography

The Recognition of Strictly Posterior Myocardial Infarction by Conventional Scalar Electrocardiography

Upright T Wave in Lead V1 as an Important Predictor of Significant Coronary Artery Disease in Patients with Chest Pain

Deep Learning for Detecting and Locating Myocardial Infarction by Electrocardiogram: A Literature Review

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