In-Hospital Prognostic Value of Electrocardiographic Parameters Other Than ST-Segment Changes in Acute Myocardial Infarction: Literature Review and Future Perspectives

QTc Interval: A frequently unrecognized electrocardiographic interval

The QT interval, an electrocardiographic temporal representation of the ventricular depolarization and repolarization, is an integral parameter that must be carefully evaluated to gather critical information regarding electrical instability that may cause malignant ventricular dysrhythmias or sudden cardiac death. The QT interval is affected by several inheritable and acquired factors, such as genetic mutations, electrolyte disturbances, and medication interactions. We strongly believe that prompt and accurate recognition of any QT interval abnormalities is critical in many clinical settings. This concise review article highlights the importance of accurate measurement of the QT interval, enhances understanding of the most prevalent factors yielding abnormalities within the QT interval and the prognostic value of the QT interval, as well as provides several key practical reminders for healthcare professionals to strengthen our clinical practice.

Diagnostic value of nocturnal trend changes in a dynamic electrocardiogram for coronary heart disease

OBJECTIVE

To explore the diagnostic value of intermittent changes in the nocturnal ST segment trend graph in a dynamic electrocardiogram (ECG) for coronary heart disease (CHD).

METHODS

A total of 205 patients who underwent coronary angiography were included in this retrospective study. The study sample was determined through a power analysis aimed at achieving power of 80% with a significance level of 0.05. The participants were divided into the CHD (n = 101) and the non-CHD (n = 104) group, based on the degree of coronary artery diameter stenosis. The morphological changes in the ST segment trend graph were observed and divided into two categories: 'wall-shaped' and 'peak-shaped' changes.

RESULTS

Among the 205 patients, 94 had nocturnal ST segment dynamic changes and 111 did not. The detection rate of CHD without nocturnal ST segment dynamic changes was 21.59%, significantly lower than the detection rate of 93.18% in those with nocturnal ST segment changes, reflecting a statistically significant difference (P < 0.05). The positive rate of ST segment in patients with single-vessel disease (71.88%) was lower than in patients with multi-vessel disease (78.57%), and both differences were statistically significant (P < 0.05). The duration of ST segment trend graph changes in 94 cases in the CHD group with intermittent changes in the nocturnal ST segment trend graph was higher than in the non-CHD group, but no significant difference was observed (P > 0.05). The detection rate of CHD in the peak-shaped dynamic change group of the nocturnal ST segment trend graph was significantly higher (76/82) than in the wall-shaped (6/82) dynamic change group (P < 0.05).

CONCLUSION

Peak-shaped changes in the nocturnal ST segment trend graph indicate coronary artery lesions. Nocturnal ST segment changes observed through dynamic ECG monitoring can serve as a valuable non-invasive predictor for CHD, providing a feasible method for early diagnosis and intervention in clinical practice.

A patient with acute myocardial infarction with electrocardiogram Aslanger's pattern

BACKGROUND

Aslanger's pattern in electrocardiogram (ECG) indicates that patients may have acute inferior myocardial infarction(AMI) with concomitant critical stenoses on other coronary arteries, which needs to be evaluated the timing of revascularization as risk equivalents of ST elevation myocardial infarction(STEMI).

CASE PRESENTATION

The patient was a 62-year-old male with chief complaint of intermittent exertional subxiphoid pain for 20 days from 30th June. One day after the last episode (19th July), the 18-lead electrocardiogram showed ST segment elevation of 0.05-0.1mV in lead III, ST segment depression in leads I, avL, and V2-V6, T wave inversion with positive terminal vector in lead V4-V5, and positive T wave in lead V6, which indicated Aslanger's pattern. With increased Troponin I (0.162ng/mL, 0-0.02), The patient was diagnosed as acute non-ST-segment elevation myocardial infarction (NSTEMI) and admitted to coronary ward on 20th July. The coronary angiography showed 95% stenosis in the distal left main coronary artery (LM) to the ostium of the left anterior descending artery (LAD), 90% stenosis in the proximal segment of the LAD, and 80% stenosis in the middle segment of the LAD, and TIMI blood flow was graded score 2. Three drug-eluting stents were implanted at the lesions. The patient's ECG returned close to normal one month after revascularization.

CONCLUSION

We presented an acute coronary syndrome case whose ECG showed with Aslanger's pattern (i.e., isolated ST-segment elevation in lead III, associated ST-segment depression in lead V4-V6 with positive T wave/terminal vector, and greater ST-segment elevation in lead V1 than in lead V2), and was confirmed severe stenosis of the LM and the proximal segment of the LAD via coronary angiography. In clinical practice, especially in the emergency, patients with ECG presenting Aslanger's pattern should be urgently evaluated with prompt treatment, and the timing of emergency coronary angiography and revascularization should be evaluated to avoid adverse outcomes caused by delayed treatment.

End-to-End Convolutional Neural Network Model to Detect and Localize Myocardial Infarction Using 12-Lead ECG Images without Preprocessing

In recent years, many studies have proposed automatic detection and localization techniques for myocardial infarction (MI) using the 12-lead electrocardiogram (ECG). Most of them applied preprocessing to the ECG signals, e.g., noise removal, trend removal, beat segmentation, and feature selection, followed by model construction and classification based on machine-learning algorithms. The selection and implementation of preprocessing methods require specialized knowledge and experience to handle ECG data. In this paper, we propose an end-to-end convolutional neural network model that detects and localizes MI without such complicated multistep preprocessing. The proposed model executes comprehensive learning for the waveform features of unpreprocessed raw ECG images captured from 12-lead ECG signals. We evaluated the classification performance of the proposed model in two experimental settings: ten-fold cross-validation where ECG images were split randomly, and two-fold cross-validation where ECG images were split into one patient and the other patients. The experimental results demonstrate that the proposed model obtained MI detection accuracies of 99.82% and 93.93% and MI localization accuracies of 99.28% and 69.27% in the first and second settings, respectively. The performance of the proposed method is higher than or comparable to that of existing state-of-the-art methods. Thus, the proposed model is expected to be an effective MI diagnosis tool that can be used in intensive care units and as wearable technology.

Utilization of Risk Scores for Coronary Heart Disease Diagnosis in Rural China

Objective

The current study was to design a cardiovascular risk score for the diagnosis of coronary heart disease (CHD) in the rural area of China and the sensitivity and specificity of this score would be assessed.

Methods

A total of 520 patients were enrolled and based on the results from coronary artery angiography, patients were divided into three groups: CHD group (coronary artery ≥50% stenosis), atherosclerosis group (coronary artery <50% stenosis) and normal groups (without stenosis). Between-group differences were evaluated and the sensitivity and specificity of cardiovascular risk score were evaluated.

Results

Compared to the normal and atherosclerosis groups, patients in the CHD group were older, had higher body mass index, and more likely to be smoking and obese, and had dyslipidemia, hypertension and diabetes, and had higher cardiovascular risk score (4.05 ± 2.15 vs 2.94 ± 1.90 vs 2.54 ± 1.59). Patients in the CHD group were more likely to have cardiovascular risk scores ≥2 (90.2% CHD group vs 74.2% atherosclerosis group vs 76.1% normal group, P < 0.05). The area under the ROC was 0.673, with 95% confidence interval was 0.623-0.722 (P < 0.001), and the sensitivity and specificity were highest when the cardiovascular risk score was 4, indicating that the value of cardiovascular risk score of 4 was a good cutoff point for CHD diagnosis.

Conclusion

Using cardiovascular risk score can improve CHD diagnosis which may help to reduce health disparities between rural and urban area.

Genetically Determined Serum Calcium Levels and Markers of Ventricular Repolarization: A Mendelian Randomization Study in the UK Biobank

BACKGROUND

ECG markers of ventricular depolarization and repolarization are associated with an increased risk of arrhythmia and sudden cardiac death. Our prior work indicated lower serum calcium concentrations are associated with longer QT and JT intervals in the general population. Here, we investigate whether serum calcium is a causal risk factor for changes in ECG measures using Mendelian randomization (MR).

METHODS

Independent lead variants from a newly performed genome-wide association study for serum calcium in >300 000 European-ancestry participants from UK Biobank were used as instrumental variables. Two-sample MR analyses were performed to approximate the causal effect of serum calcium on QT, JT, and QRS intervals using an inverse-weighted method in 76 226 participants not contributing to the serum calcium genome-wide association study. Sensitivity analyses including MR-Egger, weighted-median estimator, and MR pleiotropy residual sum and outlier were performed to test for the presence of horizontal pleiotropy.

RESULTS

Two hundred five independent lead calcium-associated variants were used as instrumental variables for MR. A decrease of 0.1 mmol/L serum calcium was associated with longer QT (3.01 ms [95% CI, 2.03 to 3.99]) and JT (2.89 ms [1.91 to 3.87]) intervals. A weak association was observed for QRS duration (secondary analyses only). Results were concordant in all sensitivity analyses.

CONCLUSIONS

These analyses support a causal effect of serum calcium levels on ventricular repolarization, in a middle-aged population of European-ancestry where serum calcium concentrations are likely stable and chronic. Modulation of calcium concentration may, therefore, directly influence cardiovascular disease risk.