U Wave Features in Body Surface Potential Mapping in Post-Myocardial Infarction Patients

Predictive Value of Tpeak-to-Tend/QT for Early Ventricular Arrhythmias and Arrhythmogenic Death in Patients with Anterior ST Elevation Myocardial Infarction

BACKGROUND

Patients with anterior ST elevation myocardial infarction (STEMI) are vulnerable to life-threatening ventricular arrhythmia and arrhythmic death. This study aimed to investigate the predictive value of Tpeak-to-Tend (TpTe) and TpTe/QT ratio in patients with anterior STEMI on admission for the occurrence of in-hospital life-threatening ventricular arrhythmias and arrhythmic death.

METHODS

This observational cross-sectional research was performed on patients with anterior STEMI who showed up within 12 hours of the beginning of symptoms and received the initial percutaneous coronary intervention (pPCI). The primary study endpoints included the assessment of sustained ventricular arrhythmias and all-cause/arrhythmic deaths throughout the hospitalization. Data collection involved clinical history, vital signs monitoring, ECG measurements, LVEF evaluation, and performance of pPCI procedures.

RESULTS

The studied patients had a mean age of 53 ± 11 years. Patients with arrhythmic events displayed a significant rise in QT dispersion, TpTe, TpTe/QT, and arrhythmic death rates (P < 0.05). A multivariate logistic regression examination revealed that HR (with an OR of 1.037 and a 95% CI of 1.004 to 1.071, P = 0.027), TpTe (with an OR of 1.025 and a 95% CI of 1.004 to 1.047, P = 0.022), and TpTe/QT (with an OR of 5.464 and a 95% CI of 2.027 to 14.726, P = 0.001) were found to be significant predictors of arrhythmic events or mortality.

CONCLUSION

In patients with anterior STEMI, TpTe and TpTe/QT ratio are significant predictors of in-hospital VA and arrhythmic death. Higher TpTe and TpTe/QT values are linked to a higher risk of these occurrences.

Body Surface Potential Mapping: Contemporary Applications and Future Perspectives

Body surface potential mapping (BSPM) is a noninvasive modality to assess cardiac bioelectric activity with a rich history of practical applications for both research and clinical investigation. BSPM provides comprehensive acquisition of bioelectric signals across the entire thorax, allowing for more complex and extensive analysis than the standard electrocardiogram (ECG). Despite its advantages, BSPM is not a common clinical tool. BSPM does, however, serve as a valuable research tool and as an input for other modes of analysis such as electrocardiographic imaging and, more recently, machine learning and artificial intelligence. In this report, we examine contemporary uses of BSPM, and provide an assessment of its future prospects in both clinical and research environments. We assess the state of the art of BSPM implementations and explore modern applications of advanced modeling and statistical analysis of BSPM data. We predict that BSPM will continue to be a valuable research tool, and will find clinical utility at the intersection of computational modeling approaches and artificial intelligence.