Predictive Role of Angle of Deviation, QRS Complex RVH, LVH and T Wave Amplitudes in Preeclamptic Pregnant Women in The Third Trimester of Pregnancy

Authors

  • Edebiri O.E Ambrose Alli University
  • Nwankwo A. A Abia State University
  • Akpe P. E University of Benin
  • Mbanaso E.L Abia State University
  • Obiesi C. N David Umahi Federal University Health Services
  • Chukwu J.A.O Gregory University

DOI:

https://doi.org/10.62951/ijph.v2i1.326

Keywords:

Preeclampsia, angle, deviation, Complex, QRS

Abstract

The use of ECG patterns as predictors of preeclampsia offers a promising approach, as it is a widely available and cost-effective tool. Specific ECG patterns, including angle of deviation, QRS Complex (Right Ventricular Hypertrophy (RVH) , Left Ventricular Hypertrophy (LVH)), and T wave amplitudes as a potential tool for predicting preeclampsia. The aim of this study is to investigate the predictive role of angle of deviation, QRS Complex (Right Ventricular Hypertrophy (RVH) , Left Ventricular Hypertrophy (LVH)), and T wave amplitudes in preeclamptic pregnant women during the third trimester. Fourty (40) consenting pregnant women were recruited from St. Philomina Catholic Hospital, Edo State, Nigeria. These subjects consisted of  twenty (20) normotensive  and twenty (20) preeclamptic pregnant women in their  third trimester of pregnancy. After the subjects were  identified and recruited into the study, they were taken to the laboratory where their vital signs was taken and their ECG patterns recorded with ECG machine. Data obtained from this study were analysed using Graph Pad Prism 9. Results generated were expressed as mean ± SEM and a P-value of ≤ 0.05 were considered statistically significant. Results from this present study show no significant differences were observed in QRS complex angles related to right ventricular hypertrophy (RVH) between normotensive and preeclamptic pregnant women. Notably, there was a significant increase in QRS complex related to left ventricular hypertrophy (LVH) in preeclamptic pregnant women, indicating left ventricular remodeling's importance. Moreover, there was a significant increase in T wave amplitude, this suggests underlying myocardial electrical remodeling or dysfunction in preeclampsia, emphasizing the need for cardiovascular monitoring. The study underscores the multifactorial nature of cardiovascular changes in preeclampsia and highlights the potential of ECG parameters in aiding early detection.

Downloads

Download data is not yet available.

References

Armaly, Z., Jadaon, J. E., Jabbour, A., & Abassi, Z. A. (2018). Preeclampsia: Novel mechanisms and potential therapeutic approaches. Frontiers in Physiology, 9, 973. https://doi.org/10.3389/fphys.2018.00973

Chaiworapongsa, T., Chaemsaithong, P., Yeo, L., & Romero, R. (2014). Preeclampsia part 1: Current understanding of its pathophysiology. Nature Reviews Nephrology, 10(8), 466–480. https://doi.org/10.1038/nrneph.2014.103

de Alencar Neto, J. N., de Andrade Matos, V. F., Scheffer, M. K., Felicioni, S. P., De Marchi, M. F. N., & Martínez-Sellés, M. (2024). ST segment and T wave abnormalities: A narrative review. Journal of Electrocardiology. https://doi.org/10.1016/j.jelectrocard.2024.01.008

Duley, L. (2009). The global impact of pre-eclampsia and eclampsia. Seminars in Perinatology, 33(3), 130–137. https://doi.org/10.1053/j.semperi.2009.02.010

Jiang, L., Liang, W., Xie, R., Fang, X., Liu, D., Zhang, M., & Shi, C. (2023). Assessment of left ventricular structure and function in preeclampsia subtypes by multimodal echocardiography. Journal of Obstetrics and Gynaecology Research, 49(8), 2031–2039. https://doi.org/10.1111/jog.15588

Khalil, A., O'Brien, P., Granger, J. P., & Thadhani, R. (2019). Preeclampsia: Pathophysiology and integrative considerations. Journal of Nutrition and Metabolism, 2019, 1–11. https://doi.org/10.1155/2019/9248592

Khan, J. A., Ashraf, A., Fayaz, F., & Qureshi, W. (2023). Electrocardiographic pattern in hypertensive disorders of pregnancy. International Journal of Research in Medical Sciences, 11(11), 4154–4159. https://doi.org/10.18203/issn.2320-6012

Nagel, C. (2023). Multiscale Cohort Modeling of Atrial Electrophysiology: Risk Stratification for Atrial Fibrillation through Machine Learning on Electrocardiograms (Vol. 27). KIT Scientific Publishing. https://doi.org/10.5445/KSP/1000135988

Pegorie, M., Khalil, A., & Green, M. (2023). Electrocardiographic changes in pre-eclampsia: A systematic review and meta-analysis. European Journal of Obstetrics & Gynecology and Reproductive Biology, 280, 1–8. https://doi.org/10.1016/j.ejogrb.2023.01.008

Vondrak, J., & Penhaker, M. (2022). Review of processing pathological vectorcardiographic records for the detection of heart disease. Frontiers in Physiology, 13, 856590. https://doi.org/10.3389/fphys.2022.856590

Downloads

Published

2025-02-21

How to Cite

Edebiri O.E, Nwankwo A. A, Akpe P. E, Mbanaso E.L, Obiesi C. N, & Chukwu J.A.O. (2025). Predictive Role of Angle of Deviation, QRS Complex RVH, LVH and T Wave Amplitudes in Preeclamptic Pregnant Women in The Third Trimester of Pregnancy. International Journal of Public Health, 2(1), 95–106. https://doi.org/10.62951/ijph.v2i1.326