Correlation between P Wave Dispersion, QRS Duration & QT Dispersion in Hospital Events in Cases of Acute Coronary Syndrome

Coronary slow flow is a rare, clinically important entity observed in acute coronary syndrome. The pathophysiological mechanism is not fully elucidated. We investigated patients with chest pain who had angiographic features consistent with the coronary slow flow. One hundred ten patients were included. Electrocardiography, echocardiography, and angiography results were retrospectively noted. The mean age was 56.4. Fifty-eight were male, and fifty-two were female. The control group consisted of patients with normal angiography. Patients had higher diastolic blood pressure, lower mean ejection fraction, higher average left ventricular end-diastolic diameter, and higher mean left atrial size than the control group (p=0.009,p=0.017,p=0.041,andp<0.001, resp.). Patients had higher average V1 ID, V6 ID, P wave dispersion, TFC LAD, TFC Cx, TFC RCA, and TFC levels than the control group. A significant linear positive relationship was found between the V1 ID and the TFC LAD, TFC Cx, TFC RCA, and TFC; also between the V6 ID and the TFC LAD, TFC Cx, TFC RCA, and TFC. Angiographic and electrocardiographic features are suggestive and diagnostic for the coronary slow flow syndrome. Although when regarded as a benign condition, coronary slow flow should be diagnosed, followed up, and treated as many of laboratory features suggest ischemic events.

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Analysis of QT Dispersion, Corrected QT Dispersion, and P-Wave Dispersion Values in Alcohol Use Disorder Patients With Excessive Alcohol Use

The Primary Care Companion For CNS Disorders ◽

10.4088/pcc.19m02541 ◽

2020 ◽

Vol 22 (1) ◽

Cited By ~ 1

Author(s):

Sema Baykara ◽

Davut Ocak ◽

Şule Şirin Berk ◽

Sedat Köroğlu

Keyword(s):

Alcohol Use ◽

Alcohol Use Disorder ◽

Qt Dispersion ◽

Wave Dispersion ◽

P Wave ◽

P Wave Dispersion ◽

Excessive Alcohol

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QT dispersion and P wave dispersion in patients with fibromyalgia

European Journal of Rheumatology ◽

10.5152/eurjrheum.2016.042 ◽

2017 ◽

Vol 3 (4) ◽

pp. 165-168 ◽

Cited By ~ 2

Author(s):

Servet Yolbas ◽

Ahmet Yildirim ◽

Deccane Duzenci ◽

Bulent Karakaya ◽

Mustafa Necati Dagli ◽

...

Keyword(s):

Qt Dispersion ◽

Wave Dispersion ◽

P Wave ◽

P Wave Dispersion

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NON-INVASIVE ESTIMATION OF DIABETES RELATED FEATURES FROM ECG USING GRAPHICAL PROGRAMAMING LANGUAGE AND MATLAB

Journal of Mechanics in Medicine and Biology ◽

10.1142/s0219519412400167 ◽

2012 ◽

Vol 12 (04) ◽

pp. 1240016

Author(s):

V. KALPANA ◽

S. T. HAMDE ◽

L. M. WAGHMARE

Keyword(s):

Virtual Instrument ◽

Qt Dispersion ◽

Wave Dispersion ◽

P Wave ◽

Biomedical Sciences ◽

P Wave Dispersion ◽

Cardiac Health ◽

Glucose Levels ◽

St Depression ◽

Blood Glucose Levels

Electrocardiography deals with the electrical activity of the heart. The condition of cardiac health is given by the electrocardiogram (ECG). ECG analysis is one of the most important aspects of research in the field of biomedical sciences and healthcare. The precision in the identification of various parameters in the ECG is of great importance for the reliability of an automated ECG analyzing system and diagnosis of cardiac diseases. Many algorithms have been developed in the last few years, each with their own advantages and limitations. In this work, we have developed an algorithm for 12-lead ECG parameter detection which works in three steps. Initially, the signal is denoised by the wavelet transform approach using a graphical programming language called LabVIEW (Laboratory Virtual Instrument Engineering Workbench). Next, primary features are detected from the denoised ECG signal using Matlab, and lastly, the secondary features related to diabetes are estimated from the detected primary features. Diabetes mellitus (DM), which is characterized by raised blood glucose levels in an individual, affects an estimated 2–4% of the world's population, making it one of the major chronic illnesses prevailing today. Recently, there has been increasing interest in the study of relationship between diabetes and cardiac health. Thus, in this work, we estimate diabetic-related secondary ECG features like corrected QT interval (QTc), QT dispersion (QTd), P wave dispersion (PD), and ST depression (STd). Our software performance is evaluated using CSE DS-3 multi-lead data base and the data acquired at SGGS IE & T, Nanded, MS, which contains 5000 samples recorded at a sampling frequency of 500 HZ. The proposed algorithm gives a sensitivity of 99.75% and a specificity of 99.83%.

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Effect of obesity on P-wave dispersion and QT dispersion in women

International Journal of Obesity ◽

10.1038/sj.ijo.0803233 ◽

2006 ◽

Vol 30 (6) ◽

pp. 957-961 ◽

Cited By ~ 44

Author(s):

E Seyfeli ◽

M Duru ◽

G Kuvandık ◽

H Kaya ◽

F Yalcin

Keyword(s):

Qt Dispersion ◽

Wave Dispersion ◽

P Wave ◽

P Wave Dispersion

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P-wave and QT Interval Dispersion Analysis in Children with End Stage Renal Disease on Regular Hemodialysis

Journal of Advances in Medicine and Medical Research ◽

10.9734/jammr/2020/v32i330384 ◽

2020 ◽

pp. 69-77

Author(s):

Mai Attia ◽

Shimaa El-Nemr ◽

Hend Abd-Elnabi ◽

Amr Zoair

Keyword(s):

Renal Disease ◽

End Stage Renal Disease ◽

Qt Interval ◽

Qt Dispersion ◽

Wave Dispersion ◽

P Wave ◽

P Wave Dispersion ◽

Stage Renal Disease ◽

End Stage ◽

Regular Hemodialysis

Objectives: The consequences of hemodialysis on P-wave dispersion and QT dispersion have not been unequivocally documented and understood and may be complex. To investigate homogeneity disorders of atrial conduction and ventricular repolarization and tendency to develop various arrhythmias by demonstrating the effects of hemodialysis in children with end stage renal disease through assessment of P-wave dispersion and QT dispersion (By electrocardiograghy). Methods: Twenty end stage renal disease patients on conventional hemodialysis for at least 12 months and twenty healthy, age and sex matched volunteers were included. Patients underwent echocardiography to exclude any abnormalities of cardiac valves or muscle. A 12-lead electrocardiogram was undertaken in order to measure minimal and maximal (P wave and QT interval) durations, P wave dispersion and QT dispersion. Results: In patient group, males were 13, females were 7 with mean age of 11.9 ± 3.4 years, mean P wave dispersion and QT dispersion were significantly longer than control group. P wave dispersion was significantly shorter after dialysis (mean= 34 ± 13.1 ms) than before dialysis (mean=42.4 ± 14 ms), whereas QT dispersion was longer after dialysis (59 ± 19 ms) than before dialysis (55.5 ± 17 ms) but the differences in QT dispersion was not significant. Also, there was no correlation between neither P wave dispersion nor QT dispersion and the electrolytes. Conclusion: P wave dispersion and QT dispersion was found to be higher in end stage renal disease children on regular hemodialysis than healthy control subjects, indicating heterogeneity disorders of atrial conduction and ventricular repolarization in these patients and tendency to develop various arrhythmias.

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