Literature DB >> 32560524

Associations between Intrinsic Heart Rate, P Wave and QT Interval Durations and Pulse Wave Analysis in Patients with Hypertension and High Normal Blood Pressure.

Ioana Mozos1,2, Cristina Gug3, Costin Mozos4, Dana Stoian5, Marius Pricop6, Daniela Jianu7,8.   

Abstract

The present study aimed to explore the relationship between electrocardiographic (ECG) and pulse wave analysis variables in patients with hypertension (HT) and high normal blood pressure (HNBP). A total of 56 consecutive, middle-aged hypertensive and HNBP patients underwent pulse wave analysis and standard 12-lead ECG. Pulse wave velocity (PWV), heart rate, intrinsic heart rate (IHR), P wave and QT interval durations were as follows: 7.26 ± 0.69 m/s, 69 ± 11 beats/minute, 91 ± 3 beats/minute, 105 ± 22 mm and 409 ± 64 mm, respectively. Significant correlations were obtained between PWV and IHR and P wave duration, respectively, between early vascular aging (EVA) and P wave and QT interval durations, respectively. Linear regression analysis revealed significant associations between ECG and pulse wave analysis variables but multiple regression analysis revealed only IHR as an independent predictor of PWV, even after adjusting for blood pressure variables and therapy. Receiver-operating characteristic (ROC) curve analysis revealed P wave duration (area under curve (AUC) = 0.731; 95% CI: 0.569-0.893) as a predictor of pathological PWV, and P wave and QT interval durations were found as sensitive and specific predictors of EVA. ECG provides information about PWV and EVA in patients with HT and HNBP. IHR and P wave durations are independent predictors of PWV, and P wave and QT interval may predict EVA.

Entities:  

Keywords:  P wave; QT interval; early vascular aging; electrocardiogram; heart rate; high normal blood pressure; hypertension; intrinsic heart rate; pulse wave velocity

Year:  2020        PMID: 32560524     DOI: 10.3390/ijerph17124350

Source DB:  PubMed          Journal:  Int J Environ Res Public Health        ISSN: 1660-4601            Impact factor:   3.390


  2 in total

1.  Machine Learning for Electrocardiographic Features to Identify Left Atrial Enlargement in Young Adults: CHIEF Heart Study.

Authors:  Chu-Yu Hsu; Pang-Yen Liu; Shu-Hsin Liu; Younghoon Kwon; Carl J Lavie; Gen-Min Lin
Journal:  Front Cardiovasc Med       Date:  2022-03-01

2.  Genetic Counseling and Management: The First Study to Report NIPT Findings in a Romanian Population.

Authors:  Cristina Gug; Ioana Mozos; Adrian Ratiu; Anca Tudor; Eusebiu Vlad Gorduza; Lavinia Caba; Miruna Gug; Catalina Cojocariu; Cristian Furau; Gheorghe Furau; Monica Adriana Vaida; Dorina Stoicanescu
Journal:  Medicina (Kaunas)       Date:  2022-01-05       Impact factor: 2.430

  2 in total

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