Relationships of electrocardiographic parameters with ambulatory hypertension in young and healthy adults

Aeschbacher, Stefanie; Metin, Fatih; Bossard, Matthias; Schoen, Tobias; Rotz, Mirco von; Mettler, Heidi M.; Abächerli, Roger; Risch, Martin; Risch, Lorenz; Conen, David

doi:10.1016/j.ijcard.2015.09.013

Cited by 5 publications

(5 citation statements)

References 27 publications

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“…QRS-amplitude increase was significant only for the HTN group. This was in accordance with [ 31 ], where increase of R and S-peaks in the group of HTN compared to the group of normotensive, was found in the examined leads;…”

Section: Discussionsupporting

confidence: 93%

Modifications in Electrocardiographic and Vectordardiographic Morphological Parameters in Elderly Males as Result of Cardiovascular Diseases and Diabetes Mellitus

2022

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Purpose. Morphological electrocardiographic and vectorcardiographic features have been used in the detection of cardiovascular diseases and prediction of the risk of cardiac death for a long time. The objective of the current study was to investigate the morphological electrocardiographic modifications in the presence of cardiovascular diseases and diabetes mellitus in an elderly male population, most of them with multiple comorbidities. Methods. A database of ECG recordings from the Italian Longitudinal Study on Aging (ILSA-CNR), created to evaluate physiological and pathological modifications related to aging, was considered. The study examined a group of 1109 males with full clinical documentation aged 65–84 years. A healthy control group (219 individuals) was compared to the groups of diabetes mellitus (130), angina pectoris (99), hypertension (607), myocardial infarction (160), arrhythmia (386), congestive heart failure (73), and peripheral artery disease (95). Twenty-one electrocardiographic features were explored, and the effects of cardiovascular diseases and diabetes on these parameters were analyzed. The three-years mortality index was derived and analyzed. Results and Conclusions. Myocardial infarction and arrhythmia were the diagnostic groups that showed a significant deviation of 11 electrocardiographic parameters compared to the healthy group, followed by hypertension and congestive heart failure (10), angina pectoris (9), and diabetes mellitus and peripheral artery disease (8). In particular, a set of three parameters (QRS and T roundness and principal component analysis of T wave) increased significantly, whereas four parameters (T amplitude, T maximal vector, T vector ratio, and T wave area dispersion) decreased significantly in all cardiovascular diseases and diabetes mellitus with respect to healthy group. The QRS parameters show a more specific discrimination with a single disease or a group of diseases, whereas the T-wave features seems to be influenced by all the pathological conditions. The present investigation of disease-related electrocardiographic parameters changes can be used in assessing the risk analysis of cardiac death, and gender medicine.

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Section: Discussionsupporting

confidence: 93%

Modifications in Electrocardiographic and Vectordardiographic Morphological Parameters in Elderly Males as Result of Cardiovascular Diseases and Diabetes Mellitus

2022

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“…T wave amplitude in CM5 is influenced by LV pressure and/or volume [7], i.e., T wave amplitude is augmented by increased LV filling pressure and/or volume after the long RR intervals in healthy individuals [8]. Temporary changes of LV loading condition modulates transmural repolarization gradient and hence repolarization wave morphologies, which is mediated by mechano-electrical coupling [9].…”

Section: Figure 3 Discussionmentioning

confidence: 99%

Rate-Dependent Repolarization Dynamics: Correlation between Electrocardiographic T Wave and U Wave

Maruyama¹

2018

JCCCVT

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U wave is the last ventricular repolarization component in electrocardiogram (ECG). Rate-dependent amplitude adaptation of U wave was less known relative to that of T wave. We experienced a patient presenting palpitation and showing ECG associated with clear physiologic upward U wave. Echocardiogram demonstrated no structural heart diseases and normal left ventricular (LV) function. T and U wave amplitudes were simultaneously plotted as a function of the preceding RR intervals using ambulatory ECG. U wave amplitude was augmented monotonously according to an increase of the preceding RR interval, whereas T wave amplitude was increased to the maximum level in the RR interval ranging from 1,000 to 1,500 msec and decreased to a steady-state level as RR interval was further prolonged. These indicate that rate-dependent repolarization gradient in T wave differs from that in physiologic U wave, which is mediated by mechano-electrical coupling under pause-dependent LV pressure and/or volume augmentation.

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“…The fragmented QRS complex is found more often with high blood pressure patients, also with a higher amplitude of the R and S wave. In the case of the T wave, the features are the same but the P wave was found to be related in some way to a change in blood pressure [ 90 , 93 , 94 , 95 ]. In previous studies, along with other discoveries, there were some shortcomings.…”

Section: Methodsmentioning

confidence: 99%

“…In previous studies, along with other discoveries, there were some shortcomings. For example, in some studies [ 91 , 92 , 94 ], the BMIs were not well spread out, some have patients mostly of a young age, some have limited patients with specific prior diagnosis, and several studies did not report any comorbidities or confounders, etc., [ 90 , 95 ]. These limitations require further study with these features before finalizing a specific list.…”

Section: Methodsmentioning

confidence: 99%

Cuffless Blood Pressure Measurement Using Linear and Nonlinear Optimized Feature Selection

Mamun

Alouani

2022

Diagnostics

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The cuffless blood pressure (BP) measurement allows for frequent measurement without discomfort to the patient compared to the cuff inflation measurement. With the availability of a large dataset containing physiological waveforms, now it is possible to use them through different learning algorithms to produce a relationship with changes in BP. In this paper, a novel cuffless noninvasive blood pressure measurement technique has been proposed using optimized features from electrocardiogram and photoplethysmography based on multivariate symmetric uncertainty (MSU). The technique is an improvement over other contemporary methods due to the inclusion of feature optimization depending on both linear and nonlinear relationships with the change of blood pressure. MSU has been used as a selection criterion with algorithms such as the fast correlation and ReliefF algorithms followed by the penalty-based regression technique to make sure the features have maximum relevance as well as minimum redundancy. The result from the technique was compared with the performance of similar techniques using the MIMIC-II dataset. After training and testing, the root mean square error (RMSE) comes as 5.28 mmHg for systolic BP and 5.98 mmHg for diastolic BP. In addition, in terms of mean absolute error, the result improved to 4.27 mmHg for SBP and 5.01 for DBP compared to recent cuffless BP measurement techniques which have used substantially large datasets and feature optimization. According to the British Hypertension Society Standard (BHS), our proposed technique achieved at least grade B in all cumulative criteria for cuffless BP measurement.

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Relationships of electrocardiographic parameters with ambulatory hypertension in young and healthy adults

Cited by 5 publications

References 27 publications

Modifications in Electrocardiographic and Vectordardiographic Morphological Parameters in Elderly Males as Result of Cardiovascular Diseases and Diabetes Mellitus

Modifications in Electrocardiographic and Vectordardiographic Morphological Parameters in Elderly Males as Result of Cardiovascular Diseases and Diabetes Mellitus

Rate-Dependent Repolarization Dynamics: Correlation between Electrocardiographic T Wave and U Wave

Cuffless Blood Pressure Measurement Using Linear and Nonlinear Optimized Feature Selection

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