Dataset Information

Office and Home Blood Pressures as Determinants of Electrocardiographic Left Ventricular Hypertrophy Among Black Nigerians Compared With White Flemish.

ABSTRACT: The association of electrocardiographic left ventricular hypertrophy (ECG-LVH) with blood pressure (BP) in Blacks living in sub-Saharan Africa remains poorly documented.In 225 Black Nigerians and 729 White Flemish, we analyzed QRS voltages and voltage-duration products and 12 criteria diagnostic of ECG-LVH in relation to office BP (mean of 5 consecutive readings) and home BP (duplicate morning and evening readings averaged over 1 week).In multivariable analyses, QRS voltage and voltage-duration indexes were generally higher in Blacks than Whites. By using any of 12 criteria, ECG-LVH was more prevalent among Black than White men (54.4% vs. 36.0%) with no ethnic difference among women (17.1%). Precordial voltages and voltage-duration products increased with office and home systolic BP (SBP), and increases were up to 3-fold steeper in Blacks. In Blacks vs. Whites, increases in the Sokolow-Lyon voltage associated with a 10-mm Hg higher SBP were 0.18 mV (95% confidence interval [CI], 0.09-0.26) vs. 0.06 mV (0.02-0.09) and 0.17 mV (0.07-0.28) vs. 0.11 mV (CI, 0.07-0.15) for office and home BP, respectively, with a significant ethnic gradient (P < 0.05). The risk of ECG-LVH increased more with office and home BP in Blacks than Whites.Associations of ECG voltages and voltage-duration products and risk of ECG-LVH with BP are steeper in Black Nigerians compared with a White reference population. In resource-poor settings of sub-Saharan Africa, the ECG in combination with office and home BP is an essential instrument in risk stratification across the entire BP range.

SUBMITTER: Odili AN

PROVIDER: S-EPMC5861556 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Office and Home Blood Pressures as Determinants of Electrocardiographic Left Ventricular Hypertrophy Among Black Nigerians Compared With White Flemish.

Odili Augustine N AN Thijs Lutgarde L Yang Wen-Yi WY Ogedengbe John O JO Nwegbu Maxwell M MM Jacobs Lotte L Wei Fang-Fei FF Feng Ying-Mei YM Zhang Zhen-Yu ZY Kuznetsova Tatiana T Nawrot Tim S TS Staessen Jan A JA

American journal of hypertension 20171101 11

<h4>Background</h4>The association of electrocardiographic left ventricular hypertrophy (ECG-LVH) with blood pressure (BP) in Blacks living in sub-Saharan Africa remains poorly documented.<h4>Methods</h4>In 225 Black Nigerians and 729 White Flemish, we analyzed QRS voltages and voltage-duration products and 12 criteria diagnostic of ECG-LVH in relation to office BP (mean of 5 consecutive readings) and home BP (duplicate morning and evening readings averaged over 1 week).<h4>Results</h4>In multiv ...[more]

PMID: 29059302

Similar Datasets

Project description:BackgroundLeft ventricular hypertrophy (LVH) strongly predicts cardiovascular diseases (CVD) and death. One-fourth of Thai adults suffer from hypertension. Nevertheless, the information on LVH among Thai patients with hypertension is not well characterized. We aimed to identify the prevalence and factors associated with electrocardiographic LVH (ECG-LVH) among patients with hypertension in Thailand.MethodsThe present study obtained the dataset from the Thailand Diabetes Mellitus/Hypertension study, which included hypertension patients aged 20 years and older receiving continuous care at outpatient clinics in hospitals nationwide in 2011-2015 and 2018. Meanwhile, those without a record of 12-lead electrocardiography (ECG) were excluded from the analysis. ECG-LVH was defined as the LVH noted regarding ECG interpretation in the medical records. Multivariable logistic regression analysis was utilized for determining factors associated with ECG-LVH and presented as the adjusted odds ratio (AOR) and 95% confidence interval (CI).ResultsFrom 226,420 hypertensive patients in the Thailand Diabetes Mellitus/Hypertension study, 38,807 individuals (17.1%) with ECG data recorded were included in the analysis. The mean age was 64.8 ± 11.5 years, and 62.2% were women. Overall, 1,557 study participants had ECG-LVH, with an estimated prevalence of 4.0% (95% CI, 3.8-4.2%). Age-adjusted ECG-LVH prevalence among women and men was 3.4 and 5.1%, respectively (P < 0.001). Multivariable analysis determined factors associated with ECG-LVH, including being men (AOR, 1.49; 95% CI, 1.31-1.69), individuals aged 70 to 79 years (AOR, 1.56; 95% CI, 1.20-2.02) and ≥ 80 years (AOR, 2.10; 95% CI, 1.58-2.78) compared to individuals aged less than 50 years, current smokers (AOR, 1.26; 95% CI, 1.09-1.46) compared to those who never smoked, systolic blood pressure ≥ 140 mmHg and diastolic blood pressure ≥ 90 mmHg (AOR, 1.58; 95% CI, 1.30-1.92) compared to systolic blood pressure < 140 mmHg and diastolic blood pressure < 90 mmHg.ConclusionsThe current study illustrated the prevalence of ECG-LVH among Thai patients with hypertension who had ECG recorded and identified high-risk groups who tended to have ECG-LVH. The findings underscore the need for targeted interventions, particularly among high-risk groups such as older individuals, men, and current smokers, to address modifiable factors associated with ECG-LVH.

Project description:The electrocardiogram (ECG) is the most common tool used to predict left ventricular hypertrophy (LVH). However, it is limited by its low accuracy (<60%) and sensitivity (30%). We set forth the hypothesis that the Machine Learning (ML) C5.0 algorithm could optimize the ECG in the prediction of LVH by echocardiography (Echo) while also establishing ECG-LVH phenotypes. We used Echo as the standard diagnostic tool to detect LVH and measured the ECG abnormalities found in Echo-LVH. We included 432 patients (power = 99%). Of these, 202 patients (46.7%) had Echo-LVH and 240 (55.6%) were males. We included a wide range of ventricular masses and Echo-LVH severities which were classified as mild (n = 77, 38.1%), moderate (n = 50, 24.7%) and severe (n = 75, 37.1%). Data was divided into a training/testing set (80%/20%) and we applied logistic regression analysis on the ECG measurements. The logistic regression model with the best ability to identify Echo-LVH was introduced into the C5.0 ML algorithm. We created multiple decision trees and selected the tree with the highest performance. The resultant five-level binary decision tree used only six predictive variables and had an accuracy of 71.4% (95%CI, 65.5-80.2), a sensitivity of 79.6%, specificity of 53%, positive predictive value of 66.6% and a negative predictive value of 69.3%. Internal validation reached a mean accuracy of 71.4% (64.4-78.5). Our results were reproduced in a second validation group and a similar diagnostic accuracy was obtained, 73.3% (95%CI, 65.5-80.2), sensitivity (81.6%), specificity (69.3%), positive predictive value (56.3%) and negative predictive value (88.6%). We calculated the Romhilt-Estes multilevel score and compared it to our model. The accuracy of the Romhilt-Estes system had an accuracy of 61.3% (CI95%, 56.5-65.9), a sensitivity of 23.2% and a specificity of 94.8% with similar results in the external validation group. In conclusion, the C5.0 ML algorithm surpassed the accuracy of current ECG criteria in the detection of Echo-LVH. Our new criteria hinge on ECG abnormalities that identify high-risk patients and provide some insight on electrogenesis in Echo-LVH.

Dataset Information

Office and Home Blood Pressures as Determinants of Electrocardiographic Left Ventricular Hypertrophy Among Black Nigerians Compared With White Flemish.

Publications

Office and Home Blood Pressures as Determinants of Electrocardiographic Left Ventricular Hypertrophy Among Black Nigerians Compared With White Flemish.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets