Prediction Of Left Ventricular Hypertrophy Research Articles

Association of vascular endothelial growth factor-C, plasma angiotensinogen and left ventricular hypertrophy in patients with hemodialysis.

This study aims to examine the relationship between fluid overload, Vascular Endothelial Growth Factor C (VEGF-C), plasma Angiotensinogen (pAGT), and echocardiography findings in hemodialysis patients. This was a single-center, cross-sectional study. Patients were divided into two groups according to mid-week inter-dialytic weight gain (mIDWG): (1) mIDWG ≤3% and (2) mIDW >3%. A total of 55 patients were enrolled in this study. While the mean pAGT and left ventricular mass index were significantly higher in patients with mIDWG >3% compared to patients with mIDWG ≤3%, VEGF-C was similar between groups. pAGT ≥76.8 mcg/L, VEGF-C ≤175.5 pg/ML, and pAGT /VEGF-C ≥0.45 were significant cut-offs for the prediction of left ventricular hypertrophy(LVH). Univariate logistic regression analysis revealed that these cut-off values were significantly associated with LVH. Renin-angiotensin-aldosterone system activation may persist in hemodialysis patients with excessive IDWG. Additionally, pAGT and VEGF-C could be risk factors for the development of LVH.

Association of serum transforming growth factor β1 with left ventricular hypertrophy in children with primary hypertension

The current study was designed to assess the association of serum transforming growth factor β1 (TGF-β1) with left ventricular hypertrophy (LVH) in children with primary hypertension. The present single-center prospective trial examined 182 patients diagnosed with primary hypertension in Children’s Hospital, Capital Institute of Pediatrics, between January 2021 and September 2022. Clinical data were analyzed, and ambulatory blood pressure was assessed for 24 h. LVH, the commonest subclinical cardiac feature of hypertension, was assessed by echocardiography. According to left ventricular geometry, cases were assigned to the LVH (n = 44) and normal geometry (n = 138) groups. Serum TGF-β1 amounts were quantitated by enzyme-linked immunosorbent assay (ELISA). Receiver operating characteristic (ROC) curves were established to analyze various variables for their predictive values in LVH. Among 182 children with primary hypertension, the concentrations of serum TGF-β1 were higher in stage 2 hypertension than in stage 1 (47.3 (38.8, 52.5) vs. 46.0 (38.6, 48.2) ng/L, Z = − 2.376; P = 0.018). Additionally, serum TGF-β1 content showed a positive correlation with BP levels (P < 0.05). TGF-β1 amounts were significantly elevated in the LVH group compared with the normal geometry group (51.7 (46.1, 54.9) vs. 46.1 (38.7, 48.1) ng/L, Z = − 4.324; P = 0.0000). Serum TGF-β1 content was positively associated with LVH (r = 0.321, P = 0.0000). Multivariable logistic regression analysis showed BMI (OR = 1.188, 95% CI 1.082–1.305; P = 0.0000) and elevated serum TGF-β1 content (OR = 1.063, 95% CI 1.016–1.113; P = 0.009) independently predicted LVH. A multivariable logistic regression model considering BMI and TGF-β1 content in LVH prediction was 0.771, with sensitivity and specificity of 72.7% and 70.3%, respectively.Conclusion: These data revealed an association of serum TGF-β1 with BP in children with primary hypertension. Serum TGF-β1 concentration was positively correlated with hypertensive cardiac damage. Serum TGF-β1 might constitute a valuable molecular marker for the prediction of LVH in children with primary hypertension. The combination of BMI and TGF-β1 has a certain diagnostic and predictive value for LVH in children with primary hypertension, which may provide a new reference index for early clinical identification of hypertensive cardiac damage.What is Known:• Experimental and clinical data indicated TGF-β1 is involved in BP elevation.• TGF-β1 is positively correlated with LVMI and hypertrophy in adults.What is New:• Our current study reveals an association of serum TGF-β1 with BP in children with primary hypertension.• Elevated serum TGF-β1 level is positively associated with LVH in children with primary hypertension.• The combination of BMI and TGF-β1 has a certain diagnostic and predictive value for LVH in children with primary hypertension.

Electrocardiographic prediction of left ventricular hypertrophy in women and men with left bundle branch block - Comparison of QRS duration, amplitude and voltage-time-integral.

Standard ECG criteria for left ventricular (LV) hypertrophy rely on QRS amplitudes. However, in the setting of left bundle branch block (LBBB), ECG correlates of LV hypertrophy are not well established. We sought to evaluate quantitative ECG predictors of LV hypertrophy in the presence of LBBB. We included adult patients with typical LBBB having ECG and transthoracic echocardiogram performed within 3months of each other in 2010-2020. Orthogonal X, Y, Z leads were reconstructed from digital 12‑lead ECGs using Kors's matrix. In addition to QRS duration, we evaluated QRS amplitudes and voltage-time-integrals (VTIs) from all 12 leads, X, Y, Z leads and 3D (root-mean-squared) ECG. We used age, sex and BSA-adjusted linear regressions to predict echocardiographic LV calculations (mass, end-diastolic and end-systolic volumes, ejection fraction) from ECG, and separately generated ROC curves for predicting echocardiographic abnormalities. We included 413 patients (53% women, age 73±12years). All 4 echocardiographic LV calculations were most strongly correlated with QRS duration (all p<0.00001). In women, QRS duration ≥ 150ms had sensitivity/specificity 56.3%/64.4% for increased LV mass and 62.7%/67.8% for increased LV end-diastolic volume. In men, QRS duration ≥ 160ms had a sensitivity/specificity 63.1%/72.1% for increased LV mass and 58.3%/74.5% for increased LV end-diastolic volume. QRS duration was best able to discriminate eccentric hypertrophy (area under ROC curve 0.701) and increased LV end-diastolic volume (0.681). In patients with LBBB, QRS duration (≥ 150 in women and≥160 in men) is a superior predictor of LV remodeling esp. eccentric hypertrophy and dilation.

24HOUR, HOME AND CLINIC BLOOD PRESSURE FOR THE PREDICTION OF LEFT VENTRICULAR HYPERTROPHY IN UNTREATED HYPERTENSIVE POPULATION

Objective: The aim of this study was to investigate which way of measuring blood pressure (BP), clinic, home or 24h-ABPM, can predict better left ventricular hypertrophy in the untreated hypertensive population. Design and method: 175 consecutive subjects (42% male) aged 57.9±14.9 years were included in the study. Subjects were never treated before for hypertension. All subjects underwent 24h-ABPM on a usual working day. Home BP monitor was provided to all patients for 7 days, while office BP was measured in the clinic using a mercury sphygmomanometer. Left ventricular hypertrophy was evaluated by a cardiologist with the use of a 3D echocardiography. Results: In the univariate analysis, only home systolic and diastolic BP were independently associated with left ventricular hypertrophy, while both clinic and 24hour systolic and diastolic BP found not to be. From ROC curves for left ventricular hypertrophy, AUC of home systolic BP monitor (0.758, p&lt;0.05) was larger than that of 24h (0.538, p&gt;0.05) and clinic BP (0.497, p&lt;0.05). As regards DBP, the ROC curves suggest no discrimination for the different ways of BP measurement. Conclusions: Home systolic BP can be a better predictor of left ventricular hypertrophy in untreated population, when compared to 24h and office systolic BP. This result shows the importance of home monitoring for the prediction of left ventricular hypertrophy, even in the untreated population.

Application of Fractional Derivatives in Characterization of ECG graphs

In this paper, we have discussed the prediction of Left Ventricular Hypertrophy (LVH) and Right Ventricular Hypertrophy (RVH) of the heart from an Electrocardiogram (ECG) Graph using fractional order calculus. An ECG is a rough or unreachable curve that is continuous everywhere but non-differentiable at some points or all points where classical calculus fails. The purpose of this paper is to find left and right fractional derivatives at those non-differentiable points and then predict LVH and RVH by calculating the phase transition values (absolute difference of left and right fractional derivatives). Fractal dimension and Hurst exponents of V1, V2, V5, and V6 leads of the ECGs have been calculated for both problematic and normal ECGs. All such measures will help doctors to diagnose LVH and RVH from ECG in a more accurate manner as compared to the techniques which are under the classical order method.

Model for Prediction of Left Ventricular Myocardial Hypertrophy in Patients with Obstructive Sleep Apnea

Obstructive sleep apnea (OSA) is diagnosed in 25% of adults and associated with high fatal risks of cardiovascular complications. Left ventricular hypertrophy (LVH) is recognized as one of the markers of such risks. In this study, we attempted to create a mathematical model for predicting LVH among OAS patients with various levels of disease severity.Materials and methods. In a prospective cohort study, we included 368 patients (358 male; age 46.0 [42.0; 49.0] yr.) with diagnosed OSA, arterial hypertension, grade I-II obesity (WHO classification 1997). The severity of sleep apnea was verified during nighttime computed somnography (CSG) on WatchPAT-200 hardware (ItamarMedical, Israel) with original software zzzPATTMSW ver. 5.1.77.7 (ItamarMedical, Israel) by registering the main respiratory polygraphic characteristics from 11.00 PM to 7:30 AM. Verification of LVH was performed in one- and two-dimensional modes in standard echocardiographic positions using Xario-200 ultrasound scanner (Toshiba, Japan) with 3.5 MHz transducer. Hemodynamic parameters of left ventricular (LV) systolic function (EF %, ESV, EDV) were determined by quantitative assessment of two-dimensional echocardiograms using the modified Simpson method. Evaluation of the systolic function of the right ventricle (RV) was performed in the «M»-mode by measuring the systolic excursion of the fibrous ring of the tricuspid valve (TAPSE).Results. ESS and TSat90% (AUC = 0.975; SD = 0.00741; CI 95% [0.953; 0.988]) should be considered the best predictors for predicting LVH in various degrees of OSA severity, allowing us to offer a predictive model with a sensitivity of 93.7% and specificity of 93.8%, after conducting a questionnaire screening and computer somnographic study.Conclusions. Our proposed model of clinical prediction of LVH among patients with various degrees of OAS is based on a carefully planned analysis of questionnaire and instrumental data, and is well applicable in real diagnostic procedures by a wide range of therapeutic practitioners.

Role of resistin, IL-6 and NH2-terminal portion proBNP in the pathogenesis of cardiac disease in type 2 diabetes mellitus.

IntroductionEpidemiological and genetic studies have recorded the association between proinflammatory cytokines and the development of insulin resistance, diabetes, and cardiovascular disease. The role of interleukin 6 (IL-6), NH2-terminal portion pro-brain natriuretic peptide (NT-proBNP) and resistin in the pathogenesis of heart disease in type 2 diabetes mellitus (T2DM) is still a matter of controversy. The current study aimed to evaluate the role of these biomarkers in the development of left ventricular systolic dysfunction and the ability to use them as non-invasive test in the prediction of left ventricular hypertrophy and systolic dysfunction in T2DM.Research design and methods150 participants were included in this case–control study. Patients were divided into two subgroups according to echocardiographic findings: group 1a included 46 patients with type 2 diabetes mellitus and echocardiographic evidence of abnormal systolic function; group 1b included 54 patients with type 2 diabetes mellitus and with normal echocardiogenic study; and group 2 included 50 apparently healthy controls. Routine laboratory investigations such as complete blood count, liver and renal function tests, and lipid profile, serum IL-6, NT-proBNP, and resistin were measured in all participants. Conventional echocardiography was done with special concern on the assessment of left ventricular systolic function (ejection fraction).ResultsThere was a significant increase in the level of resistin, NT-proBNP and IL-6 in group 1a patients compared with group 1b and in healthy controls. Echocardiographic parameters showed a significant increase in left ventricular mass index, left ventricle posterior wall thickness, interventricular septum thickness, and left ventricle mass in group 1a compared with group 1b and the control group. The increased left ventricular mass index was associated with higher levels of IL-6, NT-proBNP and resistin.ConclusionsProinflammatory cytokines had a clear relation with left ventricular systolic dysfunction and hypertrophy and can be used as early non-invasive markers for detection of left ventricular remodeling and systolic dysfunction in patients with T2DM.

Improvement of electrocardiographic diagnostic accuracy of left ventricular hypertrophy using a Machine Learning approach.

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.

Ambulatory Blood Pressure Phenotypes in Children and Adolescents

Ambulatory Blood Pressure Phenotypes in Children and Adolescents

P3819Machine learning for predicting early left ventricular abnormalities in the general population

Abstract Background Current heart failure guidelines emphasize the importance of timely detection of subclinical left ventricular (LV) remodelling and dysfunction for more precise risk stratification of asymptomatic subjects. Both LV diastolic dysfunction (LVDD) and LV hypertrophy (LVH) as assessed by echocardiography are known independent prognostic markers of future cardiovascular events in the community. However, selective screening strategies of individuals at risk who would benefit most from in-depth cardiac phenotyping are lacking. Purpose We assess the utility of several Machine Learning (ML) classifiers built on clinical and biochemical features for detecting subclinical LV abnormalities. Methods We included 1407 participants (mean age, 51 years, 51% women) randomly recruited from the general population. We used echocardiographic parameters reflecting LV diastolic function and structure to define LV abnormalities (LVDD, n=239; LVH, n=135). After that four supervised ML algorithms (Random Forest (RF), Gradient Boosting (GD), Stochastic Gradient Descent (SGD) and Support Vector Machines (SV)) were built based on routine clinical, hemodynamic and laboratory data (features; n=61) to categorize LVDD and LVH (two prediction tasks). We applied a 10-fold stratified cross-validation set-up. Results ML classifiers exhibited a high area under the ROC (AUC) for predicting LVDD with values between 88.5% and 93.1% (Figure, left panel). Age, BMI, different components of blood pressure, antihypertensive treatment, routine biomarkers such as serum electrolytes, creatinine, blood sugar, leptin, uric acid, lipid profile, as well as blood cell counts were the top selected features for predicting LVDD. Prediction AUC of ML algorithms for detection of LVH was somewhat lower than for LVDD and ranged from 72.5% to 78.7% (Figure, right panel). The top selected features for LVH classifier were similar to those of LVDD, but also included social class, serum gamma-glutamyl transferase, fasting insulin, plasma renin activity and cortisol. ROC curves (sensitivity-1-specificity) Conclusions ML algorithms combining routinely measured clinical and laboratory data have shown high accuracy of LVDD and LVH prediction. These ML classifiers might be useful to preselect individuals at risk for further in depth echocardiographic examination, monitoring and implementation of preventive strategies in order to delay transition to disease symptoms.

The Potential Role of Circulating Endothelial Cells and Endothelial Progenitor Cells in the Prediction of Left Ventricular Hypertrophy in Hypertensive Patients.

BackgroundThe main aim of present study is to evaluate the potential role of circulating endothelial cells (CECs) and endothelial progenitor cells (CEPCs) – representing specific markers of endothelial damage, in the prediction of left ventricular hypertrophy (LVH) in hypertensive patients categorized into two groups; mild (MH) and resistant hypertension (RH).Materials and MethodsThirty patients with MH and 28 subjects with RH were involved in the study. In both groups, patients were divided into an LVH and non-LVH group. The control group included 33 age and sex-matched normotensive volunteers. Physical examination, laboratory tests and echocardiography were conducted.ResultsIn both the MH and RH group, patients with as well as without LVH demonstrated a higher number of CECs and a lower ratio of CEPCs/CECs as compared to the healthy control. Multiple linear regression analysis showed a positive association of CEPCs with left ventricular mass (LVM) and left ventricular mass index (LVMI), independently of other confounders.ConclusionOur results suggest that endothelial injury observed as an elevated CECs number and its impaired regeneration, reflected by a lowered CEPCs/CECs ratio, precede LVH occurrence and may play a significant role in LVH development regardless of the clinical severity of hypertension. Moreover, independent correlation of CEPCs with echocardiographic (ECG) incidences of LVH suggests their potential use as a screening biomarker to stratify the risk of LVH development.

Left ventricular hypertrophy is associated with increased sirtuin level in newly diagnosed hypertensive patients

ABSTRACTBackground: Arterial hypertension is one of the leading causes of mortality and morbidity in general population. Sirtuin 1 (SIRT1) has diverse anti-inflammation, anti-oxidant, and anti-apopytosis effects on endothelium and is associated with endothelial aging and dysfunction. The objective of this study was to evaluate the relation of serum SIRT1 level with left ventricular hypertrophy (LVH) in newly diagnosed hypertensive patients.Methods: One hundered and twenty-five consecutive, newly diagnosed hypertensive patients were divided into two groups with regard to presence of LVH and compared to 40 healthy control subjects. LVH was determined by transthoracic echocardiography using the cube formula. Serum SIRT1 level was analyzed with enzyme-linked immunosorbent assay.Results: Serum SIRT1 level was significantly higher in patients with LVH compared to those without LVH (14.3 ± 3.9 ng/ml vs. 7.9 ± 3.6 ng/ml, ​P < 0.001) and healthy control subjects (14.3 ± 3.9 ng/ml vs 6.6 ± 2.0 ng/ml, P < 0.001). Multivariate logistic regression analysis revealed higher serum SIRT1 level independently predicted LVH in hypertensive patients (OR 1.50; 95% CI, 1.30–1.73; P < 0.001). Receiver-operating characteristic curve analysis demonstrated a cutoff value of 9.4 had a sensitivity of 90% and specificity of 74% for the prediction of LVH (AUC 0.885; 95% CI, 0.815–0.935; ​P < 0.0001).Conclusion: SIRT1 was a powerful biomarker for predicting LVH in hypertensive patients.

Abstract 12677: Serum FGF23 Level is Associated With Cardiac Abnormality Among Patients Without Chronic Kidney Disease Stages

Background: Several experimental studies have demonstrated that fibroblast growth factor 23 (FGF23) may induce myocardial hypertrophy. On the other hand, few studies have clearly demonstrated the relationship between FGF23 level and left ventricular hypertrophy among subjects without chronic kidney disease (CKD; i.e., CKD stage G1 or G2). We investigate the association between FGF23 and cardiac parameters among 903 patients with various degrees of renal function, including 234 patients with CKD stage G1/G2. Methods and Results: Serum levels of full-length FGF23 were determined by enzyme immunoassay. After adjustment for sex, age, and estimated glomerular filtration rate (eGFR), the highest FGF23 tertile was significantly associated with left ventricular hypertrophy among patients with CKD stage G1/G2 as compared with the lowest FGF23 tertile as well as among those with CKD stage G3a/G3b/G4. This association retained significance after further adjustment for serum levels of corrected calcium, inorganic phosphate, and C-reactive protein. FGF23 was also associated with left ventricular ejection fraction (LVEF) &lt;50% among patients with CKD stage G1/G after multivariate analysis. By the ROC curve analysis among these no-CKD patients, compared with model 1 (combination of age, sex, and eGFR), area under the curve of model 2 (model 1+FGF23) was significantly greater for the prediction of left ventricular hypertrophy. Conclusions: An association between FGF23 and cardiac hypertrophy and systolic dysfunction was observed among patients without CKD as well as those with CKD, suggesting FGF23 per se may have direct effect on the cardiac geometry and performance.

Eligibility and Disqualification Recommendations for Competitive Athletes With Cardiovascular Abnormalities: Task Force 6: Hypertension: A Scientific Statement from the American Heart Association and the American College of Cardiology.

An elevation of blood pressure (BP) in the systemic circulation (hypertension) is the most common cardiovascular condition in the general population and considered to be the most ubiquitous cardiovascular risk factor in competitive athletes. Competitive athletes include those athletes involved in organized sports that typically occur in schools, communities, and professional leagues, including but not limited to intramural and league sports in which medical supervision is typically required. Although most competitive athletes are between the ages of 20 and 40 years, many younger people now participate in competitive athletics. The 2013 update from the American Heart Association using the National Health and Nutrition Examination (NHANES) data from 2007 to 2010 estimates that 9.1% of men aged 20 to 34 years and 6.7% of women of that age are hypertensive, based on having an elevated BP measurement or answering “yes” to the question, “Are you taking antihypertensive medication or were you told that you had hypertension?”1 The prevalence in children and adolescents is estimated to be ≈3.5%, with higher percentages in older and obese children.2 The diagnosis of hypertension is based on the subject having an elevated BP at or above certain levels measured by routine sphygmomanometry under appropriate conditions on at least 2 separate occasions separated by at least 1 week.3 However, BP measurements in the competitive athlete are typically obtained by different healthcare providers, which makes it particularly necessary that the testing conditions be standardized before the diagnosis of hypertension is made. People >18 years of age with a BP >140 mm Hg systolic and/or >90 mm Hg diastolic are considered to have hypertension.3 In children and adolescents, hypertension is defined as average systolic or diastolic BP levels greater than the 95th percentile for sex, age, and height; however, earlier physical maturation of the competitive athlete leaves …

Left ventricular hypertrophy in controlled hypertension: Is blood pressure variability blamed?

Abstract Background Blood pressure (BP) has been shown to exhibit important variations not only in the short term but also over more prolonged periods of time. Aim To evaluate the impact of different ambulatory BP variability indices on left ventricular hypertrophy (LVH) in controlled hypertensive patients (Pts). Patients and methods Ninety controlled hypertensive Pts (office and ambulatory BP control criteria) with mean age 55.9 ± 8.5 years were enrolled. Pts were classified into two groups: Non-LVH group including 75 Pts with normal LV mass index and LVH group including 15 patients with LV mass index >134 g/m 2 in men and >110 g/m 2 in women. Mean BP and BP load values were obtained for the full 24 h and day-time and night-time periods. Similarly Standard Deviation (SD) and Average Reading Variability (ARV) were calculated in all pts. Results Regarding office BP, Dipping status and average ambulatory BP, there was no statistically significant difference between both groups. Meanwhile, SD of BP readings and ARV showed a significant difference. After step-wise regression, ARV of systolic BP 24 h was the most powerful variability index that was associated with LVH ( R 2 = 0.944). The ROC curve analysis showed that the discriminative power was best at more than 14.23 mmHg with sensitivity and specificity 100% and 96% respectively for prediction of LVH. Conclusion The adverse cardiovascular consequences of hypertension not only depend on mean BP values but may also depend on BPV, which independently adds to CV risk over elevated mean BP levels.

Assessment of increased left ventricular wall stress with the volume-based wall stress index – prediction of left ventricular hypertrophy and late gadolinium enhancement in dilative heart failure

Assessment of increased left ventricular wall stress with the volume-based wall stress index – prediction of left ventricular hypertrophy and late gadolinium enhancement in dilative heart failure

Relation of central and brachial blood pressure to left ventricular hypertrophy. The Czech Post-MONICA Study

Central blood pressure (BP) has been shown to be a better predictor of target organ damage and cardiovascular events than brachial BP. Whether central BP is a better predictor of left ventricular hypertrophy (LVH) determined by electrocardiography (ECG) is not known. Radial applanation tonometry and ECG were performed in 728 subjects from the Czech Post-MONICA Study (a randomly selected 1% population sample). LVH was determined using the Sokolow-Lyon index and Cornell product; central pressure was derived from radial pulse. Of 657 subjects included in the analysis, 17 (9.4%) below 45 years and 43 (9%) over 45 years had LVH. In multiple linear regression analysis, the Sokolow-Lyon index in younger individuals was only associated with male sex and low BMI, with no association with BP found. In older individuals, LVH was associated with higher central and brachial BP. In separate binary logistic regression analyses adjusted for covariates, the odds ratio for central systolic pressure was higher than those for brachial systolic and pulse pressure in LVH prediction. Noninvasively determined central pressure in subjects over 45 years is more strongly related to ECG LVH than brachial pressure. This further supports a closer association of central pressure with target organ damage. Voltage criteria of LVH are not independently associated with central or brachial BP in younger individuals.

Maximum Value of Home Blood Pressure

The maximum office systolic blood pressure (SBP) has been shown to be a strong predictor of cardiovascular events, independently of the mean SBP level. However, the clinical implications of maximum home SBP have never been reported. We investigated the association between the maximum home SBP and target organ damage (TOD). We assessed the left ventricular mass index (LVMI) and carotid intima-media thickness (IMT) using ultrasonography and the urinary albumin/creatinine ratio (UACR) as measures of TOD in 356 never-treated hypertensive subjects. Home BP was taken in triplicate in the morning and evening, respectively, for 14 consecutive days with a memory-equipped device. The maximum home SBP was defined as the maximum mean triplicate BP reading in the 14-day period for each individual and was significantly correlated with LVMI (r=0.51, P<0.001), carotid IMT (r=0.40, P<0.001), and UACR (r=0.29, P<0.001). The correlation coefficients with LVMI and carotid IMT were significantly larger for the maximum home SBP than the mean home SBP. In multivariate regression analyses, the maximum home SBP was independently associated with LVMI and carotid IMT, regardless of the mean home BP level. In the prediction of left ventricular hypertrophy and carotid atherosclerosis, the goodness-of-fit of the model was significantly improved when the maximum home SBP was added to the sum of the mean office and home BPs (P=0.002 and P<0.001, respectively). These findings indicate that assessment of the maximum home SBP, in addition to the mean home SBP, might increase the predictive value of hypertensive TOD in the heart and artery.

Prediction of LVH from average of R wave amplitude in leads I and V5 among adult Nigerians with hypertension

Left ventricular hypertrophy (LVH) is an independent risk factor for cardiovascular events. Many methods are used to assess it but the reference standard is echocardiography. However, this facility is available only in a few hospital centres. A set of criteria based on voltage threshold as assessed by electrocardiogram, a more readily available and portable tool had been developed. This study evaluates the ability of one of the ECG criteria to predict left ventricular hypertrophy. Aim: The aim of this study was to determine the sensitivity, specificity, accuracy, positive and negative predictive values of average of R wave amplitude in leads I and V5 in predicting LVH Methodology: This is a cross-sectional descriptive study of adult hypertensive subjects. Participants were assessed for LVH using the average of R wave amplitude in lead I and V5 =18mm. Echocardiogram was used to determine their left ventricular mass index and a value greater than 125g/m2 was used as the cut off point for LVH. The sensitivity, specificity, accuracy, positive and negative predictive values were determined for the ECG criterion. Result: Ninety subjects (45 males, 45 females) participated in the study. The prevalence of LVH by echocardiogram and the ECG criterion were 32.2% and 27.8% respectively. The sensitivity, specificity, accuracy, positive and negative predictive values for the ECG criterion were 41.9%, 79.7%, 66.7%, 52.0% and 72.3% respectively. Conclusion: The average of R wave amplitude in leads I and V5 can reliably predict LVH among hypertensive subjects. Key words: Sensitivity, Specificity, ECG criterion, LVH, hypertension

Value of ambulatory intra-arterial blood pressure monitoring in the long-term prediction of left ventricular hypertrophy and carotid atherosclerosis in essential hypertension

The aim of this study was to compare the abilities of clinic and ambulatory blood pressure (BP) to predict the long term occurrence of left ventricular hypertrophy and carotid atherosclerosis in uncomplicated hypertensive patients. Two hundred and ninety-five patients who had undergone 24-h ambulatory intra-arterial BP monitoring on the basis of an elevated clinic BP, attended follow-up at a mean of 10.2 (±3.5) years later. This consisted of a history, physical examination, risk factor profile and serum cholesterol level. Echocardiography and carotid ultrasonography were also performed to determine left ventricular mass index and maximal intima-media thickness (IMTmax), a measure of carotid atherosclerosis severity. The factors most strongly correlated with both left ventricular mass index and IMTmax were age, 24-h mean pulse pressure and 24-h mean systolic BP. Age, 24-h mean systolic BP and body mass index were independent correlates of left ventricular hypertrophy (R 2 = 17%), whereas age, 24-h mean pulse pressure and pack years were independent predictors of carotid atherosclerosis (R 2 = 34%). Clinic BP did not feature in the final model for the long term prediction of cardiovascular end-organ damage. These findings promote a role for ambulatory BP monitoring in guiding aggressiveness of drug therapy in an attempt to limit potential target organ damage.