Serum Zinc and Selenium Concentrations in Patients with Hypertrophy and Remodelling of the Left Ventricle Secondary to Arterial Hypertension

The aim of the study was to assess the relationship between serum selenium and zinc concentrations (Se-S and Zn-S) and the left ventricle geometry in patients suffering from arterial hypertension. A total of 78 people with arterial hypertension (mean age: 53.72 ± 12.74 years) participated in the study. Se-S and Zn-S were determined in all patients. The type of left ventricular remodelling and hypertrophy was determined by the left ventricular mass index (LVMI) and relative wall thickness (RWT) measured by echocardiography. Se-S and Zn-S in the whole group were 89.84 ± 18.75 µg/L and 0.86 ± 0.13 mg/L. Normal left ventricular geometry was found in 28.2% of patients; left ventricular hypertrophy (LVH) in 71.8%, including concentric remodelling in 28.2%, concentric hypertrophy in 29.5%, and eccentric hypertrophy in 14.1%. LVH was statistically significantly more frequent in patients with Se-S < median compared to patients with Se-S ≥ median (87.2% vs. 56.4%, p < 0.05), as well as in patients with Zn-S < median compared to patients with Zn-S ≥ median (83.8% vs. 60.9%, p < 0.05). In hypertensive patients, older age, higher LDL cholesterol, higher fasting glucose, lower Se-S, and lower Zn-S were independently associated with LVH. In conclusion, in hypertensive patients, left ventricular hypertrophy may be associated with low levels of selenium and zinc in the serum.

Performance of different adiposity measures for predicting left ventricular remodeling in Chinese hypertensive youth

There is no consistent conclusion on which adiposity measure is best to predict cardiovascular risk factors in youth. The present study aims to assess the performance of body mass index (BMI), waist circumference (WC), and waist-to-height ratio (WHtR) in predicting abnormal left ventricular structure in Chinese hypertensive youth. A total of 1180 youth aged 6–17 years with hypertension from the China Child and Adolescent Cardiovascular Health Study were included in this study. Logistic regression model, receiver operator characteristic (ROC) curve analysis and net reclassification improvement (NRI) method were used to assess performance of BMI, WC, and WHtR in predicting left ventricular hypertrophy (LVH) and left ventricular geometry (LVG). A 1-standard deviation increment in any of three indexes in predicting LVH and LVG were similar, e.g., with the odds ratios and 95% confidence intervals of 1.34 (1.16–1.55), 1.25 (1.08–1.45) and 1.40 (1.20–1.62), respectively. In addition, ROC analysis and NRI method confirmed the similar performance of three adiposity indexes in predicting LVH and LVG. In conclusion, BMI, WC and WHtR had similar performance in predicting abnormal left ventricular structure in Chinese hypertensive youth, but all three indexes had limited value in prediction. WHtR is a simple and convenient adiposity index for screening youth at high risk of target organ damage.

Prediction of abnormal left ventricular geometry on the ECG through machine learning with a focus on obesity

Background Cardiac remodeling, an important aspect of cardiovascular disease (CVD) progression, is emerging as a significant therapeutic target. However, the ECG is not a sensitive method of detecting left ventricular hypertrophy (LVH), and as far as we know, it cannot detect changes in left ventricular geometry (LVG) at early stages, especially before LVH is present. Its sensitivity is particularly low for obese patients. Purpose To use a machine learning (ML) classifier to detect abnormal LVG from EKG parameters/markers, even before it becomes LVH, and to propose some indicative markers useful for practitioners. We also looked at the results of our model for obese patients to test the markers in this population. Methods We enrolled 594 consecutive subjects, aged 30 years or older (mean age: 61.6±12 years old) with and without essential hypertension and no indications of CVD. We tried to build a “clean” dataset through which we can target the clinical, anthropometric, and electrocardiogram measurements indicative of abnormal LVG. All patients underwent a full echocardiographic evaluation and were classified into 2 groups; those with normal geometry (NG) vs. those with concentric remodeling (CR) or LVH. Abnormal LVG was identified as increased relative wall thickness (RWT) and/or left ventricular mass index (LVMi). We analyzed the EKG waveforms deduced to single beat averages for each lead using custom software and extracted 70 markers. We then trained a Random Forest machine learning model to classify subjects with abnormal LVG and calculated SHAP values to perform feature importance and interaction. Results The percentage of women was 56.5%, while 71.3% of all patients were hypertensive. Hypertension, age, body mass index divided by the Sokolow-Lyon voltage (BMI/S-L), QRS-T angle, and QTc duration were among the most important parameters (Figure, left panel) identified by the model as being predictive of abnormal LVG (AUC/ROC = 0.84, sensitivity = 0.94, specificity 0.61). Specifically for obese patients, whose prevalence in our population was 60.3%, our model performed well (sensitivity = 0.71, specificity = 0.92. When we tried our model without the the BMI/S-L parameter, the specificity dropped to 0.88. We also found that a cut-off point of 18 for the BMI/S-L marker predicted the patients who were more probable to have developed abnormal LVG (Figure 1). Conclusions This study is the first to demonstrate the promising potential of ML modeling for the efficient and cost-effective diagnostic screening of abnormal LVG through ECG. We found specific clinical and ECG parameters that can predict early pathological changes of LVG in patients without established CVD and detect the population who will benefit from a detailed echocardiographic evaluation. Our model contributes to the development of human-centered and autonomous technologies and can optimize patient-management and treatment. FUNDunding Acknowledgement Type of funding sources: None. Figure 1

Abnormal left ventricular geometry in female collegiate swimmers

Background There is a paucity of data describing left ventricular geometry changes in female athletes. While some studies suggest that female athletes participating in dynamic sports exhibit higher prevalence of eccentric left ventricular hypertrophy (LVH) when compared to men, a recent study suggested more concentric geometry changes in female basketball athletes. We were unable to identify studies describing the left ventricular geometry of female collegiate swimmers. Objectives To describe LV geometry changes in a cohort of female collegiate swimmers. Methods We analyzed a cohort of female collegiate swimmers who had a pre-participation cardiac evaluation by 12-lead ECG and 2-dimensional echocardiography. Left ventricular (LV) geometry was assessed based on relative wall thickness (RWT) (defined as: 2 x posterior wall thickness (PWT) divided by LV end-diastolic diameter (LVEDD)) and LV mass (LVM) (Devereux's formula: LVM = [0.8 x 1.04 [(LVEDD + interventricular septum + posterior wall thickness)3 − (LVEDD)3]] + 0.6g) and was indexed to body surface area (BSA).LVH was defined as LV mass index &gt;95 g and was defined as concentric when associated with a relative wall thickness (RWT) &gt;0.42 and as eccentric when RWT was ≤0.42. Concentric remodeling was defined as normal LVM index and increased RWT. Results A total of 83 female collegiate swimmers were included. Their age was 18.5±0.5 years (mean ± standard deviation, SD), 74 (89.2%) were White, BSA was 1.78±0.11 m2, height 173±6.3 cm, weight 66.2±7.2 K. Their interventricular septum diameter was 0.89±0.14 cm, PWT 0.92±0.15 cm, LVEDD 4.9±0.5 cm and LV end-systolic diameter (LVESD) 3.2±0.4 cm. Left atrium diameter ranged from 2.6 to 4.3 cm (mean 3.4 cm ± 0.4 cm). Aortic root diameter ranged from 1.9 to 3.5 cm (mean 2.7±0.3 cm) (Figure 1). LVH was present in 27 swimmers (32.5%). Eccentric LVH was present in 17 athletes (20.5%), concentric hypertrophy in 10 athletes (12%), and concentric remodeling in 12 (14.5%) (Figure 2). No athletes with LVH or concentric remodeling had borderline or abnormal ECG findings based on international criteria. Only two women with normal LV geometry had abnormal ECG findings: prolonged QT interval and abnormal T wave inversion. There was a linear correlation between BSA with LVEDD, LVESD and LV mass (r=0.40, 0.35, and 0.48 with P&lt;0.001,0.002 and &lt;0.001, respectively). However, there was no statistically significant difference between LV geometry groups based on BSA or blood pressure. Conclusion Our data document a high incidence of eccentric hypertrophy among female collegiate swimmers. Concentric remodeling and hypertrophy were also relatively high. Differentiating physiologic from pathologic cardiac remodeling in these athletes is critical to prevent potential complications such as sudden cardiac death, arrhythmias, and other adverse outcomes. FUNDunding Acknowledgement Type of funding sources: Foundation. Main funding source(s): This work was supported in part by the American Medical Society for Sports Medicine (AMSSM) Foundation Research Grant 2016 awarded to KE, and the University of Florida REDCap uses the NIH National Center for Advancing Translational Sciences (NCATS) grant UL1 TR001427. Figure 1 Figure 2. LV geometry in female swimmers

Systematic Comparison of Left Ventricular Geometry Between 3D-Echocardiography and Cardiac Magnetic Resonance Imaging

Aims: Left ventricular (LV) volumes estimated using three-dimensional echocardiography (3D-echo) have been reported to be smaller than those measured using cardiac magnetic resonance (CMR) imaging, but the underlying causes are not well-understood. We investigated differences in regional LV anatomy derived from these modalities and related subsequent findings to image characteristics.Methods and Results: Seventy participants (18 patients and 52 healthy participants) were imaged with 3D-echo and CMR (&lt;1 h apart). Three-dimensional left ventricular models were constructed at end-diastole (ED) and end-systole (ES) from both modalities using previously validated software, enabling the fusion of CMR with 3D-echo by rigid registration. Regional differences were evaluated as mean surface distances for each of the 17 American Heart Association segments, and by comparing contours superimposed on images from each modality. In comparison to CMR-derived models, 3D-echo models underestimated LV end-diastolic volume (EDV) by −16 ± 22, −1 ± 25, and −18 ± 24 ml across three independent analysis methods. Average surface distance errors were largest in the basal-anterolateral segment (11–15 mm) and smallest in the mid-inferoseptal segment (6 mm). Larger errors were associated with signal dropout in anterior regions and the appearance of trabeculae at the lateral wall.Conclusions: Fusion of CMR and 3D-echo provides insight into the causes of volume underestimation by 3D-echo. Systematic signal dropout and differences in appearances of trabeculae lead to discrepancies in the delineation of LV geometry at anterior and lateral regions. A better understanding of error sources across modalities may improve correlation of clinical indices between 3D-echo and CMR.

Abstract P190: Antihypertensive Treatment Improves Left Ventricular Geometry After 10 Years Even In Elderly Hypertensive Patients

Introduction: Both ageing and high blood pressure (BP) is associated with a risk of left ventricular hypertrophy; therefore, it is unclear whether antihypertensive treatment for 10 years period reduce cardiac hypertrophy and concentricity beyond the impact of ageing. We assessed the hypothesis that even in elderly patients, BP reduction is effective for left ventricular remodeling. Methods: Among 558 hypertensive patients without concurrent heart disease referred to a cardiology clinic who underwent echocardiography and ambulatory blood pressure monitoring, 151 patients’ data of echocardiography was available after 10 years of follow up period. We evaluated the relation among BP at baseline, antihypertensive medications, and change in echocardiographic parameters of left ventricular geometry. Results: Mean age was 70.8±8.2 years at baseline. 24-hour BP was 127.4±16.4/71.4±9.6mmHg, awake BP was 129.9±17.1/72.4±10.2mmHg, and asleep BP was 122.5±16.9/67.1±9.1 mmHg. After 10 years (mean age 81.0±9.0 years), number of antihypertensive increased from 1.3±1.2 to 2.0±1.1. Left ventricular mass index (LVMI) insignificantly decreased from 115.7 to 98.7mg/m 2 (p=0.167)and relative wall thickness (RWT) significantly decreased from 0.51 to 0.47(p<0.001). There were 12% of patients with normal left ventricular geometry (N), 52% with concentric remodeling (CR), 9% with eccentric hypertrophy (EH), and 27% with concentric hypertrophy (CH) at baseline. Among patients with N or CR at baseline, those who developed to CH or EH had higher night time systolic BP (126.5±17.0 vs 118.9 ±15.4, p=0.037) than those who did not. Neither number nor type of antihypertensive was related to this geometry change. In logistic regression analysis, night time systolic BP was significantly related to the progression of hypertrophy adjusting for age, sex, BMI, LVMI, RWT, and clinic systolic BP at baseline (p=0.04). Conclusions: Even in elderly hypertensive patients, antihypertensive treatment for 10 years improved LV geometry in spite of ageing. Nighttime BP at baseline predicted worsening of LV geometry after 10 years beyond clinic BP.

Disturbed Glucose Metabolism and Left Ventricular Geometry in the General Population

Background: This study sought to investigate the prevalence and clinical outcome of left ventricular (LV) geometry in prediabetes and type 2 diabetes mellitus (T2DM) and the impact of glucose metabolism on the incidence of left ventricular hypertrophy (LVH). Methods: 15,010 subjects (35–74 years) of the population-based Gutenberg Health Study were categorized into euglycemia, prediabetes, and T2DM according to clinical and metabolic (HbA1c) information. Clinical outcome was assessed via structured follow-up. Results: The study comprised 12,121 individuals with euglycemia (81.6%), 1415 with prediabetes (9.5%), and 1316 with T2DM (8.9%). Prevalence of LVH increased from euglycemia (10.2%) over prediabetes (17.8%) to T2DM (23.8%). Prediabetes and T2DM were associated with increased LV mass index (prediabetes: β1.3 (95% CI 0.78–1.81), p < 0.0001; T2DM: β2.37 (95% CI 1.81; 2.92), p < 0.0001) independent of age, sex, and cardiovascular risk factors (CVRF). The frequency of LVH was related to the presence of T2DM (prevalence ratio (PR)T2DM 1.2 (95% CI 1.06–1.35), p = 0.0038). T2DM was related to mortality independent of age, sex, and CVRF regardless of LVH (hazard ratio (HR)T2DM-LVH 2.67 (95% CI 1.94–3.66), p < 0.0001; HRT2DM-noLVH 1.59 (95% CI 1.29–1.96), p < 0.0001), prediabetes was only associated with outcome in individuals with LVH independent of age and sex (HRprediabetes-LVH 1.51 (95% CI 1.01–2.25), p = 0.045). Neither T2DM nor prediabetes were predictors of incident LVH after adjustment for clinical covariates. Conclusions: Prediabetes and T2DM promote alterations of cardiac geometry. T2DM and particularly the coprevalence of T2DM with LVH substantially reduce life expectancy. These findings highlight the need for new therapeutic and screening approaches to prevent and detect cardiometabolic diseases at an early stage.

Echocardiographic Evaluation of LV Function in Patients with Tachyarrhythmia and Reduced Left Ventricular Function in Response to Rhythm Restoration

Aims: Tachyarrhythmia due to atrial fibrillation (AF) is often associated with reduced left ventricular (LV) function and has been proposed to cause arrhythmia-induced cardiomyopathy (AIC). However, the precise diagnostics of AIC and reversibility after rhythm restoration are poorly understood. Our aim was to investigate systolic LV function in tachycardic AF and to evaluate the direct effect of rhythm restoration. Methods: We prospectively studied 24 patients (71% male, age 65 ± 9 years) with tachycardic AF and newly diagnosed reduced left ventricular ejection fraction (LVEF). Just before and immediately after electrical cardioversion (ECV), transthoracic echocardiography was performed. Geometric as well as functional data were assessed. Results: Patients presented with a heart rate (HR) of 117.4 ± 21.6/min and a 2D-/3D-LVEF of 32 ± 9/31 ± 8%. ECV to sinus rhythm normalized HR to 77 ± 11/min with an increase of 2D-/3D-LVEF to 37 ± 9/37 ± 10% (p < 0.01 vs. baseline, each). Left ventricular geometry changed with an increase of end-diastolic volume (LVEDV) while end-systolic volume (LVESV) remained unchanged. Parameters concerning myocardial deformation (global longitudinal strain (GLS), strain rate (SR)) decreased whereas the RR interval-corrected GLS (GLSc) remained unchanged. In a simple linear regression model, GLS correlated with 2D- and 3D-LVEF not only before (pre) ECV, but also after (post) ECV. We demonstrate that the increase of LVEF and GLS (ratios pre/post) correlates with the change of HR (ΔHR; R2 = 0.20, 0.33 and 0.32, p < 0.05 each), whereas ratios of GLSc and SR do not significantly correlate with HR (R2 = 0.03 and 0.01, p = n.s. each). Conclusion: In patients with tachyarrhythmia and reduced ejection fraction, ECV leads to immediate improvement in EF and GLS while HR-corrected LV contractility remains unchanged. This suggests that the immediate effects of rhythm restoration are mostly related to changes in left ventricular volume, but not to an acute improvement of heart-rate independent contractility.