Differential associations between abnormal cardiac left ventricular geometry types and cerebral white matter disease.

OBJECTIVES: Reduced cardiac outflow due to left ventricular hypertrophy has been suggested as a potential risk factor for development of cerebral white matter disease. Our study aimed to examine the correlation between left ventricular geometry and white matter disease volume to establish a clearer understanding of their relationship, as it is currently not well-established. METHODS: Consecutive patients from 2016 to 2021 who were ≥18 years and underwent echocardiography, cardiac MRI, and brain MRI within one year were included. Four categories of left ventricular geometry were defined based on left ventricular mass index and relative wall thickness on echocardiography. White matter disease volume was quantified using an automated algorithm applied to axial T2 FLAIR images and compared across left ventricular geometry categories. RESULTS: We identified 112 patients of which 34.8 % had normal left ventricular geometry, 20.5 % had eccentric hypertrophy, 21.4 % had concentric remodeling, and 23.2 % had concentric hypertrophy. White matter disease volume was highest in patients with concentric hypertrophy and concentric remodeling, compared to eccentric hypertrophy and normal morphology with a trend-P value of 0.028. Patients with higher relative wall thickness had higher white matter disease volume (10.73 ± 10.29 cc vs 5.89 ± 6.46 cc, P = 0.003), compared to those with normal relative wall thickness. CONCLUSION: Our results showed that abnormal left ventricular geometry is associated with higher white matter disease burden, particularly among those with abnormal relative wall thickness. Future studies are needed to explore causative relationships and potential therapeutic options that may mediate the adverse left ventricular remodeling and its effect in slowing white matter disease progression.

Cardiac magnetic resonance patterns of left ventricular remodeling in patients with severe aortic stenosis referred to surgical aortic valve replacement.

Left ventricular (LV) hypertrophy is a common finding in patients with severe aortic stenosis (AS). Cardiac magnetic resonance (CMR) is the gold-standard technique to evaluate LV remodeling. Our aim was to assess the prevalence and describe the patterns of LV adaptation in AS patients before and after surgical aortic valve replacement (AVR). Prospective study of 130 consecutive patients (71y [IQR 68-77y], 48% men) with severe AS, referred for surgical AVR. Patterns of LV remodeling were assessed by CMR. Besides normal LV ventricular structure, four other patterns were considered: concentric remodeling, concentric hypertrophy, eccentric hypertrophy, and adverse remodeling. At baseline CMR study: mean LV indexed mass: 81.8 ± 26.7 g/m2; mean end-diastolic LV indexed volume: 85.7 ± 23.1 mL/m2 and median geometric remodeling ratio: 0.96 g/mL [IQR 0.82-1.08 g/mL]. LV hypertrophy occurred in 49% of subjects (concentric 44%; eccentric 5%). Both normal LV structure and concentric remodeling had a prevalence of 25% among the cohort; one patient had an adverse remodeling pattern. Asymmetric LV wall thickening was present in 55% of the patients, with predominant septal involvement. AVR was performed in 119 patients. At 3-6 months after AVR, LV remodeling changed to: normal ventricular geometry in 60%, concentric remodeling in 27%, concentric hypertrophy in 10%, eccentric hypertrophy in 3% and adverse remodeling (one patient). Indexes of AS severity, LV systolic and diastolic function and NT-proBNP were significantly different among the distinct patterns of remodeling. Several distinct patterns of LV remodelling beyond concentric hypertrophy occur in patients with classical severe AS. Asymmetric hypertrophy is a common finding and LV response after AVR is diverse.

One-shot screening: Utilization of a two-dimensional convolutional neural network for automatic detection of left ventricular hypertrophy using electrocardiograms.

BACKGROUND AND OBJECTIVE: Left ventricular hypertrophy (LVH) can impair ejection function and elevate the risk of heart failure. Therefore, early detection through screening is crucial. This study aimed to propose a novel method to enhance LVH detection using 12-lead electrocardiogram (ECG) waveforms with a two-dimensional (2D) convolutional neural network (CNN). METHODS: Utilizing 42,127 pairs of ECG-transthoracic echocardiogram data, we pre-processed raw data into single-shot images derived from each ECG lead and conducted lead selection to optimize LVH diagnosis. Our proposed one-shot screening method, implemented during pre-processing, enables the superimposition of waveform source data of any length onto a single-frame image, thereby addressing the limitations of the one-dimensional (1D) approach. We developed a deep learning model with a 2D-CNN structure and machine learning models for LVH detection. To assess our method, we also compared our results with conventional ECG criteria and those of a prior study that used a 1D-CNN approach, utilizing the same dataset from the University of Tokyo Hospital for LVH diagnosis. RESULTS: For LVH detection, the average area under the receiver operating characteristic curve (AUROC) was 0.916 for the 2D-CNN model, which was significantly higher than that obtained using logistic regression and random forest methods, as well as the two conventional ECG criteria (AUROC of 0.766, 0.790, 0.599, and 0.622, respectively). Incorporating additional metadata, such as ECG measurement data, further improved the average AUROC to 0.921. The model's performance remained stable across two different annotation criteria and demonstrated significant superiority over the performance of the 1D-CNN model used in a previous study (AUROC of 0.807). CONCLUSIONS: This study introduces a robust and computationally efficient method that outperforms 1D-CNN models utilized in previous studies for LVH detection. Our method can transform waveforms of any length into fixed-size images and leverage the selected lead of the ECG, ensuring adaptability in environments with limited computational resources. The proposed method holds promise for integration into clinical practice as a tool for early diagnosis, potentially enhancing patient outcomes by facilitating earlier treatment and management.

Association Between Elevated Body Mass Index and Cardiac Organ Damage in Children and Adolescents: Evidence and Mechanisms.

INTRODUCTION: Although a number of pathophysiological aspects of childhood obesity have been reported, few information are available on obesity-related cardiac organ damage. AIM: The present study was aimed at assessing the impact of anthropometric, blood pressure (BP) and metabolic variable on cardiac structure and function in youth. METHODS: In 78 subjects aged 5-16 years attending the outpatient clinic of cardiovascular risk (Valencia, Spain) anthropometric and metabolic variables, clinic and ambulatory BP and echocardiographic parameters were assessed. Subjects were also classified according to the presence of insulin resistance. RESULTS: Subjects mean age (± SD) amounted to 12.03 ± 2.4 years and males to 53.8%. Ten subjects were normoweight, 11 overweight, 39 obese, and 18 severely obese. No significant difference in office and ambulatory BP was detected among different bodyweight groups. A significant direct correlation was observed between left ventricular mass index (LVMI) and obesity markers [body mass index (BMI): r = 0.38, waist circumference (WC): r = 0.46, P < 0.04 for both]. Left ventricular hypertrophy, relative wall thickness and left atrial diameter were significantly related to BMI and WC. In contrast, office and ambulatory BP were unrelated to other variables, and differences in LVMI among different BP phenotypes were not significant. When partitioning the population by insulin resistance, LVMI, adjusted for confounders, was significantly greater in the insulin-resistant group. CONCLUSIONS: In children and adolescents characterized by different body weight patterns, weight factors "per se" and the related insulin resistance state appear to represent the main determinants of LVMI and left ventricular hypertrophy, independently on BP values and BP phenotypes.

Gender Differences in Cardiac Organ Damage in Arterial Hypertension: Assessing the Role of Drug Nonadherence.

INTRODUCTION: Cardiac organ damage like left ventricular (LV) hypertrophy and left atrial (LA) enlargement is more prevalent in women than men with hypertension, but the mechanisms underlying this gender difference remain unclear. METHODS: We tested the association of drug nonadherence with the presence of LV hypertrophy and LA enlargement by echocardiography in 186 women and 337 men with uncontrolled hypertension defined as daytime systolic blood pressure (BP) ≥ 135mmHg despite the prescription of at least two antihypertensive drugs. Drug adherence was assessed by measurements of serum drug concentrations interpreted by an experienced pharmacologist. Aldosterone-renin-ratio (ARR) was measured on actual medication. RESULTS: Women had a higher prevalence of LV hypertrophy (46% vs. 33%) and LA enlargement (79% vs 65%, both p < 0.05) than men, while drug nonadherence (8% vs. 9%, p > 0.514) did not differ. Women were older and had lower serum renin concentration and higher ARR than men, while 24-h systolic BP (141 ± 9 mmHg vs. 142 ± 9 mmHg), and the prevalences of obesity (43% vs. 50%) did not differ (all p > 0.10). In multivariable analyses, female gender was independently associated with a two-fold increased risk of LV hypertrophy (OR 2.01[95% CI 1.30-3.10], p = 0.002) and LA enlargement (OR 1.90 [95% CI 1.17-3.10], p = 0.010), while no association with drug nonadherence was found. Higher ARR was independently associated with LV hypertrophy in men only (OR 2.12 [95% CI 1.12-4.00] p = 0.02). CONCLUSIONS: Among patients with uncontrolled hypertension, the higher prevalence of LV hypertrophy and LA enlargement in women was not explained by differences in drug nonadherence. REGISTRATION: URL:  https://www. CLINICALTRIALS: gov ; Unique identifier: NCT03209154.

Cardio-Ankle Vascular Index as a Marker of Left Ventricular Hypertrophy in Treated Hypertensives: Findings From the Pamela Study.

BACKGROUND: Findings regarding the association between Cardio-Ankle Vascular Index (CAVI) and cardiac hypertension-mediated organ damage (HMOD), such as left ventricular hypertrophy (LVH) assessed by echocardiography, in elderly hypertensive patients are scanty. We sought to investigate this issue in the hypertensive fraction of the general population treated with anti-hypertensive drugs enrolled in the Pressioni Monitorate E Loro Associazioni (PAMELA) study. METHODS: The study included 239 out of 562 participants who attended the second and third surveys of the PAMELA study performed after 10 and 25 years from the initial evaluation. Data collection included medical history, anthropometric parameters, office, home, ambulatory blood pressure (BP), blood examinations, echocardiography, and CAVI measurements. RESULTS: In the whole study sample (age 69 ±â€…9 years, 54% males), CAVI was positively correlated with age, office, home, ambulatory systolic BP, LV mass (LVM) index, and negatively associated with body mass index (BMI). In multivariate analysis, CAVI was associated with the LVM index (P < 0.05) independently of major confounders. The participants with LVH exhibited significantly higher CAVI (10.6 ±â€…2.8 vs. 9.2 ±â€…1.8 m/s P < 0.001), larger left atrial diameter, and lower LV ejection fraction values than their counterparts without it. The CAVI value of 9.4 m/s was the best cut-off for prediction of LVH in the whole sample. CONCLUSIONS: Our study provides new evidence of an independent association between CAVI and LVH in treated elderly hypertensive patients and suggests that the use of this metric of arterial stiffness could not only be used to evaluate vascular damage but also to stratify the risk of LVH.

24-h central pressure is a valuable predictor for left ventricular hypertrophy in non-dialysis patients with chronic kidney disease.

The current research on the relationship between 24-h central pressure and 24-h brachial pressure with left ventricular hypertrophy (LVH) is characterised by limited sample size and inconsistent findings. Furthermore, the association has never been explored in chronic kidney disease (CKD). A multicentre, cross-sectional study among non-dialysis patients with CKD was conducted. All participants underwent brachial and central ambulatory blood pressure monitoring using MobilO-Graph PWA, while trained cardiologists performed echocardiography. In this study, 2117 non-dialysis patients with CKD were examined. 24-h central systolic blood pressure with c2 calibration (24-h c2SBP) demonstrated a stronger association with left ventricular mass index and LVH compared with 24-h brachial systolic blood pressure (24-h bSBP) in the univariate and multivariate regression analyses. The multivariate net reclassification index (NRI) analysis revealed that 24-h c2SBP exhibited greater discriminatory power over 24-h bSBP (NRI = 0.310, 95% CI [0.192-0.429], P < 0.001). Applying 130/135 mmHg as the threshold for 24-h bSBP/c2SBP to cross-classify, the patients were divided into concordant normotension (1509 individuals), isolated brachial hypertension (155 individuals), isolated central hypertension (11 individuals), and concordant hypertension (442 individuals). With concordant normotension as the reference, the multivariable-adjusted ORs were 0.954 (95% CI, 0.534-1.640; P = 0.870) for isolated brachial hypertension and 2.585 (95%CI, 1.841-3.633; P < 0.001) for concordant hypertension. Among non-dialysis patients with CKD, 24-h c2SBP exhibits greater efficacy in identifying the presence of LVH compared with 24-h bSBP. The presence of LVH was greater in cases of concordant hypertension compared with cases of isolated brachial hypertension and concordant normotension.

Association between short-term blood pressure variability and target organ damage in non-dialysis patients with chronic kidney disease.

BACKGROUND: It is unclear whether short-term blood pressure variability (BPV) is associated with target organ damage in patients with non-dialysis chronic kidney disease (CKD). METHODS: A cross-sectional, single-center study was conducted among 3442 non-dialysis CKD patients hospitalized in the department of Nephrology of the Fifth Affiliated Hospital of Sun Yat-sen University from November 2017 to July 2022 and collected the demographic, laboratory, clinic blood pressure, ambulatory blood pressure data, and short-term BPV assessed by the weighted standard deviation (wSD) derived from ambulatory blood pressure monitoring (ABPM). Multivariate logistic analyses were used to evaluate the independent effects between short-term BPV and subclinical target organ damage, including left ventricular hypertrophy (LVH), abnormal carotid intima-media thickness (CIMT), low estimated glomerular filtration rate (eGFR), and albuminuria. RESULTS: The average age of the participants was 47.53 ± 14.06 years and 56% of participants were male. The baseline eGFR was 69 mL/min/1.73 m2. Based on the tertile distribution of wSD according to equal numbers, patients were divided into three categories with T1(< 9.66 mmHg), T2(9.66-12.23 mmHg), and T3(> 12.23 mmHg) of SBPV; T1(< 8.17 mmHg), T2(8.17-9.93 mmHg), and T3(> 9.93 mmHg) of DBPV. The participants with the higher wSD group had a higher prevalence of target organ damage than their counterparts (P-trend < 0.05). An increasing trend in short-term variability was present with advancing CKD stages (P-trend < 0.001). Multivariate logistic analyses results showed that the odds ratio (OR) of SBP wSD was (1.07 [1.03,1.11], P < 0.001) for LVH, (1.04 [1.01,1.07, P = 0.029) for abnormal CIMT, (1.05 [1.02,1.08], P = 0.002) for low eGFR, and (1.06 [1.02,1.09], P = 0.002) for albuminuria; The OR of DBP wSD was (1.07 [1.02,1.12], P = 0.005) for LVH, (1.05 [1.01,1.09], P = 0.028) for abnormal CIMT, (1.05 [1.01,1.09], P = 0.022) for low eGFR, and (1.05 [1.01,1.10], P = 0.025) for albuminuria when adjusted for confounding factors and mean BP. CONCLUSIONS: In conclusion, short-term BPV is associated with target organ damage, and irresponsible of average blood pressure levels, in Chinese non-dialysis CKD participants.

Deep learning to detect left ventricular structural abnormalities in chest X-rays.

BACKGROUND AND AIMS: Early identification of cardiac structural abnormalities indicative of heart failure is crucial to improving patient outcomes. Chest X-rays (CXRs) are routinely conducted on a broad population of patients, presenting an opportunity to build scalable screening tools for structural abnormalities indicative of Stage B or worse heart failure with deep learning methods. In this study, a model was developed to identify severe left ventricular hypertrophy (SLVH) and dilated left ventricle (DLV) using CXRs. METHODS: A total of 71 589 unique CXRs from 24 689 different patients completed within 1 year of echocardiograms were identified. Labels for SLVH, DLV, and a composite label indicating the presence of either were extracted from echocardiograms. A deep learning model was developed and evaluated using area under the receiver operating characteristic curve (AUROC). Performance was additionally validated on 8003 CXRs from an external site and compared against visual assessment by 15 board-certified radiologists. RESULTS: The model yielded an AUROC of 0.79 (0.76-0.81) for SLVH, 0.80 (0.77-0.84) for DLV, and 0.80 (0.78-0.83) for the composite label, with similar performance on an external data set. The model outperformed all 15 individual radiologists for predicting the composite label and achieved a sensitivity of 71% vs. 66% against the consensus vote across all radiologists at a fixed specificity of 73%. CONCLUSIONS: Deep learning analysis of CXRs can accurately detect the presence of certain structural abnormalities and may be useful in early identification of patients with LV hypertrophy and dilation. As a resource to promote further innovation, 71 589 CXRs with adjoining echocardiographic labels have been made publicly available.

Discordance interpretation of left ventricular size between echocardiography and cardiac magnetic resonance in pediatric patients with aortic/mitral regurgitation.

PURPOSE: This study investigated discordance between echocardiography (echo) and cardiac magnetic resonance (CMR) measurements of the left ventricle (LV) in pediatric patients with aortic and/or mitral regurgitation (AR/MR). METHODS: Retrospective cohort study of pediatric patients. The cohorts were comprised of patients with AR/MR vs. non-AR/MR. Left ventricular end diastolic volume (LVEDV) by CMR and left ventricular internal diameter diastolic (LVIDd) by echo were obtained from clinical reports then echo images were reviewed to remeasure LVEDV by bullet method. Left ventricular internal diameter systolic (LVIDs) and left ventricular ejection fraction (LVEF) measurements by echo and LVEF by CMR were obtained from clinical reports. Fractional shortening (FS%) was recalculated. Z-scores were calculated using normative data. Correlation between echo and CMR LV measurements was assessed using correlation coefficients. Bland-Altman plots assessed bias between imaging modalities. Receiver operator characteristic (ROC) analysis was performed for detection of LV enlargement and LV dysfunction. RESULTS: AR/MR patients had greater discrepancy in LV size interpretation by Z-score compared to non-AR/MR patients. This discrepancy persisted when the bullet method short axis measurements were incorporated. There was negative bias in echo-based measurements compared to CMR. The diagnostic performance of echo in identifying moderate LV enlargement was worse for AR/MR pediatrics patients. CONCLUSION: The discordant interpretation of LV size by echo compared to CMR is worse in pediatric patients with AR/MR when compared to patients without AR/MR even when short axis measurements are incorporated. This finding suggests non-uniform geometrical changes in the LV as it enlarges due to AR/MR.

Pediatric ECG-Based Deep Learning to Predict Left Ventricular Dysfunction and Remodeling.

BACKGROUND: Artificial intelligence-enhanced ECG analysis shows promise to detect ventricular dysfunction and remodeling in adult populations. However, its application to pediatric populations remains underexplored. METHODS: A convolutional neural network was trained on paired ECG-echocardiograms (≤2 days apart) from patients ≤18 years of age without major congenital heart disease to detect human expert-classified greater than mild left ventricular (LV) dysfunction, hypertrophy, and dilation (individually and as a composite outcome). Model performance was evaluated on single ECG-echocardiogram pairs per patient at Boston Children's Hospital and externally at Mount Sinai Hospital using area under the receiver operating characteristic curve (AUROC) and area under the precision-recall curve (AUPRC). RESULTS: The training cohort comprised 92 377 ECG-echocardiogram pairs (46 261 patients; median age, 8.2 years). Test groups included internal testing (12 631 patients; median age, 8.8 years; 4.6% composite outcomes), emergency department (2830 patients; median age, 7.7 years; 10.0% composite outcomes), and external validation (5088 patients; median age, 4.3 years; 6.1% composite outcomes) cohorts. Model performance was similar on internal test and emergency department cohorts, with model predictions of LV hypertrophy outperforming the pediatric cardiologist expert benchmark. Adding age and sex to the model added no benefit to model performance. When using quantitative outcome cutoffs, model performance was similar between internal testing (composite outcome: AUROC, 0.88, AUPRC, 0.43; LV dysfunction: AUROC, 0.92, AUPRC, 0.23; LV hypertrophy: AUROC, 0.88, AUPRC, 0.28; LV dilation: AUROC, 0.91, AUPRC, 0.47) and external validation (composite outcome: AUROC, 0.86, AUPRC, 0.39; LV dysfunction: AUROC, 0.94, AUPRC, 0.32; LV hypertrophy: AUROC, 0.84, AUPRC, 0.25; LV dilation: AUROC, 0.87, AUPRC, 0.33), with composite outcome negative predictive values of 99.0% and 99.2%, respectively. Saliency mapping highlighted ECG components that influenced model predictions (precordial QRS complexes for all outcomes; T waves for LV dysfunction). High-risk ECG features include lateral T-wave inversion (LV dysfunction), deep S waves in V1 and V2 and tall R waves in V6 (LV hypertrophy), and tall R waves in V4 through V6 (LV dilation). CONCLUSIONS: This externally validated algorithm shows promise to inexpensively screen for LV dysfunction and remodeling in children, which may facilitate improved access to care by democratizing the expertise of pediatric cardiologists.

Construction and validation of a nomogram to predict left ventricular hypertrophy in low-risk patients with hypertension.

Electrocardiography (ECG) is an accessible diagnostic tool for screening patients with hypertensive left ventricular hypertrophy (LVH). However, its diagnostic sensitivity is low, with a high probability of false-negatives. Thus, this study aimed to establish a clinically useful nomogram to supplement the assessment of LVH in patients with hypertension and without ECG-LVH based on Cornell product criteria (low-risk hypertensive population). A cross-sectional dataset was used for model construction and divided into development (n = 2906) and verification (n = 1447) datasets. A multivariable logistic regression risk model and nomogram were developed after screening for risk factors. Of the 4353 low-risk hypertensive patients, 673 (15.4%) had LVH diagnosed by echocardiography (Echo-LVH). Eleven risk factors were identified: hypertension awareness, duration of hypertension, age, sex, high waist-hip ratio, education level, tea consumption, hypochloremia, and other ECG-LVH diagnostic criteria (including Sokolow-Lyon, Sokolow-Lyon products, and Peguero-Lo Presti). For the development and validation datasets, the areas under the curve were 0.724 (sensitivity = 0.606) and 0.700 (sensitivity = 0.663), respectively. After including blood pressure, the areas under the curve were 0.735 (sensitivity = 0.734) and 0.716 (sensitivity = 0.718), respectively. This novel nomogram had a good predictive ability and may be used to assess the Echo-LVH risk in patients with hypertension and without ECG-LVH based on Cornell product criteria.

Left Ventricular Hypertrophy in Male and Female Judo Athletes.

Changes in cardiac geometry develop after intense and prolonged training. Left ventricular enlargement, increased relative wall thickness, and growing mass of the left ventricle occur after strenuous exercise. Combat sports such as judo can lead to left ventricular hypertrophy. Previous studies have found that there are differences in left ventricular chamber size and thickness between the sexes, with female athletes having smaller wall diameters and less hypertrophy than male athletes. The research aims to examine heart muscle adaptations and remodeling of cardiac geometry among elite judo athletes and to evaluate differences between males and females. A cross-sectional study included a group of 19 (males n=10, females n=9) professional judokas between 20 and 30 years. Demographic and anthropometric data were collected. Cardiac geometry was determined by two-dimensional transthoracic echocardiography. In terms of left ventricular mass and the left ventricular mass index significant differences were found between male and female judokas (233.44±68.75 g vs. 164.11±16.59 g, p=0.009), (105.16±24.89 vs. 84.66±15.06, p=0.044), respectively. A greater enlargement of the heart muscle is observed in male athletes compared to the female group. Left ventricle enlargement is likely to occur among elite-level judokas.

Left ventricular hypertrophy as a risk factor for accelerated brain aging: Results from the Study of Health in Pomerania.

Previous studies provided evidence for the importance of cardiac structure abnormalities, in particular greater left ventricular (LV) mass, for brain aging, but longitudinal studies are lacking to date. We included 926 individuals (median age 48 years; 53% women) from the TREND cohort of the Study of Health in Pomerania (SHIP) without reduced ejection fraction or a history of myocardial infarction. LV mass index (LVMI) was determined by echocardiography at baseline. Brain morphometric measurements were derived from magnetic resonance images at baseline and 7-year follow-up. Direct effects of baseline LVMI on brain morphometry at follow-up were estimated using linear regression models with adjustment for baseline brain morphometry. At baseline, median LVMI was 40 g/m2.7 and 241 individuals (26%) met the criterion of LV hypertrophy. After correction for multiple testing, baseline LVMI was directly associated with reduced global cortical thickness and increased cortical brain age at follow-up independent from hypertension and blood pressure. Exposure-outcome relations were nonlinear and significantly stronger in the upper half of the exposure distribution. Specifically, an increase in baseline LVMI from the 50% quantile to the 95% quantile was associated additional 2.7 years (95% confidence interval = [1.5 years, 3.8 years]) of cortical brain age at follow-up. Additional regional analyses yielded bilateral effects on multiple frontal cortical regions. Our findings highlight the role of cardiac structure in brain aging. LVMI constitutes an easily measurable marker that might help to identify persons at risk for cognitive impairment and dementia.

Differences Between Two Distinct Hypertrophic Cardiac Conditions: Fabry Disease versus Hypertrophic Cardiomyopathy. / Diferenças entre Duas Condições Cardíacas Hipertróficas Distintas: Doença de Fabry Versus Cardiomiopatia Hipertrófica.

BACKGROUND: Hypertrophic cardiomyopathy (HCM) and Fabry disease (FD) are genetically inherited diseases with left ventricular hypertrophy (LVH) phenotype characteristics that cause adverse cardiac outcomes. OBJECTIVES: To investigate the demographic, clinical, biochemical, electrocardiographic (ECG), and echocardiographic (ECHO) differences between HCM and FD. METHODS: 60 HCM and 40 FD patients were analyzed retrospectively as a subanalysis of the 'LVH-TR study' after excluding patients with atrial fibrillation, pace rhythm, bundle branch blocks, and second and third-degree atrioventricular (AV) blocks. The significance level was accepted as <0.05. RESULTS: Male gender (p=0.048) and creatinine (p=0.010) are significantly higher in favor of FD; however, ST depression (p=0.028), QT duration (p=0.041), interventricular septum thickness (IVSd) (p=0.003), posterior wall thickness (PWd) (p=0.009), moderate-severe mitral regurgitation (MR) (p=0.013), and LV mass index (LVMI) (p=0.041) are significantly higher in favor of HCM in the univariate analyses. In multivariate analysis, statistical significance only continues in creatinine (p=0.018) and QT duration (0.045). FD was positively correlated with creatinine (rho=0.287, p=0.004) and HCM was positively correlated with PWd (rho=0.306, p=0.002), IVSd (rho=0.395, p<0.001), moderate-severe MR (rho=0.276, p<0.005), LVMI (rho=0.300, p=0.002), relative wall thickness (RWT) (rho=0.271, p=0.006), QT duration (rho=0.213, p=0.034) and ST depression (rho=0.222, p=0.026). CONCLUSION: Specific biochemical, ECG, and ECHO characteristics can aid in the differentiation and early diagnosis of HCM and FD.

FUNDAMENTO: A cardiomiopatia hipertrófica (CMH) e a doença de Fabry (DF) são doenças herdadas geneticamente com características fenotípicas de hipertrofia ventricular esquerda (HVE) que causam resultados cardíacos adversos. OBJETIVOS: Investigar as diferenças demográficas, clínicas, bioquímicas, eletrocardiográficas (ECG) e ecocardiográficas (ECO) entre CMH e DF. MÉTODOS: 60 pacientes com CMH e 40 pacientes com DF foram analisados retrospectivamente como uma subanálise do "estudo LVH-TR" após exclusão de pacientes com fibrilação atrial, ritmo de estimulação, bloqueios de ramo e bloqueios atrioventriculares (AV) de segundo e terceiro graus. O nível de significância foi aceito como <0,05. RESULTADOS: O sexo masculino (p=0,048) e a creatinina (p=0,010) são significativamente maiores a favor da DF; entretanto, infradesnivelamento do segmento ST (p=0,028), duração do QT (p=0,041), espessura do septo interventricular (SIVd) (p=0,003), espessura da parede posterior (PWd) (p=0,009), insuficiência mitral moderada a grave (IM) (p=0,013) e o índice de massa ventricular esquerda (IMVE) (p=0,041) são significativamente maiores a favor da CMH nas análises univariadas. Na análise multivariada, a significância estatística apenas permanece na creatinina (p=0,018) e na duração do intervalo QT (0,045). A DF foi positivamente correlacionada com a creatinina (rho=0,287, p=0,004) e a CMH foi positivamente correlacionada com o PWd (rho=0,306, p=0,002), IVSd (rho=0,395, p<0,001), IM moderada-grave (rho= 0,276, p<0,005), IMVE (rho=0,300, p=0,002), espessura relativa da parede (ERP) (rho=0,271, p=0,006), duração do QT (rho=0,213, p=0,034) e depressão do segmento ST (rho =0,222, p=0,026). CONCLUSÃO: Características bioquímicas, ECG e ECO específicas podem auxiliar na diferenciação e no diagnóstico precoce da CMH e da DF.

Left ventricular hypertrophy phenotype to predict incident atrial fibrillation: The Multi-Ethnic Study of Atherosclerosis.

BACKGROUND AND AIM: Left ventricular hypertrophy (LVH) has been shown to be associated with the occurrence of atrial fibrillation (AF). However, the predictive value of the LVH phenotype for incident AF remains uncertain. This study aimed to investigate the predictive value of LVH phenotype for incident AF. METHODS AND RESULTS: This study utilized the Multi-Ethnic Study of Atherosclerosis (MESA) data. LVH was defined by cardiac magnetic resonance measured LV mass index. Isolated LVH was determined as LVH without elevated cardiac biomarker and malignant LVH was determined as LVH with at least 1 elevated biomarker. Receiver-operating characteristic (ROC) analysis was performed to calculate areas under the curves (AUC) for predicting AF. A total of 4983 community-dwelling participants were included, with a mean age of 61.5 years. 279 (5.6 %) had isolated LVH, and 222 (4.5 %) had malignant LVH. During a median follow-up of 8.5 years, 272 incident AF was observed. Compared to participants without LVH and elevated cardiac biomarkers, those with isolated LVH (HR, 1.82; 95 % CI, 1.03-3.20) and malignant LVH (HR, 4.13; 95 % CI, 2.77-6.16) had a higher risk of incident AF. Malignant LVH carried a 1.5-fold increased risk of AF compared to isolated LVH (HR: 2.48, 95 % CI: 1.30-4.73). Including the LVH phenotype in the CHARGE-AF model improved model discrimination (AUC increase: 0.03, p < 0.001). CONCLUSIONS: The risks of AF incidence varied across LVH phenotypes. Malignant LVH carried the highest risk among LVH phenotypes. LVH phenotype provides incremental predictive value over the variables included in the CHARGE-AF model.