Fabry disease is a rare X-linked inherited lysosomal storage disorder caused by the absence or reduction of alfa-galactosidase A activity in lysosomes, resulting in accumulation of glycosphingolipids in various tissues. The main organ affected is the heart, which frequently manifests as left ventricular hypertrophy and can ultimately lead to cardiac fibrosis, heart failure, valve disease, cardiac conduction abnormalities and sudden cardiac death. Today we know that myocyte damage starts before these signs and symptoms are detectable on routine studies, during the designated pre-clinical phase of Fabry disease. The initiation of specific therapy for Fabry disease during the early stages of the disease has a great impact on the prognosis of these patients avoiding progression to irreversible fibrosis and preventing cardiovascular complications. Cardiac imaging has become an essential tool in the management of Fabry disease as it can help physicians suspect the disorder, diagnose patients in the early stages and improve outcomes. The recent development of novel imaging techniques makes necessary an update on the subject. This review discusses the role of multimodal imaging in the diagnosis, staging, patient selection for treatment and prognosis of Fabry disease and discusses recent advances in imaging techniques that provide new insights into the pathogenesis of the disorder and the possibility of novel treatment targets.

Several studies suggested the utility of artificial intelligence (AI) in screening left ventricular hypertrophy (LVH). We hence conducted systematic review and meta-analysis comparing diagnostic accuracy of AI to Sokolow-Lyon\'s and Cornell\'s criteria. Our aim was to provide a comprehensive overview of the newly developed AI tools for diagnosing LVH. We searched MEDLINE, EMBASE, and Cochrane databases for relevant studies until May 2023. Included were observational studies evaluating AI\'s accuracy in LVH detection. The area under the receiver operating characteristic curves (ROC) and pooled sensitivities and specificities assessed AI\'s performance against standard criteria. A total of 66,479 participants, with and without LVH, were included. Use of AI was associated with improved diagnostic accuracy with summary ROC (SROC) of 0.87. Sokolow-Lyon\'s and Cornell\'s criteria had lower accuracy (0.68 and 0.60). AI had sensitivity and specificity of 69% and 87%. In comparison, Sokolow-Lyon\'s specificity was 92% with a sensitivity of 25%, while Cornell\'s specificity was 94% with a sensitivity of 19%. This indicating its superior diagnostic accuracy of AI based algorithm in LVH detection. Our study demonstrates that AI-based methods for diagnosing LVH exhibit higher diagnostic accuracy compared to conventional criteria, with notable increases in sensitivity. These findings contribute to the validation of AI as a promising tool for LVH detection.

UNASSIGNED: We conducted a comprehensive systematic review to examine the efficacy of intensive blood pressure lowering on the risk of left ventricular hypertrophy (LVH).
UNASSIGNED: We searched PubMed, Scopus, Web of Science, Cochrane Central, and EMBASE for all relevant randomized controlled trials. The primary outcome was the incidence of left ventricular hypertrophy. We used the risk ratio (RR) and hazard ratio (HR) with a 95% confidence interval as our effect sizes.
UNASSIGNED: Four studies, comprising 20,747 patients, were included. Intensive blood pressure lowering was linked with a diminished LVH incidence (RR: 0.66, 95% CI [0.56-0.77]). We also found that intensive blood pressure lowering increased the risk of LVH regression in patients with baseline LVH (RR: 1.21, 95% CI [1.11-1.32]). Finally, intensive blood pressure lowering was linked with a reduced risk of cardiovascular disease (HR: 0.71, 95% CI [0.60-0.85]). No significant heterogeneity was seen in either outcome.
UNASSIGNED: Our study suggests that intensive blood pressure lowering effectively reduces the risk of LVH and cardiovascular disease. An interactive version of our analysis can be accessed here: https://databoard.shinyapps.io/lvh_hypertophy/.

Fibroblast growth factors (FGF) are a type of cell signaling proteins that are mostly produced by macrophages. They are essential for a variety of biological activities involved in normal development. Fibroblast growth factor 23 (FGF23) is the newest and youngest member of the FGF endocrine subfamily, along with fibroblast growth factor 19 (FGF19) and fibroblast growth factor 21 (FGF21). In this study, we conduct a systematic review of all known literature to identify the risk of elevated FGF23 in the cardiovascular system. The analysis includes the risk of cardiovascular disease for both primary and secondary causes of elevated FGF23, such as chronic renal insufficiency. This systematic literature review adhered to the Preferred Reporting Items and Meta-Analysis (PRISMA) standards. A total of 4,793 records were identified across different databases. After that, 273 records were retrieved and reviewed. After carefully examining the titles and summaries of each report, 249 additional entries were eliminated. About 24 studies from the remaining records were chosen by primary and secondary authors for screening, and they performed a quality assessment using common quality check tools. Finally, this review included 11 studies. Following a thorough analysis, we came to the conclusion that FGF23 can be regarded as a novel biomarker and should be included in the group of heart biomarkers that have already been identified, such as B-type natriuretic peptide (BNP), for the early identification of a variety of highly prevalent cardiovascular disorders.

Background: Left ventricular hypertrophy (LVH) is a powerful predictor of future cardiovascular events. Objectives: The objectives of this study were to conduct a systematic review of machine learning (ML) algorithms for the identification of LVH and compare them with respect to the classical features of test sensitivity, specificity, accuracy, ROC and the traditional ECG criteria for LVH. Methods: A search string was constructed with the operators \"left ventricular hypertrophy, electrocardiogram\" AND machine learning; then, Medline and PubMed were systematically searched. Results: There were 14 studies that examined the detection of LVH utilizing the ECG and utilized at least one ML approach. ML approaches encompassed support vector machines, logistic regression, Random Forest, GLMNet, Gradient Boosting Machine, XGBoost, AdaBoost, ensemble neural networks, convolutional neural networks, deep neural networks and a back-propagation neural network. Sensitivity ranged from 0.29 to 0.966 and specificity ranged from 0.53 to 0.99. A comparison with the classical ECG criteria for LVH was performed in nine studies. ML algorithms were universally more sensitive than the Cornell voltage, Cornell product, Sokolow-Lyons or Romhilt-Estes criteria. However, none of the ML algorithms had meaningfully better specificity, and four were worse. Many of the ML algorithms included a large number of clinical (age, sex, height, weight), laboratory and detailed ECG waveform data (P, QRS and T wave), making them difficult to utilize in a clinical screening situation. Conclusions: There are over a dozen different ML algorithms for the detection of LVH on a 12-lead ECG that use various ECG signal analyses and/or the inclusion of clinical and laboratory variables. Most improved in terms of sensitivity, but most also failed to outperform specificity compared to the classic ECG criteria. ML algorithms should be compared or tested on the same (standard) database.

Cantu syndrome is a rare and complex multisystem disorder characterized by hypertrichosis, facial dysmorphism, osteochondroplasia and cardiac abnormalities. With only 150 cases reported worldwide, Cantu syndrome is now gaining wider recognition due to molecular testing and a growing body of literature that further characterizes the syndrome and some of its most important features. Cardiovascular pathology previously described in the literature include cardiomegaly, pericardial effusion, vascular dilation and tortuosity, and other congenital heart defects. However, cardiovascular involvement is highly variable amongst individuals with Cantu syndrome. In some instances, it can be extensive and severe requiring surgical management and long term follow up.
Herein we report a case of a fourteen-year-old female who presented with worsening pericardial effusion of unknown etiology, and echocardiographic findings of concentric left ventricular hypertrophy, a mildly dilated aortic root and ascending aorta. Her medical history was notable for hemoptysis and an episode of pulmonary hemorrhage secondary to multiple aortopulmonary collaterals that were subsequently embolized in early childhood. She was initially managed with Ibuprofen and Colchicine but continued to worsen, and ultimately required a pericardial window for the management of refractory pericardial effusion. Imaging studies obtained on subsequent visits revealed multiple dilated and tortuous blood vessels in the head, neck, chest, and pelvis. A cardiomyopathy molecular studies panel was sent, and a pathogenic variant was identified in the ABCC9 gene, confirming the molecular diagnosis of autosomal dominant Cantu syndrome.
Vascular anomalies and significant cardiac involvement are often present in Cantu syndrome, however there are currently no established screening recommendations or surveillance protocols in place. The triad of hypertrichosis, facial dysmorphism, and unexplained cardiovascular involvement in any patient should raise suspicion for Cantu syndrome and warrant further investigation. Initial cardiac evaluation and follow up should be indicated in any patient with a clinical and/or molecular diagnosis of Cantu syndrome. Furthermore, whole body imaging should be utilized to evaluate the extent of vascular involvement and dictate long term monitoring and care.

The cardiovascular risk associated with left ventricular hypertrophy (LVH) in the community and, particularly, in the hypertensive fraction of the general population, represents the rationale for its timely and accurate identification in order to implement adequate preventive strategies. Although electrocardiography (ECG) is the first-line and most economical method of diagnosing LVH its accuracy is largely suboptimal. Over the last 70 years, dozens of different ECG criteria, mostly based on measurements of QRS voltages, have been proposed. In this long journey, a few years ago Peguero et al. developed a novel ECG voltage criterion, currently recognized as Peguero-Lo Presti (PLP) suggesting that it has greater sensitivity than traditional ECG-LVH criteria. Considering that in the last 5 years numerous studies have investigated the diagnostic value of this new index, this review aimed to summarize the data published so far on this topic focusing both on the accuracy in identifying the presence of LVH compared with imaging techniques such as echocardiography (ECHO) and magnetic resonance imaging (MRI) and the value in predicting hard outcomes. The evidence in favor of the greater diagnostic accuracy of the PLP criterion in detecting LVH, phenotyped by ECHO or MRI, and in the stratification of hard outcomes compared with traditional ECG criteria does not appear to be sufficiently proven. Given that the diagnosis of LVH by all ECG criteria (including the PLP) exclusively based on the QRS amplitude is largely imprecise, the development of new multiparametric ECG criteria based on artificial intelligence could represent a real improvement in the diagnostic capacity of the ECG.

BACKGROUND: Autosomal dominant polycystic kidney disease (ADPKD) is the most common hereditary kidney disease with a prevalence of 1:400 to 1:1,000 in Caucasians. It is caused by mutations in the PKD1 gene located on chromosome 16p13.3 (in about 85% cases) as well as in the PKD2 gene on chromosome 4q13-23. In the Polish population, the disease is associated with PKD1 mutations in 84% of the ADPKD-affected families. PKD1 and PKD2 genes encode the proteins polycystin-1 (PC1) and polycystin-2 (PC2), respectively. The presence of kidney cysts is a characteristic feature in the ADPKD patients. But in the ADPKD patients, cardiovascular abnormalities, such as hypertension (HT) with higher systolic blood pressure (SBP) and diastolic blood pressure (DBP) values, higher left ventricular mass (LVM), intracranial (ICAN) and extracranial aneurysms, and cardiac valve defects, are significantly more common than in the general population.
CONCLUSIONS: According to the literature data, both higher LVM and vascular dysfunction already occur in children and young adults with normal renal function and without HT. Moreover, biventricular diastolic dysfunction, endothelial dysfunction, increased carotid intima-media thickness, and impaired coronary flow velocity reserve are present even in young patients with ADPKD who have normal HT and well-preserved renal function. In patients with ADPKD, hypertension has some specific features; in the youngest age group of children, the prevalence of hypertension is greater if their parents suffer from hypertension; in normotensive young ADPKD-diagnosed individuals, ambulant SBP and DBP values were significantly higher than in age- and gender-matched controls; hypertension appears at least 10 years earlier than spontaneous HT in general population. In adults, HT is often diagnosed before any substantial reduction in the GFR, and a lower nocturnal dip in BP in comparison to hypertensives in the general population. PKD1 and PKD2 gene products (PC1 and PC2 proteins) have been shown to assemble at the plasma membrane and to regulate calcium (Ca2+) entry. A defect in Ca2+ binding mediated by mutations in polycystin proteins is a hypothetical factor contributing to left ventricular mass increase. Altered intracellular Ca2+ handling contributes importantly to impaired contractility associated with heart failure. Impairment of intracellular Ca2+ homeostasis and mitochondrial function has been implicated in the development of LVH.
CONCLUSIONS: It can be assumed that the cause of LVH in ADPKD patients is the natural course of this disease with developing HT and deteriorating kidney function, which may be influenced by the presence of PKD1- and PKD2-mutated gene products: PC1 and PC2 proteins.

Hypertrophic cardiomyopathy (HCM) is a hereditary cardiac condition characterized by unexplained left ventricular hypertrophy without a hemodynamic cause. This condition is prevalent in the United States, resulting in various clinical manifestations, including diastolic dysfunction, left ventricular outflow obstruction, cardiac ischemia, and atrial fibrillation. HCM is associated with several genetic mutations, with sarcomeric mutations being the most common and contributing to a more complex disease course. Early diagnosis of HCM is essential for effective management, as late diagnosis often requires invasive treatments and creates a substantial financial burden. Disparities in HCM diagnosis and treatment exist between high-income and low-income countries. High-income countries have more resources to investigate and implement advanced diagnostic and treatment modalities. In contrast, low-income countries face challenges in accessing diagnostic equipment, trained personnel, and affordable medications, leading to a lower quality of life and life expectancy for affected individuals. Diagnostic tools for HCM include imaging studies such as 2D echocardiography, cardiovascular magnetic resonance (CMR), and electrocardiograms (ECGs). CMR is considered the gold standard but remains inaccessible to a significant portion of the world\'s population, especially in low-income countries. Genetics plays a crucial role in HCM, with numerous mutations identified in various genes. Genetic counseling is essential but often limited in low-income countries due to resource constraints. Disparities in healthcare access and adherence to treatment recommendations exist between high-income and low-income countries, leading to differences in patient outcomes. Addressing these disparities is essential to improve the overall management of HCM on a global scale. In conclusion, this review highlights the complex nature of HCM, emphasizing the importance of early diagnosis, genetic counseling, and access to appropriate diagnostic and therapeutic interventions. Addressing healthcare disparities is crucial to ensure that all individuals with HCM receive timely and effective care, regardless of their geographic location or socioeconomic status.

Masked hypertension (MH) occurs when office blood pressure is normal, but hypertension is confirmed using out-of-office blood pressure measures. Hypertension is a risk factor for subclinical cardiovascular outcomes, including left ventricular hypertrophy, increased left ventricular mass index, carotid intima media thickness, and pulse wave velocity. However, the risk factors for ambulatory blood pressure monitoring defined MH and its association with subclinical cardiovascular outcomes are unclear. A systematic literature search on 9 databases included English publications from 1974 to 2023. Pediatric MH prevalence was stratified by disease comorbidities and compared with the general pediatric population. We also compared the prevalence of left ventricular hypertrophy, and mean differences in left ventricular mass index, carotid intima media thickness, and pulse wave velocity between MH versus normotensive pediatric patients. Of 2199 screened studies, 136 studies (n=28 612; ages 4-25 years) were included. The prevalence of MH in the general pediatric population was 10.4% (95% CI, 8.00-12.80). Compared with the general pediatric population, the risk ratio (RR) of MH was significantly greater in children with coarctation of the aorta (RR, 1.91), solid-organ or stem-cell transplant (RR, 2.34), chronic kidney disease (RR, 2.44), and sickle cell disease (RR, 1.33). MH patients had increased risk of subclinical cardiovascular outcomes compared with normotensive patients, including higher left ventricular mass index (mean difference, 3.86 g/m2.7 [95% CI, 2.51-5.22]), left ventricular hypertrophy (odds ratio, 2.44 [95% CI, 1.50-3.96]), and higher pulse wave velocity (mean difference, 0.30 m/s [95% CI, 0.14-0.45]). The prevalence of MH is significantly elevated among children with various comorbidities. Children with MH have evidence of subclinical cardiovascular outcomes, which increases their risk of long-term cardiovascular disease.