Publications by authors named "M S Silvetti"
Inherited cardiac channelopathies are major causes of sudden cardiac death (SCD) in young people. Genetic testing is focused on the identification of single-nucleotide variants (SNVs) by Next-Generation Sequencing (NGS). However, genetically elusive cases can carry copy number variants (CNVs), which need specific detection tools.
View Article and Find Full Text PDFHypothesis: The aim of the study was to evaluate the correlation between NTproBNP and left ventricular mass (LVM) in children affected by hypertrophic cardiomyopathy (HCM), both asymptomatic, symptomatic, and with implantable cardioverter-defibrillator (ICD).
Methods: A total of 225 pediatric patients were evaluated and 45 were enrolled in the study because met inclusion criteria (age < 18 years; diagnosis of hypertrophic cardiomyopathy; NTproBNP > 600 pg/ml).
Results: The analysis showed a significant correlation between NTproBNP level and LVM (p = 0.
Article Synopsis
- Left ventricular hypertrabeculation (LVHT) is a heart condition that can lead to various symptoms, including serious issues like heart failure and arrhythmias, making it difficult to identify which cases are benign versus pathological.
- A study analyzed 140 pediatric patients with LVHT over ten years, and found that 23.6% of them experienced arrhythmias, with various types identified, including supraventricular and ventricular arrhythmias.
- Results indicated a significant relationship between specific genetic variants (class 4 or 5) and the occurrence of arrhythmias, while the patients generally had good outcomes, with no reported sudden cardiac deaths.
Article Synopsis
- Primary benign cardiac tumors in children are rare but can lead to serious complications like malignant ventricular arrhythmias and cardiac death.
- A study conducted over 38 years included 97 children with various types of tumors, revealing that those with tumors larger than 2.3 cm or diagnosed with fibromas had worse health outcomes.
- The research highlighted that 24.5% of the patients experienced clinically significant arrhythmias, suggesting that tumor type and size are important indicators of potential risks.
We argue that the type of meta-learning proposed by Binz et al. generates models with low interpretability and falsifiability that have limited usefulness for neuroscience research. An alternative approach to meta-learning based on hyperparameter optimization obviates these concerns and can generate empirically testable hypotheses of biological computations.
View Article and Find Full Text PDF