Objective

Side-to-side anastomosis provides excellent results for TAPVC repair while left atrial enlargement procedures appear to be associated with higher risk of late arrhythmias. Although early and aggressive reintervention for recurrent PV obstruction is mandatory, intrinsic PV stenosis remains a predictor of adverse outcome.

Quantitative analysis evaluation of globus pallidus:thalamus and dentate nucleus:pons of the pediatric brain demonstrated an increase after serial administrations of macrocyclic GBCA. Further research is necessary to fully understand GBCA pharmacokinetic in children.

Cardiac defects were present in three-quarters of our patients. Pulmonary arterial lesions generally improved, while supravalvar aortic stenosis often progressed. Atypical cardiac malformations, particularly ventricular septal defects, occurred frequently. Systemic hypertension was found in one-fifth, even in the absence of structural cardiac defects. The short-term mortality was low.

In recent years, gadolinium-based contrast agents have been associated with different types of toxicity. In particular, nephrogenic systemic fibrosis, a progressive sclerotic-myxedematous systemic disease of unknown etiology, is related to gadolinium-based contrast agent administration in patients with kidney dysfunction. More recently, evidence of magnetic resonance signal intensity changes on pre-contrast T1-weighted images after multiple gadolinium-based contrast agent administrations resulted in the hypothesis of gadolinium brain accumulation in patients with normal renal function, subsequently confirmed in pathological samples. However, there is limited current data and further investigations are necessary before drawing definite conclusions on the clinical consequences of gadolinium-based contrast agent accumulation in human tissues and particularly in the brain. Gadolinium-based contrast agent-related toxicity appears connected to molecular stability, which varies together with the pharmacokinetic properties of the compound and depends on the individual characteristics of the subject. During a lifetime, the physiological changes occurring in the human body may influence its interaction with gadolinium-based contrast agents: the integrity and developmental stage of the organs has an effect on the dynamics of gadolinium-based contrast agent distribution and excretion, thus leading to different possible mechanisms of deposition and toxicity. Therefore, the aim of this work is to discuss the pharmacokinetics and pharmacodynamics of gadolinium-based contrast agents, with a special focus on the brain, and to explore potential predominant gadolinium-based contrast agent-related toxicity in two cornerstone periods of the human life cycle: fetal/neonatal and adulthood/aged.

After arterial switch operation, there is an increasing frequency of neoaortic regurgitation, which may lead to significant valvular dysfunction later in life. The trap-door type of coronary reimplantation is associated with an increased risk for valvular dysfunction, possibly because of a distortion of the sinotubular junction geometry. For this reason, we recommend the punch technique for repair in all but the most complicated coronary pattern.

Two types of congenital mitral ring, with diverse valve pathology and outcome, were identified. Rarely seen in neonates, the ring develops and often progresses during infancy. Recognition is important because surgical results are better than for other forms of congenital mitral stenosis.

More than a year has passed since the report of the first case of coronavirus disease 2019 (COVID), and increasing deaths continue to occur. Minimizing the time required for resource allocation and clinical decision making, such as triage, choice of ventilation modes and admission to the intensive care unit is important. Machine learning techniques are acquiring an increasingly sought-after role in predicting the outcome of COVID patients. Particularly, the use of baseline machine learning techniques is rapidly developing in COVID mortality prediction, since a mortality prediction model could rapidly and effectively help clinical decision-making for COVID patients at imminent risk of death. Recent studies reviewed predictive models for SARS-CoV-2 diagnosis, severity, length of hospital stay, intensive care unit admission or mechanical ventilation modes outcomes; however, systematic reviews focused on prediction of COVID mortality outcome with machine learning methods are lacking in the literature. The present review looked into the studies that implemented machine learning, including deep learning, methods in COVID mortality prediction thus trying to present the existing published literature and to provide possible explanations of the best results that the studies obtained. The study also discussed challenging aspects of current studies, providing suggestions for future developments.