Background: Cardiovascular complications due to viral infection pose a significant risk in vulnerable patients such as those with congenital heart disease (CHD). Limited data exists regarding the incidence of influenza and its impact on cardiovascular outcomes among this specific patient population.
Methods: A retrospective cohort study was designed using the Canadian Congenital Heart Disease (CanCHD) database-a pan-Canadian database of CHD patients with up to 35 years of follow-up.
In rodents, anxiety is charactered by heightened vigilance during low-threat and uncertain situations. Though activity in the frontal cortex and limbic system are fundamental to supporting this internal state, the underlying network architecture that integrates activity across brain regions to encode anxiety across animals and paradigms remains unclear. Here, we utilize parallel electrical recordings in freely behaving mice, translational paradigms known to induce anxiety, and machine learning to discover a multi-region network that encodes the anxious brain-state.
View Article and Find Full Text PDFBackground: Traditional methods of risk assessment for thoracic aortic aneurysm (TAA) based on aneurysm size alone have been called into question as being unreliable in predicting complications. Biomechanical function of aortic tissue may be a better predictor of risk, but it is difficult to determine in vivo.
Objectives: This study investigates using a machine learning (ML) model as a correlative measure of energy loss, a measure of TAA biomechanical function.
Professional divers exposed to pressures greater than 11 ATA (1.1 MPa) may suffer from high-pressure neurological syndrome (HPNS). Divers who use closed-circuit breathing apparatus and patients and medical attendants undergoing hyperbaric oxygen therapy (HBOT) face the risk of CNS hyperbaric oxygen toxicity (HBOTx) at oxygen pressure above 2 ATA (0.
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