Surgical revascularisation in an adult with coarctation of the aorta.

One of the most common congenital cardiac anomalies is It accounts for 4%-6% of all congenital heart defects. A CoA case surviving into adulthood may result in hypertension, weak femoral pulse, limb and bowel ischaemia and heart failure. A man in his early 20s presented with severe lower limb and abdominal pain with long-standing hypertension, refractory to antihypertensives.

Factors influencing the first dose of measles vaccination uptake in 42 low- and middle-income countries.

Objectives: Vaccination against measles still stands as a highly impactful public health strategy for mitigating childhood morbidity and mortality. Relatively poor immunization coverage among children has been observed in low and middle-income countries (LMICs). Our study intended to determine socio-demographic factors associated with the 1st dose of measles vaccination among South Asian (SA) and SubSaharan African (SSA) countries children.

Chronic Morbidities Overrule Acute Morbidities in Determining Self-Reported Health in Rural Bangladesh.

Self- rated health (SRH) is a valuable screening-level measure of a community's health status. A better understanding of the factors that influence SRH is time-demanding and challenging. This study aims to examine the determinants of SRH by investigating health morbidities, demographic and socio-economic factors in Bangladesh perspective.

Delivery Methods in Twin Gestations: Evaluating Outcomes, Risk Factors, and the Paradigm Shift Towards Elective Cesarean Deliveries.

During the past decade, there has been a consistent rise in the number of twin births and the number of overall cesarean sections (CS) worldwide. This is owed to a variety of social, economic, educational, and scientific factors. More women are opting to advance their professional careers and gain financial stability before having children.

Role of artificial intelligence and machine learning in the diagnosis of cerebrovascular disease.

Introduction: Cerebrovascular diseases are known to cause significant morbidity and mortality to the general population. In patients with cerebrovascular disease, prompt clinical evaluation and radiographic interpretation are both essential in optimizing clinical management and in triaging patients for critical and potentially life-saving neurosurgical interventions. With recent advancements in the domains of artificial intelligence (AI) and machine learning (ML), many AI and ML algorithms have been developed to further optimize the diagnosis and subsequent management of cerebrovascular disease.