Congenital heart disease (CHD) is the most common birth defect and affects approximately 8 out of every 1,000 infants born each year. Despite antenatal screening and at least one examination before discharge infants with critical CHD (CCHD) are routinely not detected before discharge from the newborn nursery. Newborn screening for CCHD using pulse oximetry is widely endorsed however until recent efforts, CCHD screening programs had only been implemented at the individual hospital level. The purpose of this paper is to describe the implementation of CCHD screening across the entire Emirate of Abu Dhabi. The Health Authority-Abu Dhabi (HAAD), in collaboration with Children's National Medical Center (Children's National), successfully implemented CCHD screening at the emirate level using a "train-the-trainer," two-tiered approach, starting with two pilot hospitals then rolling the program out to all birthing facilities. In the first year, CCHD screening was added as a mandatory test to the HAAD Newborn Screening Standard, has been implemented in most birthing facilities, and occurs for the majority of infants (86 %) in Abu Dhabi. This led to the identification of ten newborns with CCHD. Based on the successful identification and mitigation of barriers to implementation, the approach may be adapted for similar programs in other populations.
Background: The recent pandemic condition developed from the Coronavirus Disease 2019 (COVID-19) outbreak, have a profound effect on almost all the aspects of society. This outbreak has greatly compromised both the mental and physical health of the frontline healthcare workers and supporting hospital staff since they are responsible for the diagnosis and treatment of infected individuals with COVID-19. This study aimed to investigate the psychological impacts and factors causing stress among the healthcare workers & supporting hospital staff during the COVID-19 outbreak and also to identify the preferred coping strategies. Methodology: This cross-sectional survey-based study was conducted from 1st to 30th February 2020. The sample comprised of frontline healthcare workers & hospital staff providing supporting services like laboratory personnel & administrative workers. The data was collected using a structured self-administered online questionnaire focusing on the impacts of COVID-19, factors causing stress and the coping strategies used by frontline medical workers to deal with the psychological impacts of such pandemics. Results: A total of 127 frontline medical workers completed the survey. The findings from the present study suggested that frontline healthcare workers & hospital staff experience both psychological as well as emotional impacts due to COVID-19. The mean Impact of Event Scale (IES) score was 24.44±19.41 indicating partial PTSD or at least a few symptoms of PTSD. The major factor causing stress among these health workers was their fear of inflicting COVID-19 on family (33.1%). Among the coping strategies, emotion-focused coping techniques and positive thinking were found to be the most preferred strategies among the frontline medical workers and hospital staff in coping stress associated with the COVID-19 outbreak. Conclusion: The current study emphasizes the significance of the psychological impacts of COVID-19 among healthcare workers and the importance of psychiatric help for these long-term traumatic influences.
Artificial intelligence (AI) is the study of algorithms that enable machines to analyze and execute cognitive activities including problem solving, object and word recognition, reduce the inevitable errors to improve the diagnostic accuracy, and decision-making. Hepatobiliary procedures are technically complex and the use of AI in perioperative management can improve patient outcomes as discussed below. Three-dimensional (3D) reconstruction of images obtained
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ultrasound, computed tomography scan or magnetic resonance imaging, can help surgeons better visualize the surgical sites with added depth perception. Pre-operative 3D planning is associated with lesser operative time and intraoperative complications. Also, a more accurate assessment is noted, which leads to fewer operative complications. Images can be converted into physical models with 3D printing technology, which can be of educational value to students and trainees. 3D images can be combined to provide 3D visualization, which is used for preoperative navigation, allowing for more precise localization of tumors and vessels. Nevertheless, AI enables surgeons to provide better, personalized care for each patient.
Cerebral amyloid angiopathy (CAA) is a common untreatable cause of lobar hemorrhages and cognitive decline in the older population. Subset of patients present with its inflammatory subtype with rapid decline in cognitive functions and neurological deficits. Most commonly the underlying pathophysiology of this disease is deposition of insoluble amyloid protein into blood vessel walls which results in vessel fragility leading to local neurotoxicity which may eventually leads to lobar hemorrhages and cognitive decline. The term “Amyloid Spell” encompasses transient focal neurological deficits which is commonly misdiagnosed as seizures or transient ischemic attack in the emergency department. Radiologic findings in these patients may reveal microbleeds, cortical superficial siderosis, white matter hyperintensities, and cerebral edema which support the clinical diagnosis which could be otherwise challenging. CAA diagnostic criteria require CT (Edinburgh Criteria) or MRI imaging, or neuropathology. The diagnosis can be suspected without imaging or neuropathology but cannot be confirmed. This review article provides a critical outlook on different types of presentations, updated diagnostic criteria and management of CAA patients illustrating underlying mechanisms associated with neuronal injury secondary to amyloid deposition.
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