Background: The decision to allocate hospitals for the initial reception of hostages abducted on the October 7th Hamas attack introduced an array of unprecedented challenges. These challenges stemmed from a paucity of existing literature and protocols, lack of information regarding captivity conditions, and variability in hostage characteristics and circumstances.
Objective: To describe the rapid development, implementation and evaluation of the Hostage-ReSPOND protocol, a comprehensive trauma-informed procedure for the care of hostages, including young children, their caregivers and families, immediately following their release from prolonged captivity.
Background: At the beginning of 2020, the coronavirus disease 2019 (COVID-19) pandemic presented a new burden on healthcare systems.
Objectives: To evaluate the impact of the COVID-19 pandemic on the outcome of non-COVID patients in Israel.
Methods: We conducted a retrospective observational cohort study at a tertiary medical center in Israel.
Background: Autoimmune neutropenia (AIN) is divided into primary and secondary forms. The former is more prevalent in children and is usually a self-limiting disease. Secondary AIN is more common in adults and often occurs in the setting of another autoimmune disorder or secondary to infections, malignancies or medications.
View Article and Find Full Text PDFAs the coronavirus pandemic emerged in late 2019, a task force was founded in the Sheba Medical Center and began preparing for the arrival of the pandemic to Israel. Several wards were put in charge of isolated COVID-19 patients. A new intensive care unit was formed for the most critical COVID-19 patients, requiring mechanical ventilation and multi-organ treatment.
View Article and Find Full Text PDFAmong patients with Coronavirus disease (COVID-19), the ability to identify patients at risk for deterioration during their hospital stay is essential for effective patient allocation and management. To predict patient risk for critical COVID-19 based on status at admission using machine-learning models. Retrospective study based on a database of tertiary medical center with designated departments for patients with COVID-19.
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