인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
Abstract Background Mucormycosis is a serious life-threatening fungal infection that recently made severe sudden and devastating surge during the second wave of the COVID-19 epidemic with a mortality rate of up to 50%. Although the causality link between COVID-19 and rhino-orbito-cerebral mucormycosis (ROCM) remains unclear, many factors including poor diabetes control, high doses of steroids, viral-induced lymphopenia, and cytokine storm have been attributed to ROCM in patients with COVID-19. Orienting to risk factors and early recognition of this potentially fatal opportunistic infection is the key to optimal management and improved outcomes. In these contexts, we conducted a prospective study for 33 patients admitted to our tertiary hospital to determine the risk factors for ROCM in patients with COVID-19 and the cumulative mortality rates. Results This study found a statistically significant relation between the fate of death in COVID-MUCOR patients who had presented fever, ophthalmoplegia, facial skin necrosis, and visual loss with those who received dose of steroid to control their respiratory symptoms P < 0.001. Death from COVID-MUCOR was statistically significant related to the prolonged interval from the onset of the symptoms to start of treatment and intervention. Also, it was found that there was a significant decrease in duration between COVID-19 infection and the start of mucormycosis (days) with incidence of DKA on admission. Nineteen (57.6%) of the patients had uncontrolled diabetes mellitus (hemoglobin A1C (HbA1c) of > 7.0%). Conclusion Mucormycosis epidemic was precipitated by a unique confluence of risk factors: diabetes mellitus, widespread use of steroids, and perhaps SARS-CoV-2 infection itself. Restricting steroid use in patients with severe COVID-19 requiring oxygen therapy, and screening for and optimally controlling hyperglycemia, can prevent COVID-MUCOR in a large majority.
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.