Sugiyama Masaya
Department of Viral Pathogenesis and Controls, National Center for Global Health and Medicine, Ichikawa, Japan.
Glob Health Med. 2023 Apr 30;5(2):78-84. doi: 10.35772/ghm.2022.01046.
The outbreak of the novel coronavirus infection caused worldwide confusion. The problem with this infection is that it causes severe illness in some patients, resulting in a high rate of death if appropriate treatment is not given. If patients with severe illness that requires treatment are appropriately identified, treatment can be focused on these patients. However, in the early days of the COVID-19 outbreak, the inability to predict and diagnose the disease led to hospitals being overwhelmed. Therefore, various methods for the diagnosis of severe disease were developed early on, and various methods are still being investigated to predict high-risk patients. The currently available prediction methods are divided into those that predict the onset of severe disease and those used to determine the severity of the disease. Specifically, the main methods include genetic factors, serum humoral factors, laboratory tests, and diagnostic imaging. Since each of these factors has different features, using them in combination is likely to be advantageous.
新型冠状病毒感染的爆发引起了全球的混乱。这种感染的问题在于,它会使一些患者患上重病,如果不给予适当治疗,死亡率会很高。如果能够适当地识别出需要治疗的重症患者,就可以集中对这些患者进行治疗。然而,在新冠疫情爆发的早期,由于无法预测和诊断这种疾病,医院不堪重负。因此,早期就开发了各种诊断重症的方法,目前仍在研究各种方法来预测高危患者。目前可用的预测方法分为预测重症发病的方法和用于确定疾病严重程度的方法。具体来说,主要方法包括遗传因素、血清体液因素、实验室检查和诊断成像。由于这些因素各自具有不同的特点,联合使用它们可能会有优势。