Muhammad Sajjad, Fischer Igor, Naderi Soheil, Faghih Jouibari Morteza, Abdolreza Sheikhrezaei, Karimialavijeh Ehsan, Aslzadeh Sara, Mashayekhi Mahsa, Zojaji Mohaddeseh, Kahlert Ulf Dietrich, Hänggi Daniel
Department of Neurosurgery, Medical Faculty, Heinrich-Heine-University, Moorenstrasse 5, 40225 Düsseldorf, Germany.
Department of Neurosurgery, Tehran University of Medical Sciences, Theran 1417613151, Iran.
Pathogens. 2021 Jan 11;10(1):58. doi: 10.3390/pathogens10010058.
Coronavirus disease 2019 (COVID-19), with an increasing number of deaths worldwide, has created a tragic global health and economic emergency. The disease, caused by severe acute respiratory syndrome coronavirus 2019 (SARS-CoV-19), is a multi-system inflammatory disease with many of COVID-19-positive patients requiring intensive medical care due to multi-organ failures. Biomarkers to reliably predict the patient's clinical cause of the virus infection, ideally, to be applied in point of care testing or through routine diagnostic approaches, are highly needed. We aimed to probe if routinely assessed clinical lab values can predict the severity of the COVID-19 course. Therefore, we have retrospectively analyzed on admission laboratory findings in 224 consecutive patients from four hospitals and show that systemic immune inflammation index (SII) is a potent marker for predicting the requirement for invasive ventilator support and for worse clinical outcome of the infected patient. Patients' survival and severity of SARS-CoV-2 infection could reliably be predicted at admission by calculating the systemic inflammatory index of individual blood values. We advocate this approach to be a feasible and easy-to-implement assay that may be particularly useful to improve patient management during high influx crisis. We believe with this work to contribute to improving infrastructure availability and case management associated with COVID-19 pandemic hurdles.
2019年冠状病毒病（COVID-19）在全球范围内导致的死亡人数不断增加，引发了一场悲惨的全球卫生和经济紧急情况。该疾病由严重急性呼吸综合征冠状病毒2 2019（SARS-CoV-19）引起，是一种多系统炎症性疾病，许多COVID-19阳性患者因多器官衰竭而需要重症医疗护理。迫切需要能够可靠预测病毒感染患者临床病因的生物标志物，理想情况下可用于即时检测或通过常规诊断方法进行检测。我们旨在探究常规评估的临床实验室值是否能够预测COVID-19病程的严重程度。因此，我们回顾性分析了来自四家医院的224例连续患者入院时的实验室检查结果，结果表明全身免疫炎症指数（SII）是预测有创通气支持需求以及感染患者不良临床结局的有力标志物。通过计算个体血液值的全身炎症指数，在入院时能够可靠地预测患者的生存情况和SARS-CoV-2感染的严重程度。我们主张这种方法是一种可行且易于实施的检测方法，在高流量危机期间可能对改善患者管理特别有用。我们相信这项工作有助于改善与COVID-19大流行障碍相关的基础设施可用性和病例管理。
