Medicine/Rheumatology, Lewis Katz School of Medicine at Temple University, Philadelphia, Pennsylvania, USA
Department of Psychology, University of Milano-Bicocca, Milan, Italy.
Ann Rheum Dis. 2021 Jan;80(1):88-95. doi: 10.1136/annrheumdis-2020-218323. Epub 2020 Sep 25.
To develop predictive criteria for COVID-19-associated cytokine storm (CS), a severe hyperimmune response that results in organ damage in some patients infected with COVID-19. We hypothesised that criteria for inflammation and cell death would predict this type of CS.
We analysed 513 hospitalised patients who were positive for COVID-19 reverse transcriptase PCR and for ground-glass opacity by chest high-resolution CT. To achieve an early diagnosis, we analysed the laboratory results of the first 7 days of hospitalisation. We implemented logistic regression and principal component analysis to determine the predictive criteria. We used a 'genetic algorithm' to derive the cut-offs for each laboratory result. We validated the criteria with a second cohort of 258 patients.
We found that the criteria for macrophage activation syndrome, haemophagocytic lymphohistiocytosis and the HScore did not identify the COVID-19 cytokine storm (COVID-CS). We developed new predictive criteria, with sensitivity and specificity of 0.85 and 0.80, respectively, comprising three clusters of laboratory results that involve (1) inflammation, (2) cell death and tissue damage, and (3) prerenal electrolyte imbalance. The criteria identified patients with longer hospitalisation and increased mortality. These results highlight the relevance of hyperinflammation and tissue damage in the COVID-CS.
We propose new early predictive criteria to identify the CS occurring in patients with COVID-19. The criteria can be readily used in clinical practice to determine the need for an early therapeutic regimen, block the hyperimmune response and possibly decrease mortality.
开发与 COVID-19 相关细胞因子风暴（CS）相关的预测标准，这是一种严重的过度免疫反应，导致某些感染 COVID-19 的患者发生器官损伤。我们假设炎症和细胞死亡的标准将预测这种类型的 CS。
我们分析了 513 名经 COVID-19 逆转录酶 PCR 和胸部高分辨率 CT 检测呈阳性的住院患者。为了实现早期诊断，我们分析了住院前 7 天的实验室结果。我们实施了逻辑回归和主成分分析来确定预测标准。我们使用“遗传算法”为每个实验室结果确定截止值。我们使用第二组 258 名患者验证了这些标准。
我们发现巨噬细胞活化综合征、噬血细胞性淋巴组织细胞增多症和 H 评分标准无法识别 COVID-19 细胞因子风暴（COVID-CS）。我们开发了新的预测标准，敏感性和特异性分别为 0.85 和 0.80，包括三个实验室结果群，涉及（1）炎症，（2）细胞死亡和组织损伤，以及（3）肾前电解质失衡。这些标准确定了住院时间更长和死亡率增加的患者。这些结果强调了 COVID-CS 中过度炎症和组织损伤的相关性。
我们提出了新的早期预测标准，以识别 COVID-19 患者中发生的 CS。这些标准可以在临床实践中轻松使用，以确定是否需要早期治疗方案，阻断过度免疫反应并可能降低死亡率。
