Hippchen Theresa, Altamura Sandro, Muckenthaler Martina U, Merle Uta
Department of Internal Medicine IV, University Hospital Heidelberg, Heidelberg, Germany.
Pediatric Oncology, Hematology and Immunology, University Hospital Heidelberg, Heidelberg, Germany.
Hemasphere. 2020 Nov 10;4(6):e492. doi: 10.1097/HS9.0000000000000492. eCollection 2020 Dec.
Iron metabolism might play a crucial role in cytokine release syndrome in COVID-19 patients. Therefore, we assessed iron metabolism markers in COVID-19 patients for their ability to predict disease severity. COVID-19 patients referred to the Heidelberg University Hospital were retrospectively analyzed. Patients were divided into outpatients (cohort A, n = 204), inpatients (cohort B, n = 81), and outpatients later admitted to hospital because of health deterioration (cohort C, n = 23). Iron metabolism parameters were severely altered in patients of cohort B and C compared to cohort A. In multivariate regression analysis including age, gender, CRP and iron-related parameters only serum iron and ferritin were significantly associated with hospitalization. ROC analysis revealed an AUC for serum iron of 0.894 and an iron concentration <6 μmol/l as the best cutoff-point predicting hospitalization with a sensitivity of 94.7% and a specificity of 67.9%. When stratifying inpatients in a low- and high oxygen demand group serum iron levels differed significantly between these two groups and showed a high negative correlation with the inflammatory parameters IL-6, procalcitonin, and CRP. Unexpectedly, serum iron levels poorly correlate with hepcidin. We conclude that measurement of serum iron can help predicting the severity of COVID-19. The differences in serum iron availability observed between the low and high oxygen demand group suggest that disturbed iron metabolism likely plays a causal role in the pathophysiology leading to lung injury.
铁代谢可能在新冠病毒疾病(COVID-19)患者的细胞因子释放综合征中起关键作用。因此,我们评估了COVID-19患者的铁代谢标志物预测疾病严重程度的能力。对转诊至海德堡大学医院的COVID-19患者进行了回顾性分析。患者被分为门诊患者(A组,n = 204)、住院患者(B组,n = 81)以及后来因健康状况恶化而入院的门诊患者(C组,n = 23)。与A组相比,B组和C组患者的铁代谢参数发生了严重改变。在包括年龄、性别、C反应蛋白(CRP)和铁相关参数的多变量回归分析中,只有血清铁和铁蛋白与住院显著相关。受试者工作特征(ROC)分析显示,血清铁的曲线下面积(AUC)为0.894,铁浓度<6 μmol/L作为预测住院的最佳截断点,敏感性为94.7%,特异性为67.9%。将住院患者分为低氧需求组和高氧需求组时,两组之间的血清铁水平存在显著差异,并且与炎症参数白细胞介素-6(IL-6)、降钙素原和CRP呈高度负相关。出乎意料的是,血清铁水平与铁调素的相关性较差。我们得出结论,血清铁的测量有助于预测COVID-19的严重程度。在低氧需求组和高氧需求组之间观察到的血清铁可用性差异表明,铁代谢紊乱可能在导致肺损伤的病理生理过程中起因果作用。