Absolute Eosinophil Count Predicts Intensive Care Unit Transfer Among Elderly COVID-19 Patients From General Isolation Wards - Huang, Jinjin; Zhang, Zhicheng; Liu, Shunfang; Gong, Chen; Chen, Liping; Ai, Guo; Zhu, Xiaodong; Zhang, Chunli; Li, Dengju (Frontiers in Medicine, 2020)
Objectives: As of June 1, 2020, Coronavirus disease 2019 (COVID-19) has caused a global pandemic and resulted in over 370,000 deaths worldwide. Early identification of COVID-19 patients who need to be admitted to intensive care unit (ICU) helps improve the outcomes. We aim to investigate whether absolute eosinophil count (AEC) can predict ICU transfer among elderly COVID-19 patients from general isolated wards. Methods: A retrospective study of 94 elderly patients older than 60 years of age with COVID-19 was conducted. We compared the basic clinical characteristics and levels of inflammation markers on admission to general isolated wards and the needs for ICU transfer between the eosinopenia (AEC on admission <20 cells/µL) and non-eosinopenia (AEC ≥20 cells/µL) groups. Results: There was a significantly higher ICU transfer rate in the eosinopenia group than the non-eosinopenia group (51% vs. 9%, P <0.001). Multivariate analysis revealed that eosinopenia was associated with an increased risk of ICU transfer in elderly COVID-19 patients (adjusted OR 6.12 [95% CI, 1.23-30.33], P = 0.027]) after adjustment of age, lymphocyte count, neutrophil count, C-reactive protein (CRP) and ferritin levels. The eosinopenia group had higher levels of CRP, ferritin and cytokines (IL-2R, IL-6, IL-8, IL-10 and TNF-α) compared to the non-eosinophil group (P <0.001). The AUC of AEC on admission for predicting ICU transfer among elderly COVID-19 patients was 0.828 (95% CI, 0.732-0.923). The best cut-off value of AEC was 25 cells/μL with a sensitivity of 91% and a specificity of 71%, respectively. Conclusion: AEC on admission is a valid predictive marker for ICU transfer among elderly COVID-19 patients from general isolated wards, and therefore can help case triage and optimize ICU utilization, especially for health care facilities with limited ICU capacity.