Associations of immunological features with COVID-19 severity: a systematic review and meta-analysis.

BACKGROUND: COVID-19 has spread widely worldwide, causing millions of deaths. We aim to explore the association of immunological features with COVID-19 severity. METHODS: We conducted a meta-analysis to estimate mean difference (MD) of immune cells and cytokines levels with COVID-19 severity in PubMed, Web of Science, Scopus, the Cochrane Library and the grey literature. RESULTS: A total of 21 studies with 2033 COVID-19 patients were included. Compared with mild cases, severe cases showed significantly lower levels of immune cells including CD3+ T cell (× 106, MD, - 413.87; 95%CI, - 611.39 to - 216.34), CD4+ T cell (× 106, MD, - 203.56; 95%CI, - 277.94 to - 129.18), CD8+ T cell (× 106, MD, - 128.88; 95%CI, - 163.97 to - 93.79), B cell (× 106/L; MD, - 23.87; 95%CI, - 43.97 to - 3.78) and NK cell (× 106/L; MD, - 57.12; 95%CI, - 81.18 to - 33.06), and significantly higher levels of cytokines including TNF-α (pg/ml; MD, 0.34; 95%CI, 0.09 to 0.59), IL-5 (pg/ml; MD, 14.2; 95%CI, 3.99 to 24.4), IL-6 (pg/ml; MD, 13.07; 95%CI, 9.80 to 16.35), and IL-10 (pg/ml; MD, 2.04; 95%CI, 1.32 to 2.75), and significantly higher levels of chemokines as MCP-1 (SMD, 3.41; 95%CI, 2.42 to 4.40), IP-10 (SMD, 2.82; 95%CI, 1.20 to 4.45) and eotaxin (SMD, 1.55; 95%CI, 0.05 to 3.05). However, no significant difference was found in other indicators such as Treg cell (× 106, MD, - 0.13; 95%CI, - 1.40 to 1.14), CD4+/CD8+ ratio (MD, 0.26; 95%CI, - 0.02 to 0.55), IFN-γ (pg/ml; MD, 0.26; 95%CI, - 0.05 to 0.56), IL-2 (pg/ml; MD, 0.05; 95%CI, - 0.49 to 0.60), IL-4 (pg/ml; MD, - 0.03; 95%CI, - 0.68 to 0.62), GM-CSF (SMD, 0.44; 95%CI, - 0.46 to 1.35), and RANTES (SMD, 0.94; 95%CI, - 2.88 to 4.75). CONCLUSION: Our meta-analysis revealed significantly lower levels of immune cells (CD3+ T, CD4+ T, CD8+ T, B and NK cells), higher levels of cytokines (TNF-α, IL-5, IL-6 and IL-10) and higher levels of chemokines (MCP-1, IP-10 and eotaxin) in severe cases in comparison to mild cases of COVID-19. Measurement of immunological features could help assess disease severity for effective triage of COVID-19 patients.

Absolute Eosinophil Count Predicts Intensive Care Unit Transfer Among Elderly COVID-19 Patients From General Isolation Wards.

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 the intensive care unit (ICU) helps to improve the outcomes. We aim to investigate whether absolute eosinophil count (AEC) can predict ICU transfer among elderly COVID-19 patients from general isolation wards. Methods: A retrospective study of 94 elderly patients older than 60 years old with COVID-19 was conducted. We compared the basic clinical characteristics and levels of inflammation markers on admission to general isolation 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 in 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 odds ratio (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 [interleukin-2 receptor (IL-2R), interleukin-6 (IL-6), interleukin-8 (IL-8), interleukin-10 (IL-10), and tumor necrosis factor-α (TNF-α)] than the non-eosinophil group (P < 0.001). The area under the curve 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: Absolute eosinophil count on admission is a valid predictive marker for ICU transfer among elderly COVID-19 patients from general isolation wards and, therefore, can help case triage and optimize ICU utilization, especially for health care facilities with limited ICU capacity.