ABSTRACT
BACKGROUND AND OBJECTIVES: Therapeutic plasma exchange (TPE) has been used in severe COVID-19 disease to eliminate the cytokine storm. This meta-analysis aims to assess the effectiveness of TPE in reducing mortality in severe COVID-19 disease compared to standard treatment. MATERIALS AND METHODS: A comprehensive literature search was performed in PubMed, the Cochrane database and the International Clinical Trial Registry Platform (ICTRP). The random-effect model was used to calculate the risk ratio and standardized mean difference (SMD) as pooled effect size for the difference in mortality and length of the intensive care unit (ICU) stay. The risk of bias and publication bias were assessed in R version 4.1.0. The certainty of the evidence was calculated using the GradePro tool. RESULTS: The database identified 382 participants from six studies, including one randomized control trial. Egger's test did not detect any publication bias (p = 0.178). The random model analysis for mortality evaluated a risk ratio of 0.38 (95% CI: 0.28-0.52) with a significant reduction in the TPE group. The certainty of the evidence was moderate, with a risk ratio of 0.34 (95% CI: 0.24-0.49). Length of ICU stays between TPE versus standard care showed an SMD of 0.08 (95% CI: -0.38, 0.55) and was not significant. CONCLUSION: The length of ICU stay in the TPE group was not different from standard care. However, this meta-analysis revealed a significant benefit of TPE in reducing mortality in severe COVID-19 disease compared to standard treatment.
ABSTRACT
Coronavirus disease 2019 (COVID-19) broke out and then became a global epidemic at the end of 2019. With the increasing number of deaths, early identification of disease severity and interpretation of pathogenesis are very important. Aiming to identify biomarkers for disease severity and progression of COVID-19, 75 COVID-19 patients, 34 healthy controls and 23 patients with pandemic influenza A(H1N1) were recruited in this study. Using liquid chip technology, 48 cytokines and chemokines were examined, among which 33 were significantly elevated in COVID-19 patients compared with healthy controls. HGF and IL-1ß were strongly associated with APACHE II score in the first week after disease onset. IP-10, HGF and IL-10 were correlated positively with virus titers. Cytokines were significantly correlated with creatinine, troponin I, international normalized ratio and procalcitonin within two weeks after disease onset. Univariate analyses were carried out, and 6 cytokines including G-CSF, HGF, IL-10, IL-18, M-CSF and SCGF-ß were found to be associated with the severity of COVID-19. 11 kinds of cytokines could predict the severity of COVID-19, among which IP-10 and M-CSF were excellent predictors for disease severity. In conclusion, the levels of cytokines in COVID-19 were significantly correlated with the severity of the disease in the early stage, and serum cytokines could be used as warning indicators of the severity and progression of COVID-19. Early stratification of disease and intervention to reduce hypercytokinaemia may improve the prognosis of COVID-19 patients.