The Chemokine MIG is Associated with an Increased Risk of COVID-19 Mortality in Mexican Patients.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is an emergent viral disease in which the host inflammatory response modulates the clinical outcome. Severe outcomes are associated with an exacerbation of inflammation in which chemokines play an important role as the attractants of immune cells to the tissues. OBJECTIVE: To evaluate the relationship of the chemokines IL-8, RANTES, MIG, MCP-1, and IP-10 with COVID-19 severity and outcomes in Mexican patients. METHODS: We analyzed the serum levels of IL-8, RANTES, MIG, MCP-1 and IP-10 in 148 COVID-19 hospitalized patients classified as mild (n=20), severe (n=61), and critical (n=67), as well as in healthy individuals (n=10), by flow cytometry bead array assay. RESULTS: Chemokine levels were higher in patients than in the healthy individuals, but only MIG, MCP-1, and IP-10 increased according to the disease severity, showing the highest levels in the critical group. MIG, MCP-1, and IP-10 levels were also higher in COVID-19 patients with comorbidities such as renal disease, type 2 diabetes, and hypertension. Moreover, elevated MIG levels seem to be related to organic failure/shock, and an increased risk of death. CONCLUSIONS: Our results suggest that the increased levels of MCP-1, IP-10, and especially MIG might be useful in predicting severe COVID-19 outcomes and could be promising therapeutic targets.

The Usefulness of Peripheral Blood Cell Counts to Distinguish COVID-19 from Dengue during Acute Infection.

COVID-19 and dengue disease are challenging to tell apart because they have similarities in clinical and laboratory features during the acute phase of infection, leading to misdiagnosis and delayed treatment. The present study evaluated peripheral blood cell count accuracy to distinguish COVID-19 non-critical patients from non-severe dengue cases between the second and eleventh day after symptom onset. A total of 288 patients infected with SARS-CoV-2 (n = 105) or dengue virus (n = 183) were included in this study. Neutrophil, platelet, and lymphocyte counts were used to calculate the neutrophil-lymphocyte ratio (NLR), the platelet-lymphocyte ratio (PLR), and the neutrophil-lymphocyte*platelet ratio (NLPR). The logistic regression and ROC curves analysis revealed that neutrophil and platelet counts, NLR, LPR, and NLPR were higher in COVID-19 than dengue. The multivariate predictive model showed that the neutrophils, platelets, and NLPR were independently associated with COVID-19 with a good fit predictive value (p = 0.1041). The neutrophil (AUC = 0.95, 95% CI = 0.84-0.91), platelet (AUC = 0.89, 95% CI = 0.85-0.93) counts, and NLR (AUC = 0.88, 95% CI = 0.84-0.91) were able to discriminate COVID-19 from dengue with high sensitivity and specificity values (above 80%). Finally, based on predicted probabilities on combining neutrophils and platelets with NLR or NLPR, the adjusted AUC was 0.97 (95% CI = 0.94-0.98) to differentiate COVID-19 from dengue during the acute phase of infection with outstanding accuracy. These findings might suggest that the neutrophil, platelet counts, and NLR or NLPR provide a quick and cost-effective way to distinguish between dengue and COVID-19 in the context of co-epidemics in low-income tropical regions.