ABSTRACT
Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes a disease (coronavirus disease 2019, COVID-19) that may develop into a systemic disease with immunosuppression and death in its severe form. Myeloid-derived suppressive cells (MDSCs) are inhibitory cells that contribute to immunosuppression in patients with cancer and infection. Increased levels of MDSCs have been found in COVID-19 patients, although their role in the pathogenesis of severe COVID-19 has not been clarified. For this reason, we raised the question whether MDSCs could be useful in the follow-up of patients with severe COVID-19 in the intensive care unit (ICU). Thus, we monitored the immunological cells, including MDSCs, in 80 patients admitted into the ICU. After 1, 2, and 3 weeks, we examined for a possible association with mortality (40 patients). Although the basal levels of circulating MDSCs did not discriminate between the two groups of patients, the last measurement before the endpoint (death or ICU discharge) showed that patients discharged alive from the ICU had lower levels of granulocytic MDSCs (G-MDSCs), higher levels of activated lymphocytes, and lower levels of exhausted lymphocytes compared with patients who had a bad evolution (death). In conclusion, a steady increase of G-MDSCs during the follow-up of patients with severe COVID-19 was found in those who eventually died.
ABSTRACT
BACKGROUND: Early identification of patients with COVID-19 who may develop critical illness is of great importance. METHODS: In this study a retrospective cohort of 264 COVID-19 cases admitted at Macarena University was used for development and internal validation of a risk score to predict the occurrence of critical illness in hospitalized patients with COVID-19. Backward stepwise logistic regression was used to derive the model, including clinical and laboratory variables predictive of critical illness. Internal validation of the final model used bootstrapped samples and the model scoring derived from the coefficients. External validation was performed in a cohort of 154 cases admitted at Valme and Virgen del Rocio University Hospital. RESULTS: A total of 62 (23.5%) patients developed a critical illness during their hospitalization stay, 21 (8.0%) patients needed invasive ventilation, 34 (12.9%) were admitted at the ICU and the overall mortality was of 14.8% (39 cases). 5 variables were included in the final model: age >59.5 years (OR: 3.11;95%CI 1.39-6.97), abnormal CRP results (OR: 5.76;95%CI 2.32-14.30), abnormal lymphocytes count (OR: 3.252;95%CI 1.56-6.77), abnormal CK results (OR: 3.38;95%CI 1.59-7.20) and abnormal creatinine (OR: 3.30;95%CI 1.42-7.68). The AUC of this model was 0.850 with sensitivity of 65% and specificity of 87% and the IDI and NRI were 0.1744 and 0.2785, respectively. The validation indicated a good discrimination for the external population. CONCLUSIONS: Biomarkers add prognostic information in COVID-19 patients. Our risk-score provides an easy to use tool to identify patients who are likely to develop critical illness during their hospital stay.