COVID-19 patients with altered steroid hormone levels are more likely to have higher disease severity.

PURPOSE: This study aims to evaluate the correlations between the severity of the disease and serum steroid levels by analyzing the serum steroid levels in COVID-19 patients with different levels of disease progression and the control group. METHODS: Morning serum Aldosterone, 11-deoxycortisol, Androstenedione, 17-hydroxyprogesterone, Dihydrotestosterone (DHT), Dehydroepiandrosterone (DHEA), Corticosterone, Dehydroepiandrosterone sulfate (DHEAS), Estrone, Estradiol, Progesterone, 11-deoxycorticosterone, Cortisol, Corticosterone, Androsterone, Pregnenolone, 17-hydroxypregnenolone and 21-deoxycortisol levels were measured in 153 consecutive patients were grouped as mild, moderate, and severe based on the WHO COVID-19 disease severity classification and the control group. Steroid hormone levels were analyzed at once with a liquid chromatography-tandem mass spectrometric method (LC-MS/MS). RESULTS: In our study, nearly all steroids were statistically significantly higher in the patients' group than in the control group (p < 0.001). Also, DHEA was an independent indicator of the disease severity with COVID-19 CONCLUSIONS: Our study reveals that the alteration in steroid hormone levels was correlated with disease severity. Also, steroid hormone levels should be followed up during COVID-19 disease management.

Assessment of Galectin-1, Galectin-3, and Prostaglandin E2 Levels in Patients with COVID-19.

It is important to determine the inflammatory biomarkers in the severity of coronavirus disease 2019 (COVID-19) with the emergence of the pandemic. Galectins and prostaglandins play important roles in the regulation of immune and inflammatory responses. Therefore, this study aimed to investigate Galectin-1 (Gal-1), Galectin-3 (Gal-3), and prostaglandin E2 (PGE2) levels in patients with COVID-19. Serum concentrations of Gal-1, Gal-3, and PGE2 were measured using enzyme-linked immunosorbent assay on 84 patients with COVID-19 (severe = 29 and nonsevere = 55) and 56 healthy controls. In this study, increased levels of Gal-1 (median, 9.86, 6.35, and 3.67 ng/mL), Gal-3 (median, 415.31, 326.33, and 243.13 pg/mL), and PGE2 (median, 193.17, 192.58, and 124.62 pg/mL) levels were found in patients with COVID-19 than in healthy controls (P < 0.001 for all). In the severe disease group, Gal-3 levels were higher, while no differences were noted in Gal-1 and PGE2 levels (P = 0.011, P = 0.263, and P = 0.921, respectively). Serum levels of Gal-1 were positively correlated with those of Gal-3 (P = 0.871 and P < 0.001). Gal-3, C-reactive protein, lymphocyte count, and age were found as independent predictors of disease severity (P = 0.002, P = 0.001, P = 0.007, and P = 0.003, respectively). With the emergence of effective drug needs in the COVID-19 pandemic, differentiation of severe disease is important. Therefore, Gal-3 could be a potential prognostic biomarker of COVID-19.

Lymphocyte Subset Alteration and Monocyte CD4 Expression Reduction in Patients with Severe COVID-19.

The spectrum of coronavirus disease 2019 (COVID-19) severity, related to cellular immune functions, has not been fully clarified yet. Therefore, this study aimed to investigate the alteration of peripheral blood cells in patients with COVID-19. The flow cytometric characterization of immune cell subset was performed on 69 COVID-19 patients and 21 healthy controls. These data were evaluated based on the disease severity. A total of 69 patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were classified as asymptomatic infection (n = 14), nonsevere (n = 39), and severe (n = 16) groups. Decreased lymphocytes and increased CD14 + 4- monocytes are found in patients with severe COVID-19. Decreased CD4 expression level was observed in the monocytes of patients with severe COVID-19. The total lymphocytes, B and T lymphocytes, CD4+ cells and CD8+ cells, and natural killer (NK) and natural killer T (NKT) cells were found to be decreased in patients with severe COVID-19. The CD4+/CD8+ ratio was not significantly different between patients with COVID-19 and healthy controls. The percentage of activated T cells (CD3+HLA-DR+) and B cells (CD19+CD38+) was lower in patients with severe COVID-19. Age and CD4- monocytes were independent predictors of disease severity. The SARS-CoV-2 infection may affect lymphocyte subsets, resulting in decreased T and B cells, monocytes, and NK and NKT cells. Decreased CD4 expression level by monocytes was significantly correlated with disease severity. Further studies on the host immune response to SARS-CoV-2 infection are necessary to predict the disease severity and protect against the virus.

Clinical and laboratory features of COVID-19: Predictors of severe prognosis.

BACKGROUND: Coronavirus disease 2019 (COVID-19) emerged first in December 2019 in Wuhan, China and quickly spread throughout the world. Clinical and laboratory data are of importance to increase the success in the management of COVID-19 patients. METHODS: Data were obtained retrospectively from medical records of 191 hospitalized patients diagnosed with COVID-19 from a tertiary single-center hospital between March and April 2020. Prognostic effects of variables on admission among patients who received intensive care unit (ICU) support and those who didn't require ICU care were compared. RESULTS: Patients required ICU care (n = 46) were older (median, 71 vs. 43 years), with more underlying comorbidities (76.1% vs. 33.1%). ICU patients had lower lymphocytes, percentage of large unstained cell (%LUC), hemoglobin, total protein, and albumin, but higher leucocytes, neutrophils, neutrophil-lymphocyte ratio (NLR), monocyte-lymphocyte ratio (MLR), platelet-lymphocytes ratio (PLR), urea, creatinine, aspartate amino transferase (AST), lactate dehydrogenase (LDH), and D-dimer when compared with non-critically ill patients (p < 0.001). A logistic regression model was created to include ferritin, %LUC, NLR, and D-dimer. %LUC decrease and D-dimer increase had the highest odds ratios (0.093 vs 5.597, respectively) to predict severe prognosis. D-dimer, CRP, and NLR had the highest AUC in the ROC analysis (0.896, 0.874, 0.861, respectively). CONCLUSIONS: The comprehensive analysis of clinical and admission laboratory parameters to identify patients with severe prognosis is important not only for the follow-up of the patients but also to identify the pathophysiology of the disease. %LUC decrease and D-dimer, NLR, and CRP increases seem to be the most powerful laboratory predictors of severe prognosis.