[Investigation of the Relationship Between the Immune Responses due to COVID-19 Vaccine and Peripheral Bloodlymphocyte Subtypes of Healthcare Workers]. / Saglik Çalisanlarinda COVID-19 Asisina Bagli Bagisik Yanit ile Hemogram Parametreleri ve Periferik Kandaki Lenfosit Alt Tipleri Arasindaki Iliskinin Arastirilmasi.

Worldwide vaccination is the best strategy to limit the Coronavirus disease-2019 (COVID-19) pandemic. The aim of this study was to investigate the antibody levels and hemogram parameters and the prediction of T-helper, T-cytotoxic and B lymphocyte subtypes in the peripheral blood for the development of these antibodies in the selected group of healthcare workers who were vaccinated with CoronaVac® (Sinovac, China). In a previous study with the same researchers, blood samples were taken from healthcare workers one month after the second vaccination, and anti-RBD anti-severe acute respiratory syndrome coronavirus-2 (anti-SARS-CoV-2) IgG antibodies were measured by enzyme linked immunosorbent assay (ELISA) method. Test results were classified as binding antibody <25.6 BAU/mL unresponsive, 25.6-35.1 BAU/mL weak response, <35.2 BAU/mL strong response, according to the assay manufacturer's recommendations. According to these criteria, it was determined that 22 (8.3%) people had no response, 25 (9.5%) people had a moderate response, and 217 (82.2%) people had a strong response. According to these results, 30 people from each group were invited. The results of three individuals were excluded from the evaluation due to chronic illness. A total of 87 health workers were included in the study. Twenty-two of these people had no response, 25 had a moderate response, and 40 had a good response. Flow cytometry was used to examine the peripheral blood lymphocyte percentage distribution. Statistical analyzes were performed with SPSS 26 software. The conformity of the variables to the normal distribution was examined using analytical methods (Kolmogorov-Smirnov/ Shapiro-Wilk tests). Pearson's Chi-square test was used to compare categorical variables. The correlation between the antibody level and the measurement results of hemogram parameters and lymphocyte indicators was evaluated by Pearson's correlation analysis. The model was established by performing linear regression analysis with the variables correlated with the antibody level. Cases with a p value below 0.05 were considered statistically significant. The age range of the participants in the study was 22-69. The mean age was 45.5 ± 10.4 years. Antibodies against SARS-CoV-2 virus were detected by ELISA method in 65 (74.7%) of the healthcare professionals, while no antibodies were detected in 22 (25.3%) of them. Lymphocyte count (p= 0.002), CD3 count (p= 0.0004), CD4 count (p= 0.0001), CD3/CD19 ratio (p= 0.011), CD4 percentage (p= 0.004) in the antibody positive group was found to be significant. According to the level of correlation between antibody level and lymphocyte indicators, a statistically significant negative correlation was found in CD3, CD4, CD8 and CD19 positive lymphocytes, respectively, and the best correlation was observed in CD3 positive lymphocytes. The formula f (Antibody level)= y= 358002 -0.176 x CD3 + 0.469 x CD19 was created using the linear regression model. In the light of the data of this study, the central role of T and B cells in COVID-19 immunization emerges. The vaccine-related antibody level-related formula may be useful for healthcare professionals in patient follow-up. It is thought that conducting vaccine related immune response studies involving larger populations will contribute more to the literature.

The effects of lung involvement, clinical and laboratory parameters on outcome in elderly patients with coronavirus disease 2019.

We aimed to investigate the association of lung involvement and biochemical parameters with patients' demographic characteristics, and how this association effects the disease course and mortality in elderly patients diagnosed with coronavirus disease 2019 (COVID-19). Age, degree of pulmonary involvement, comorbidities, and biochemical parameters of 211 patients who were 60 years or older, diagnosed with COVID-19, and had lung involvement were analyzed. The effects of these parameters on ICU admission and mortality were investigated. Advanced age, severity of lung involvement, elevated D-dimer, ferritin, and fibrinogen levels, and a previous history ofchronic obstructive pulmonary disease (COPD)were significant for predicting ICU admission and mortality. Along with advanced age, both the severity of lung involvement and a history of COPD had major impact on mortality in the course of COVID-19.

Roles of certain biochemical and hematological parameters in predicting mortality and ICU admission in COVID-19 patients.

OBJECTIVE: In this study, we aimed to retrospectively analyze the roles of certain hematological and biochemical parameters in predicting mortality and intensive care unit admission in patients diagnosed with coronavirus disease 2019 (COVID-19). METHODS: We analyzed the complete blood count and biochemical parameters of 186 COVID-19 patients by using the polymerase chain reaction test. Whether these parameters can be used to predict intensive care unit admission and mortality in the COVID-19 patients was investigated. RESULTS: The complete blood count and biochemical parameters of COVID-19 patients and in those admitted to intensive care unit were compared. The red cell distribution width, ferritin, lactate dehydrogenase, D-dimer, C-reactive protein, prothrombin time, and creatinine levels were found to be the most significant parameters. We found that these parameters are significant for predicting not only intensive care unit admission, but also the mortality of the patients admitted to the intensive care unit. CONCLUSIONS: We determined that the most effective parameters to predict intensive care unit admission and mortality in COVID-19 patients are ferritin, lactate dehydrogenase, D-dimer, C-reactive protein, red cell distribution width, creatinine, and intensive care unit. Close monitoring of these parameters and early intervention in alterations are of vital importance.