An association between immune status and chest CT scores in COVID-19 patients

Development and external validation of a prognostic tool for nonsevere COVID-19 inpatients

To develop a machine learning model and nomogram to predict the probability of persistent virus shedding (PVS) in hospitalized patients with coronavirus disease 2019 (COVID-19), the clinical symptoms and signs, laboratory parameters, cytokines, and immune cell data of 429 patients with nonsevere COVID-19 were retrospectively reviewed. Two models were developed using the Akaike information criterion (AIC). The performance of these two models was analyzed and compared by the receiver operating characteristic (ROC) curve, calibration curve, net reclassification index (NRI), and integrated discrimination improvement (IDI). The final model included the following independent predictors of PVS: sex, C-reactive protein (CRP) level, interleukin-6 (IL-6) level, the neutrophil-lymphocyte ratio (NLR), monocyte count (MC), albumin (ALB) level, and serum potassium level. The model performed well in both the internal validation (corrected C-statistic = 0.748, corrected Brier score = 0.201) and external validation datasets (corrected C-statistic = 0.793, corrected Brier score = 0.190). The internal calibration was very good (corrected slope = 0.910). The model developed in this study showed high discriminant performance in predicting PVS in nonsevere COVID-19 patients. Because of the availability and accessibility of the model, the nomogram designed in this study could provide a useful prognostic tool for clinicians and medical decision-makers.

Follow-up study of anti-SARS-CoV-2 IgG antibody response in COVID-19 patients up to 6 months after infection

Introduction: The aim of the current study was to investigate the relationship between lung involvement of SARS-CoV-2 and antibody levels of COVID-19 patients 3 and 6 months from the disease. Methods: A total of 156 participants were divided into two groups, Group 1: lung involvement (LI)-positive and Group 2: LI-negative. Biochemical parameters and anti-SARS-CoV-2 IgG antibody levels were measured. Results: The results showed that mean levels of urea, LDH, CRP, ferritin, neutrophil count and D-dimer were significantly higher in the LI-positive group. In addition, mean antibody levels in the 3rd and 6th months were higher in the LI-positive group (p < 0.005). Discussion: High antibody levels in LI-positive patients correlated with some immunologic and biochemical parameters. Further studies should be performed to determine protective antibody levels against reinfection, how long protective titers last and the mechanisms by which COVID-19 symptoms, demographics and comorbidities may drive higher antibody levels.