Prediction models for respiratory outcomes in patients with COVID-19: integration of quantitative computed tomography parameters, demographics, and laboratory features.

Background: We aimed to develop integrative machine-learning models using quantitative computed tomography (CT) parameters in addition to initial clinical features to predict the respiratory outcomes of coronavirus disease 2019 (COVID-19). Methods: This was a retrospective study involving 387 patients with COVID-19. Demographic, initial laboratory, and quantitative CT findings were used to develop predictive models of respiratory outcomes. High-attenuation area (HAA) (%) and consolidation (%) were defined as quantified percentages of the area with Hounsfield units between -600 and -250 and between -100 and 0, respectively. Respiratory outcomes were defined as the development of pneumonia, hypoxia, or respiratory failure. Multivariable logistic regression and random forest models were developed for each respiratory outcome. The performance of the logistic regression model was evaluated using the area under the receiver operating characteristic curve (AUC). The accuracy of the developed models was validated by 10-fold cross-validation. Results: A total of 195 (50.4%), 85 (22.0%), and 19 (4.9%) patients developed pneumonia, hypoxia, and respiratory failure, respectively. The mean patient age was 57.8 years, and 194 (50.1%) were female. In the multivariable analysis, vaccination status and levels of lactate dehydrogenase, C-reactive protein (CRP), and fibrinogen were independent predictors of pneumonia. The presence of hypertension, levels of lactate dehydrogenase and CRP, HAA (%), and consolidation (%) were selected as independent variables to predict hypoxia. For respiratory failure, the presence of diabetes, levels of aspartate aminotransferase, and CRP, and HAA (%) were selected. The AUCs of the prediction models for pneumonia, hypoxia, and respiratory failure were 0.904, 0.890, and 0.969, respectively. Using the feature selection in the random forest model, HAA (%) was ranked as one of the top 10 features predicting pneumonia and hypoxia and was first place for respiratory failure. The accuracies of the cross-validation of the random forest models using the top 10 features for pneumonia, hypoxia, and respiratory failure were 0.872, 0.878, and 0.945, respectively. Conclusions: Our prediction models that incorporated quantitative CT parameters into clinical and laboratory variables showed good performance with high accuracy.

Reactogenicity and Immunogenicity of the ChAdOx1 nCOV-19 Coronavirus Disease 2019 Vaccine in South Korean Healthcare Workers.

PURPOSE: The association between reactogenicity and immunogenicity of the ChAdOx1 nCOV-19 is controversial. We aimed to evaluate this association among South Korean healthcare workers (HCWs). MATERIALS AND METHODS: Participants received two doses of the ChAdOx1vaccine 12 weeks apart. Blood samples were tested for anti-severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) spike protein receptor binding domain antibodies about 2 months after the first and second doses using the Elecsys Anti-SARS-CoV-2 S assay kits. Adverse events were noted using an online self-reporting questionnaire. RESULTS: Among the 232 HCWs, pain (85.78% after the first dose vs. 58.62% after the second dose, p<0.001) was the most prominent local reaction, and myalgia or fatigue (84.05% vs. 53.02%, p<0.001) was the most prominent systemic reaction. The frequency of all adverse events was significantly reduced after the second dose. After the first dose, the anti-SARS-CoV-2 S showed significantly higher titer in the group with swelling, itching, fever, and nausea. Also, the anti-SARS-CoV-2 S titer significantly increased as the grade of fever (p=0.007) and duration of fever (p=0.026) increased; however, there was no significant correlation between immunogenicity and adverse event after the second dose. The group with pain after the first dose showed a greater increase in the anti-SARS-CoV-2 S difference between the second and first doses compared to the group without pain (542.2 U/mL vs. 363.8 U/mL, p=0.037). CONCLUSION: The frequency of adverse events occurring after the first dose of the ChAdOx1 was significantly reduced after the second dose. Interestingly, the elevation of anti-SARS-CoV-2 S titer was significantly increased in the group with pain after the first dose.

Effectiveness of Convalescent Plasma Therapy in Severe or Critically Ill COVID-19 Patients: A Retrospective Cohort Study.

PURPOSE: Coronavirus disease-2019 (COVID-19) is a novel respiratory infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); there are few specific treatments. Convalescent plasma (CP), donated by people who have recovered from COVID-19, is an investigational therapy for severe or critically ill patients with COVID-19. MATERIALS AND METHODS: This retrospective cohort study evaluated the effectiveness of CP therapy in patients with severe or life-threatening cases of COVID-19 at two hospitals in Seoul, Korea, between May and September 2020. Clinical outcomes were evaluated in 20 patients with CP therapy in a descriptive manner. Additionally, the changes in cycle threshold (Ct) values of 10 patients with CP therapy were compared to those of 10 controls who had the same (±0.8) initial Ct values but did not receive CP. RESULTS: Of the 20 patients (mean age 66.6 years), 18 received high-dose oxygen therapy using mechanical ventilators or high-flow nasal cannulas. Systemic steroids were administered to 19 patients who received CP. The neutralizing antibody titers of the administered CP were between 1:80 and 1:10240. There were two ABO-mismatched transfusions. The World Health Organization ordinal scale score and National Institutes of Health severity score improved in half of the patients within 14 days. Those who received CP showed a higher increase in Ct values at 24 h and 72 h after CP therapy compared to controls with similar initial Ct values (p=0.002). No transfusion-related side effects were observed. CONCLUSION: CP therapy may be a potential therapeutic option in severe or critically ill patients with COVID-19.

Patterns of viral clearance in the natural course of asymptomatic COVID-19: Comparison with symptomatic non-severe COVID-19.

OBJECTIVES: The aim of this study was to elucidate patterns of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) clearance in the natural course of asymptomatic coronavirus disease 2019 (COVID-19). METHODS: Consecutive patients with non-severe COVID-19 were included retrospectively. Asymptomatic patients with a normal body temperature and no evidence of pneumonia throughout the disease course were assigned to the asymptomatic group. The reverse transcription PCR (RT-PCR) assay was repeated every two to five days after the first follow-up RT-PCR assay. Negative conversion was defined as two consecutive negative RT-PCR assay results within a 24-h interval. Rebound of the cycle threshold (Ct) value was defined as negative from the single RT-PCR assay and positive from the following assay. RESULTS: Among a total of 396 patients identified (median age 42.5 years (interquartile range (IQR) 25.0-55.0 years), 35.6% male), 68 (17.2%) were assigned to the asymptomatic group and 328 (82.8%) to the symptomatic group. The time until negative conversion was significantly shorter in the asymptomatic group than in the symptomatic group: median 14.5 days (IQR 11.0-21.0 days) and 18.0 days (IQR 15.0-22.0 days), respectively (p = 0.001). Rebound of Ct values was observed in 78 patients (19.7%). CONCLUSIONS: Time until negative conversion is shorter in asymptomatic COVID-19 than in symptomatic COVID-19. Rebound of Ct values is not uncommon.