Longitudinal Dynamics of Cellular Responses in Recovered COVID-19 Patients.

Safe and effective vaccines and therapeutics based on the understanding of antiviral immunity are urgently needed to end the COVID-19 pandemic. However, the understanding of these immune responses, especially cellular immune responses to SARS-CoV-2 infection, is limited. Here, we conducted a cohort study of COVID-19 patients who were followed and had blood collected to characterize the longitudinal dynamics of their cellular immune responses. Compared with healthy controls, the percentage of activation of SARS-CoV-2 S/N-specific T cells in recovered patients was significantly higher. And the activation percentage of S/N-specific CD8+ T cells in recovered patients was significantly higher than that of CD4+ T cells. Notably, SARS-CoV-2 specific T-cell responses were strongly biased toward the expression of Th1 cytokines, included the cytokines IFNγ, TNFα and IL2. Moreover, the secreted IFNγ and IL2 level in severe patients was higher than that in mild patients. Additionally, the number of IFNγ-secreting S-specific T cells in recovered patients were higher than that of N-specific T cells. Overall, the SARS-CoV-2 S/N-specific T-cell responses in recovered patients were strong, and virus-specific immunity was present until 14-16 weeks after symptom onset. Our work provides a basis for understanding the immune responses and pathogenesis of COVID-19. It also has implications for vaccine development and optimization and speeding up the licensing of the next generation of COVID-19 vaccines.

Abnormal Indexes of Liver and Kidney Injury Markers Predict Severity in COVID-19 Patients.

BACKGROUND: SARS-CoV-2 can damage not only the lungs but also the liver and kidney. Most critically ill patients with coronavirus disease 2019 (COVID-19) have liver and kidney dysfunction. We aim to investigate the levels of liver and kidney function indexes in mild and severe COVID-19 patients and their capability to predict the severity of the disease. METHODS: The characteristics and laboratory indexes were compared between patients with different conditions. We applied binary logistic regression to find the independent risk factors of severe patients. Receiver operating characteristic (ROC) analysis was used to predict the severity of COVID-19 using the liver and kidney function indexes. RESULTS: This study enrolled 266 COVID-19 patients, including 235 mild patients and 31 severe patients. Compared with mild patients, severe patients had lower albumin (ALB) and higher alanine aminotransferase (ALT), aspartate aminotransferase (AST), and urea nitrogen (BUN) (all p<0.001). Binary logistic regression analysis also identified ALB [OR=0.273 (0.079-0.947), p=0.041] and ALT [OR=2.680 (1.036-6.934), p=0.042] as independent factors of severe COVID-19 patients. Combining ALB, ALT, BUN, and LDH exhibited the area under ROC at 0.914, with a sensitivity of 86.7% and specificity of 83.0%. CONCLUSION: COVID-19 patients, especially severe patients, have damage to liver and kidney function. ALT, AST, LDH, and BUN could be independent factors for predicting the severity of COVID-19. Combining the ALB, ALT, BUN, and LDH could predict the transition from mild to severe in COVID-19 patients.

Comparative effectiveness of Lopinavir/Ritonavir-based regimens in COVID-19.

The coronavirus disease 2019 (COVID-19) is an epidemic disease caused by the Severe Acute Respiratory Syndrome Corona Virus 2 (SARS-CoV-2) and spreading throughout the world rapidly. Here we evaluated the efficacy of the Lopinavir/Ritonavir (LPV/r) and its combination with other drugs in the treatment of COVID-19. We included 170 confirmed COVID-19 patients who had been cured and discharged. Their antiviral therapies were LPV/r alone or combinations with interferon (IFN), Novaferon and Arbidol. We evaluated the medication efficacy by comparing the time of the negative nucleic acid conversion and the length of hospitalization mainly. The LPV/r + Novaferon [6.00 (4.00-8.00) and 7.50 (5.00-10.00) days] had shorter time of the negative nucleic acid conversion (P = .0036) and shorter time of hospitalization (P < .001) compared with LPV/r alone [9.00 (5.00-12.00) and 12.00 (11.00-15.00) days] and LPV/r + IFN [9.00 (7.25-11.00) and 12.00 (10.00-13.50) days]. On the contrary, LPV/r + IFN [9.00 (7.25-11.00) and 12.00 (10.00-13.50) days] had shorter time of the negative nucleic acid conversion (P = .031) and shorter time of hospitalization (P < .001) compared with LPV/r + IFN +Novaferon [10.00 (8.00-11.25) and 13.50 (11.50-17.00) days] and LPV/r + IFN +Arbidol [14.00 (9.75-19.00) and 19.50 (13.25-24.00) days]. In conclusion, the combination of LPV/r and Novaferon may have better efficacy against COVID-19. However, adding IFN based on LPV/r + Novaferon or adding Arbidol based on LPV/r + IFN may not improve the efficacy.

Severity Detection for the Coronavirus Disease 2019 (COVID-19) Patients Using a Machine Learning Model Based on the Blood and Urine Tests.

The recent outbreak of the coronavirus disease-2019 (COVID-19) caused serious challenges to the human society in China and across the world. COVID-19 induced pneumonia in human hosts and carried a highly inter-person contagiousness. The COVID-19 patients may carry severe symptoms, and some of them may even die of major organ failures. This study utilized the machine learning algorithms to build the COVID-19 severeness detection model. Support vector machine (SVM) demonstrated a promising detection accuracy after 32 features were detected to be significantly associated with the COVID-19 severeness. These 32 features were further screened for inter-feature redundancies. The final SVM model was trained using 28 features and achieved the overall accuracy 0.8148. This work may facilitate the risk estimation of whether the COVID-19 patients would develop the severe symptoms. The 28 COVID-19 severeness associated biomarkers may also be investigated for their underlining mechanisms how they were involved in the COVID-19 infections.

Epidemiologic and clinical characteristics of 42 deaths caused by SARS-CoV-2 infection in Wuhan, China: A retrospective study.

This study described the epidemiologic and clinical characteristics of patients who died from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, and pointed out the potential risk factors associated with fatal outcomes. Retrospective data from 42 death cases due to SARS-CoV-2 infection at Tongji Hospital Affiliated to Huazhong University of Science and Technology, Wuhan, China was analyzed. Demographics, clinical detection, laboratory findings, and treatments of the deceased were collected and analyzed. The average time between onset of symptoms and admission to the hospitals was 11 ± 5 days of hospitalization. Among the deceased, 60% were with co-morbidities. All of them were having fever and bilateral pneumonia on computed tomography, abnormal infection-related biomarkers, and renal impairment. Abnormal blood coagulation parameters that appeared in more than half of them, were consistent with disseminated intravascular coagulation. All of the patients were treated in the ICU. Based on the fact that SARS-CoV-2 infection carries a risk of mortality, we may infer a few older male patients with underlying comorbidities are likely to have the increased risk. Impaired consciousness level, markers of renal impairment and coagulation abnormalities may be poor prognostic factors.

Incidence of Adverse Drug Reactions in COVID-19 Patients in China: An Active Monitoring Study by Hospital Pharmacovigilance System.

To evaluate the incidence, type, and risk factors associated with adverse drug reactions (ADRs) among patients with coronavirus disease 2019 (COVID-19) by Hospital Pharmacovigilance System (CHPS). A retrospective analysis was performed on 217 patients with COVID-19 admitted to the First Hospital of Changsha in China, from January 17, 2020, to February 29, 2020. The active monitoring model in CHPS was used to detect ADR signals of the hospital information system. The risk factors for the ADRs were classified using the World Health Organization-Uppsala Monitoring Centre (WHO-UMC) system. Univariate and multivariate logistic regressions were carried out to analyze the risk factors of ADRs. Our results showed that the prevalence of ADRs was 37.8% in the patients, which was predominated by drug-induced gastrointestinal disorders and liver system disorders (23.0% vs. 13.8%). The ADR could be explained by the use of lopinavir/ ritonavir and umifenovir by 63.8% and 18.1%, respectively. There were 96.8% of ADRs that occurred within 14 days of hospitalization. Multivariable analysis showed that length of stay (odds ratio (OR): 2.02; 95% confidence interval (CI) 1.03-3.96; P = 0.04), number of drugs used in the hospital (OR: 3.17; 95% CI 1.60-6.27; P = 0.001) and underlying basic diseases (OR: 2.07; 95% CI 1.02-4.23; P = 0.04) were independent risk factor for ADRs in the patients. Together, the incidence of ADRs was significantly high during the treatment period. Moreover, the active monitoring of the CHPS system reflected ADRs during COVID-19 treatment in the real world, which provided reference for safe medication in the clinic.