Development of a nomogram to assess the impact of the myocardial injury on the prognosis of COVID-19 patients.

Coronavirus disease 2019 (COVID-19) has been spreading worldwide. Many COVID-19 patients were accompanied by myocardial injury during the course of the disease. To evaluate the association of cardiac injury with clinical outcomes in COVID-19 patients, we recruited 261 COVID-19 cases admitted to Tongji Hospital of Huazhong University of Science and Technology in this study. Compared with patients without myocardial injury, those with myocardial injury were older, with shorter hospital stays and lower survival rates. They also had higher levels of inflammatory biomarkers (Interleukin-6,8,10 and C-reactive protein), coagulation biomarkers, liver and kidney function markers. Kaplan-Meier analysis demonstrated that patients with myocardial injury had a higher mortality rate. The multivariate Cox regression model and the nomogram revealed that myocardial injury, co-morbidity, and abnormal procalcitonin (PCT) levels were independent risk factors of the mortality of COVID-19 patients. The linear correlation analysis and the ROC curve suggested a predictive value of the neutrophil-lymphocyte ratio (NLR) in cardiac injury. Summarily, myocardial injury in COVID-19 patients is associated with a higher mortality risk. Attention should be paid to monitoring myocardial injury in patients with significantly elevated myocardial markers and NLR at admission.

Two novel nomograms based on inflammatory cytokines or lymphocyte subsets to differentially diagnose severe or critical and Non-Severe COVID-19.

We intend to evaluate the differences of the clinical characteristics, cytokine profiles and immunological features in patients with different severity of COVID-19, and to develop novel nomograms based on inflammatory cytokines or lymphocyte subsets for the differential diagnostics for severe or critical and non-severe COVID-19 patients. We retrospectively studied 254 COVID-19 patients, 90 of whom were severe or critical patients and 164 were non-severe patients. Severe or critical patients had significantly higher levels of inflammatory cytokines than non-severe patients as well as lower levels of lymphocyte subsets. Significantly positive correlations between cytokine profiles were observed, while they were all significantly negatively correlated with lymphocyte subsets. Two effective nomograms were developed according to two multivariable logistic regression cox models based on inflammatory cytokine profiles and lymphocyte subsets separately. The areas under the receiver operating characteristics of two nomograms were 0.834 (95% CI: 0.779-0.888) and 0.841 (95% CI: 0.756-0.925). The bootstrapped-concordance indexes of two nomograms were 0.834 and 0.841 in training set, and 0.860 and 0.852 in validation set. Calibration curves and decision curve analyses demonstrated that the nomograms were well calibrated and had significantly more clinical net benefits. Our novel nomograms can accurately predict disease severity of COVID-19, which may facilitate the identification of severe or critical patients and assist physicians in making optimized treatment suggestions.

A Retrospective Study of 268 Patients with SARS-CoV-2 Infection to Evaluate the Association Between Blood Glucose and Severity of COVID-19 Pneumonia and Patient Mortality.

BACKGROUND Diabetes is one of the most commonly reported comorbidities among patients infected with SARS-CoV-2. This retrospective study of patients with SARS-CoV-2 infection was conducted to evaluate the association between blood glucose levels and the severity of COVID-19 pneumonia and patient mortality. MATERIAL AND METHODS A total of 268 patients with confirmed SARS-CoV-2 infection were included in this retrospective study. We obtained demographic characteristics, clinical symptoms, laboratory data, and survival information from patients' electronic medical records. Blood glucose was measured on admission to the hospital. Comorbidities, including hypertension, diabetes, chronic kidney disease, chronic liver disease, chronic obstructive pulmonary disease, and cardiovascular disease, were collected by self-reported medical history. RESULTS Significantly higher risks of severe COVID-19 were found in patients with blood glucose levels ranging from 5.53 to 7.27 mmol/L (odds ratio [OR], 3.98; 95% confidence interval [CI], 1.81-8.75) and in patients with blood glucose ≥7.27 mmol/L (OR, 12.10; 95% CI, 5.53-26.48) than in those with blood glucose <5.53 mmol/L. There was a trend toward better survival in patients with blood glucose <5.53 mmol/L than in patients with blood glucose from 5.53 to 7.27 mmol/L (hazard ratio [HR], 6.34; 95% CI, 1.45-27.71) and ≥7.27 mmol/L (HR, 19.37; 95% CI, 4.68-80.17). Estimated 10-day overall survival rates were 96.8%, 90.6%, and 69.3% in patients with blood glucose <5.53 mmol/L, 5.53 to 7.27 mmol/L, and ³7.27 mmol/L, respectively. CONCLUSIONS Hyperglycemia was association with severity of COVID-19 pneumonia and with increased patient mortality. These findings support the need for blood glucose monitoring and control of hyperglycemia in patients with COVID-19 pneumonia.

Peripheral Inflammatory Cytokines and Lymphocyte Subset Features of Deceased COVID-19 Patients.

OBJECTIVE: To compare the difference of inflammatory cytokines and lymphocyte subsets between deceased patients and survivors with COVID-19. METHODS: This retrospective study included 254 confirmed patients from 10 January to 11 March, 2020, at Tongji Hospital of Wuhan, China. Laboratory and immunologic features were collected and analyzed, and the main outcomes focused on inflammatory cytokines and lymphocyte subsets. RESULTS: A trend of markedly higher levels of inflammatory cytokines as well as lower lymphocyte subset levels in deceased patients was observed compared with survivors. ROC curve analyses indicated that inflammatory cytokines and the decrease levels of T cell, Th (helper T cells) cell, Ts (suppressor T cells) cell, B cell, and NK cell along with Th/Ts ratio increase could be used to predict the death of COVID-19. Multivariate analyses showed that higher levels of IL-6, IL-8, and IL-10 remained significantly correlated with shorter survival time and that the amount of Ts cells was negatively associated with the possibility of death in COVID-19 patients. In conclusion, SARS-CoV-2 would cause lymphopenia and result in decreased lymphocyte subset cells, particularly in Ts cell counts, which further induces hyperinflammatory response and cytokine storm. IL-6, IL-8, IL-10, and Ts cell might be independent predictors for the poor outcome of COVID-19.