Objective: To predict the in-hospital incidence of acute respiratory distress syndrome(ARDS) in COVID-19 patients by developing a predictive nomogram.Methods: Patients with COVID-19 admitted to Changsha Public Health ...Objective: To predict the in-hospital incidence of acute respiratory distress syndrome(ARDS) in COVID-19 patients by developing a predictive nomogram.Methods: Patients with COVID-19 admitted to Changsha Public Health Centre between 30 January 2020, and 22 February 2020 were enrolled in this study. Clinical characteristics and laboratory variables were analyzed and compared between patients with or without ARDS. Clinical characteristics and laboratory variables that were risk factors of ARDS were screened by the least absolute shrinkage and selection operator binary logistic regression. Based on risk factors, a prediction model was established by logistic regression and the final nomogram prognostic model was performed. The calibration curve was applied to evaluate the consistency between the nomogram and the ideal observation.Results: A total of 113 patients, including 99 non-ARDS patients and 14 ARDS patients were included in this study. Eight variables including hypertension, chronic obstructive pulmonary disease, cough, lactate dehydrogenase, creatine kinase, white blood count, body temperature, and heart rate were included in the model. The area under receiver operating characteristic curve, specificity, sensitivity, and accuracy of the full model were 0.969, 1.000, 0.857, and 0.875, respectively. The calibration curve also showed good agreement between the predicted and observed values in the model.Conclusions: The nomogram can be used to predict the in-hospital incidence of ARDS in COVID-19 patients.展开更多
Aims:During the COVID-19 epidemic,chest computed tomography(CT)has been highly recommended for screen-ing of patients with suspected COVID-19 because of an unclear contact history,overlapping clinical features,and an ...Aims:During the COVID-19 epidemic,chest computed tomography(CT)has been highly recommended for screen-ing of patients with suspected COVID-19 because of an unclear contact history,overlapping clinical features,and an overwhelmed health system.However,there has not been a full comparison of CT for diagnosis of heart failure or COVID-19 pneumonia.Methods:Patients with heart failure(n=23)or COVID-19 pneumonia(n=23)and one patient with both diseases were retrospectively enrolled.Clinical information and chest CT images were obtained and analyzed.Results:There was no difference in ground-glass opacity,consolidation,crazy paving pattern,the lobes affected,and septal thickening between heart failure and COVID-19 pneumonia.However,a less rounded morphology(4%vs.70%,P=0.00092),more peribronchovascular thickening(70%vs.35%,P=0.018)and fi ssural thickening(43%vs.4%,P=0.002),and less peripheral distribution(30%vs.87%,P=0.00085)were found in the heart failure group than in the COVID-19 group.Importantly,there were also more patients with upper pulmonary vein enlargement(61%vs.4%,P=0.00087),subpleural effusion(50%vs.0%,P=0.00058),and cardiac enlargement(61%vs.4%,P=0.00075)in the heart failure group than in the COVID-19 group.Besides,more fi brous lesions were found in the COVID-19 group,although there was no statistical difference(22%vs.4%,P=0.080).Conclusions:Although there is some overlap of CT features between heart failure and COVID-19,CT is still a useful tool for differentiating COVID-19 pneumonia.展开更多
基金Key Research and Development Program of Hunan Province (NO. 2020SK3004)Emergency Project of Prevention and Control for COVID-19 of Central South University (No. 160260005)。
文摘Objective: To predict the in-hospital incidence of acute respiratory distress syndrome(ARDS) in COVID-19 patients by developing a predictive nomogram.Methods: Patients with COVID-19 admitted to Changsha Public Health Centre between 30 January 2020, and 22 February 2020 were enrolled in this study. Clinical characteristics and laboratory variables were analyzed and compared between patients with or without ARDS. Clinical characteristics and laboratory variables that were risk factors of ARDS were screened by the least absolute shrinkage and selection operator binary logistic regression. Based on risk factors, a prediction model was established by logistic regression and the final nomogram prognostic model was performed. The calibration curve was applied to evaluate the consistency between the nomogram and the ideal observation.Results: A total of 113 patients, including 99 non-ARDS patients and 14 ARDS patients were included in this study. Eight variables including hypertension, chronic obstructive pulmonary disease, cough, lactate dehydrogenase, creatine kinase, white blood count, body temperature, and heart rate were included in the model. The area under receiver operating characteristic curve, specificity, sensitivity, and accuracy of the full model were 0.969, 1.000, 0.857, and 0.875, respectively. The calibration curve also showed good agreement between the predicted and observed values in the model.Conclusions: The nomogram can be used to predict the in-hospital incidence of ARDS in COVID-19 patients.
基金supported by a grant from the National Natural Science Foundation of China projects 81600248(to Z.Zhu)and 81670269(to S.Zhou).
文摘Aims:During the COVID-19 epidemic,chest computed tomography(CT)has been highly recommended for screen-ing of patients with suspected COVID-19 because of an unclear contact history,overlapping clinical features,and an overwhelmed health system.However,there has not been a full comparison of CT for diagnosis of heart failure or COVID-19 pneumonia.Methods:Patients with heart failure(n=23)or COVID-19 pneumonia(n=23)and one patient with both diseases were retrospectively enrolled.Clinical information and chest CT images were obtained and analyzed.Results:There was no difference in ground-glass opacity,consolidation,crazy paving pattern,the lobes affected,and septal thickening between heart failure and COVID-19 pneumonia.However,a less rounded morphology(4%vs.70%,P=0.00092),more peribronchovascular thickening(70%vs.35%,P=0.018)and fi ssural thickening(43%vs.4%,P=0.002),and less peripheral distribution(30%vs.87%,P=0.00085)were found in the heart failure group than in the COVID-19 group.Importantly,there were also more patients with upper pulmonary vein enlargement(61%vs.4%,P=0.00087),subpleural effusion(50%vs.0%,P=0.00058),and cardiac enlargement(61%vs.4%,P=0.00075)in the heart failure group than in the COVID-19 group.Besides,more fi brous lesions were found in the COVID-19 group,although there was no statistical difference(22%vs.4%,P=0.080).Conclusions:Although there is some overlap of CT features between heart failure and COVID-19,CT is still a useful tool for differentiating COVID-19 pneumonia.
