ABSTRACT
Objective: To analyze the risk factors of fatal outcome in patients with severe COVID-19. Method(s): The clinical characteristics of 107 patients with severe COVID-19 admitted in Renmin Hospital of Wuhan University from February 12 to March 12, 2020 were retrospectively analyzed. During the hospitalization 49 patients died (fatal group) and 58 patients survived (survival group). The clinical characteristics, baseline laboratory findings were analyzed using R and Python statistical software. The risk factors of fatal outcome in patients with severe COVID-19 were analyzed with multivariate logistic regression. Result(s): Univariate analysis showed that the two groups had statistically significant differences in age, clinical classification, dry cough, dyspnea and laboratory test indicators (P<0.05 or <0.01). The random forest model was used to rank the significance of the statistically significant variables in the univariate analysis, and the selected variables were included in the binary logistic regression model. After stepwise regression analysis, the patient's clinical type, age, neutrophil count, and the proportion of CD3 cells are independent risk factors for death in severe COVID-19 patients. Dry cough is an independent protective factor for the death of severe COVID-19 patients. Conclusion(s): COVID-19 patients with fatal outcome are more likely to have suppressed immune function, secondary infection and inflammatory factor storm. These factors may work together in severe patients, leading to intractable hypoxemia and multiple organ dysfunction and resulting in fatal outcome of patients. The study indicates that timely intervention and treatment measures against above factors may be effective to save the lives of patients with severe COVID-19.Copyright © 2020 by the Chinese Medical Association.
ABSTRACT
Objective: To analyze the risk factors of fatal outcome in patients with severe COVID-19. Method(s): The clinical characteristics of 107 patients with severe COVID-19 admitted in Renmin Hospital of Wuhan University from February 12 to March 12, 2020 were retrospectively analyzed. During the hospitalization 49 patients died (fatal group) and 58 patients survived (survival group). The clinical characteristics, baseline laboratory findings were analyzed using R and Python statistical software. The risk factors of fatal outcome in patients with severe COVID-19 were analyzed with multivariate logistic regression. Result(s): Univariate analysis showed that the two groups had statistically significant differences in age, clinical classification, dry cough, dyspnea and laboratory test indicators (P<0.05 or <0.01). The random forest model was used to rank the significance of the statistically significant variables in the univariate analysis, and the selected variables were included in the binary logistic regression model. After stepwise regression analysis, the patient's clinical type, age, neutrophil count, and the proportion of CD3 cells are independent risk factors for death in severe COVID-19 patients. Dry cough is an independent protective factor for the death of severe COVID-19 patients. Conclusion(s): COVID-19 patients with fatal outcome are more likely to have suppressed immune function, secondary infection and inflammatory factor storm. These factors may work together in severe patients, leading to intractable hypoxemia and multiple organ dysfunction and resulting in fatal outcome of patients. The study indicates that timely intervention and treatment measures against above factors may be effective to save the lives of patients with severe COVID-19.Copyright © 2020 by the Chinese Medical Association.
ABSTRACT
Objective: To analyze the risk factors of fatal outcome in patients with severe COVID-19. Method(s): The clinical characteristics of 107 patients with severe COVID-19 admitted in Renmin Hospital of Wuhan University from February 12 to March 12, 2020 were retrospectively analyzed. During the hospitalization 49 patients died (fatal group) and 58 patients survived (survival group). The clinical characteristics, baseline laboratory findings were analyzed using R and Python statistical software. The risk factors of fatal outcome in patients with severe COVID-19 were analyzed with multivariate logistic regression. Result(s): Univariate analysis showed that the two groups had statistically significant differences in age, clinical classification, dry cough, dyspnea and laboratory test indicators (P<0.05 or <0.01). The random forest model was used to rank the significance of the statistically significant variables in the univariate analysis, and the selected variables were included in the binary logistic regression model. After stepwise regression analysis, the patient's clinical type, age, neutrophil count, and the proportion of CD3 cells are independent risk factors for death in severe COVID-19 patients. Dry cough is an independent protective factor for the death of severe COVID-19 patients. Conclusion(s): COVID-19 patients with fatal outcome are more likely to have suppressed immune function, secondary infection and inflammatory factor storm. These factors may work together in severe patients, leading to intractable hypoxemia and multiple organ dysfunction and resulting in fatal outcome of patients. The study indicates that timely intervention and treatment measures against above factors may be effective to save the lives of patients with severe COVID-19.Copyright © 2020 by the Chinese Medical Association.
ABSTRACT
During the COVID-19 pandemic, wearing masks in public spaces has become a protective strategy. Field tests and questionnaire surveys were carried out at a university library in Guangzhou, China, during June 2021 and January 2022. The indoor environmental parameters were observed, thermal sensation votes of students on various environmental parameters were collected, symptoms of students wearing masks were quantified, and the appropriate amount of time to wear masks was established. To identify acceptable and comfortable temperature ranges, the relationship between thermal sensation and thermal index was investigated. During summer and winter, people wearing masks are symptomatic for a certain duration. The most frequently voted symptom was facial heat (62.7 % and 54.6 % during summer and winter, respectively), followed by dyspnea. During summer, more than 80 % of the participants subjects were uncomfortable and showed some symptoms after wearing masks for more than 2 h (3 h during winter). In the summer air conditioning environment in Guangzhou, the neutral Top was 26.4 °C, and the comfortable Top range was 25.1–27.7 °C. Under the natural ventilation environment in winter, the neutral Top was 20.5 °C, and the comfortable Top range was 18.5–22.5 °C. This study may provide guidance for indoor office work and learning to wear masks in Guangzhou. © 2022 Elsevier Ltd
ABSTRACT
Objective: To evaluate the value of improved pulmonary ultrasonography in the follow-up assessment of lung damage in patients who recovered from corona virus disease 2019(COVID-19). Methods: Twenty-two patients who were cured of COVID-19 in Quanzhou First Hospital from January to May 2020 were randomly selected and divided into 7 mild cases, 12 moderate cases and 3 severe cases according to the first high-resolution CT (HRCT) at admission. Six months after recovery, modified lung ultrasonography and HRCT were used prospectively to assess the lung damage and evaluate the correlation and consistency between the two techniques. Results: ①There were significant differences in lung damage between the mild group and the moderate group, severe group (all P<0.05), while there was no significant difference between the moderate group and severe group (P>0.05). ②There was good consistency between the improved lung ultrasound examination and HRCT (Kappa=0.776, P<0.001). ③There was a positive correlation between the score of improved pulmonary ultrasound examination and HRCT Warrick score (r=0.755, P<0.001). Conclusions: Improved pulmonary ultrasonography can be used as a priority in the evaluation of pulmonary damage follow-up in patients with COVID-19 recovery, reducing the use of CT, and providing favorable evidence for further clinical management. © 2021 Chinese Medical Association
ABSTRACT
Objective: To analyze the risk factors of fatal outcome in patients with severe COVID-19. Methods: The clinical characteristics of 107 patients with severe COVID-19 admitted in Renmin Hospital of Wuhan University from February 12 to March 12, 2020 were retrospectively analyzed. During the hospitalization 49 patients died (fatal group) and 58 patients survived (survival group). The clinical characteristics, baseline laboratory findings were analyzed using R and Python statistical software. The risk factors of fatal outcome in patients with severe COVID-19 were analyzed with multivariate logistic regression. Results: Univariate analysis showed that the two groups had statistically significant differences in age, clinical classification, dry cough, dyspnea and laboratory test indicators (P<0.05 or <0.01). The random forest model was used to rank the significance of the statistically significant variables in the univariate analysis, and the selected variables were included in the binary logistic regression model. After stepwise regression analysis, the patient's clinical type, age, neutrophil count, and the proportion of CD3 cells are independent risk factors for death in severe COVID-19 patients. Dry cough is an independent protective factor for the death of severe COVID-19 patients. Conclusion: COVID-19 patients with fatal outcome are more likely to have suppressed immune function, secondary infection and inflammatory factor storm. These factors may work together in severe patients, leading to intractable hypoxemia and multiple organ dysfunction and resulting in fatal outcome of patients. The study indicates that timely intervention and treatment measures against above factors may be effective to save the lives of patients with severe COVID-19. Copyright © 2020 by the Chinese Medical Association.