ABSTRACT
COVID-19 is a kind of pneumonia with new coronavirus infection, and the risk of death in COVID-19 patients with diabetes is four times higher than that in healthy people. It is unclear whether there is a difference in chest CT images between type 2 diabetes mellitus (T2DM) and non-diabetes mellitus (NDM) COVID-19 patients. The aim of this study was to investigate the differences in chest CT images between T2DM and NDM patients with COVID-19 based on a quantitative method of artificial intelligence. A total of 62 patients with COVID-19 pneumonia were retrospectively enrolled and divided into group A (T2DM COVID-19 pneumonia group, n = 15) and group B (NDM COVID-19 pneumonia group, n = 47). The clinical and laboratory examination information of the two groups was collected. Quantitative features (volume of consolidation shadows and ground glass shadows, proportion of consolidation shadow (or ground glass shadow) to lobe volume, total volume, total proportion, and number) of chest spiral CT images were extracted using Dr. Wise @Pneumonia software. The results showed that among the 26 CT image features, the total volume and proportion of bilateral pulmonary consolidation shadow in group A were larger than those in group B (P=0.031 and 0.019, respectively); there was no significant difference in the total volume and proportion of bilateral pulmonary ground glass density shadow between the two groups (P > 0.05). In group A, the blood glucose level was correlated with the volume of consolidation shadow and the proportion of consolidation shadow to right middle lobe volume, and higher than those patients in group B. In conclusion, the inflammatory exudation in the lung of COVID-19 patients with diabetes is more serious than that of patients without diabetes based on the quantitative method of artificial intelligence. Moreover, the blood glucose level is positively correlated with pulmonary inflammatory exudation in COVID-19 patients.
ABSTRACT
Nurses' work-related fatigue has been recognized as a threat to nurse health and patient safety. The aim of this study was to assess the prevalence of fatigue among first-line nurses combating with COVID-19 in Wuhan, China, and to analyze its influencing factors on fatigue. A multi-center, descriptive, cross-sectional design with a convenience sample was used. The statistical population consisted of the first-line nurses in 7 tertiary general hospitals from March 3, 2020 to March 10, 2020 in Wuhan of China. A total of 2667 samples from 2768 contacted participants completed the investgation, with a response rate of 96.35%. Social-demographic questionnaire, work-related questionnaire, Fatigue Scale-14, Generalized Anxiety Disorder-7, Patient Health Questionnaire-9, and Chinese Perceived Stress Scale were used to conduct online survey. The descriptive statistic of nurses' social-demographic characteristics was conducted, and the related variables of work, anxiety, depression, perceived stress and fatigue were analyzed by t-tests, nonparametric test and Pearson's correlation analysis. The significant factors which resulted in nurses' fatigue were further analyzed by multiple linear regression analysis. The median score for the first-line nurses' fatigue in Wuhan was 4 (2, 8). The median score of physical and mental fatigue of them was 3 (1, 6) and 1 (0, 3) respectively. According to the scoring criteria, 35.06% nurses (n=935) of all participants were in the fatigue status, their median score of fatigue was 10 (8, 11), and the median score of physical and mental fatigue of them was 7 (5, 8) and 3 (2, 4) respectively. Multiple linear regression analysis revealed the participants in the risk groups of anxiety, depression and perceived stress had higher scores on physical and mental fatigue and the statistically significant positive correlation was observed between the variables and nurses' fatigue, the frequency of exercise and nurses' fatigue had a statistically significant negative correlation, and average daily working hours had a significantly positive correlation with nurses' fatigue, and the frequency of weekly night shift had a low positive correlation with nurses' fatigue (P<0.01). There was a moderate level of fatigue among the first-line nurses fighting against COVID-19 pandemic in Wuhan, China. Government and health authorities need to formulate and take effective intervention strategies according to the relevant risk factors, and undertake preventive measures aimed at reducing health hazards due to increased work-related fatigue among first-line nurses, and to enhance their health status and provide a safe occupational environment worldwide. Promoting both medical and nursing safety while combating with the pandemic currently is warranted.