Prediction Model of hospitalization time of COVID-19 patients based on Gradient Boosted Regression Trees.

When an outbreak of COVID-19 occurs, it will cause a shortage of medical resources and the surge of demand for hospital beds. Predicting the length of stay (LOS) of COVID-19 patients is helpful to the overall coordination of hospital management and improves the utilization rate of medical resources. The purpose of this paper is to predict LOS for patients with COVID-19, so as to provide hospital management with auxiliary decision-making of medical resource scheduling. We collected the data of 166 COVID-19 patients in a hospital in Xinjiang from July 19, 2020, to August 26, 2020, and carried out a retrospective study. The results showed that the median LOS was 17.0 days, and the average of LOS was 18.06 days. Demographic data and clinical indicators were included as predictive variables to construct a model for predicting the LOS using gradient boosted regression trees (GBRT). The MSE, MAE and MAPE of the model are 23.84, 4.12 and 0.76 respectively. The importance of all the variables involved in the prediction of the model was analyzed, and the clinical indexes creatine kinase-MB (CK-MB), C-reactive protein (CRP), creatine kinase (CK), white blood cell count (WBC) and the age of patients had a higher contribution to the LOS. We found our GBRT model can accurately predict the LOS of COVID-19 patients, which will provide good assistant decision-making for medical management.

COVID-induced 3 weeks' treatment delay may exacerbate breast cancer patient's psychological symptoms.

The delayed access to cancer treatment due to the outbreak of COVID-19 pandemic posed a unique challenge to breast cancer patients and caused a significant level of mental distress among them. In the current research, we examined the psychological impacts of COVID on a subpopulation of breast cancer patients from a hospital in Shaanxi province of China using Symptom Checklist-90-R (SCL-90-R). Participants were 195 breast cancer patients at the outpatient clinic of Xijing hospital, Xi'an, Shaanxi Province, China. We found that a treatment delay of more than 3 weeks may exacerbate breast cancer patients' psychological symptoms, such as somatization, obsessive-compulsive disorder, interpersonal sensitivity, depression, hostility, phobic anxiety, paranoid ideation, and psychoticism, whereas a short-term delay of less than 3 weeks is less likely to have a significant effect on one's mental well-being. Additionally, breast cancer survivors, especially those at more advance stages, tend to experience more elevated psychological symptoms with longer treatment delay, and whose treatments continues to be delayed reported stronger psychological symptoms than individuals whose treatment are resumed, regardless of treatment type.

Prevalence and Associated Factors of PTSD Symptoms After the COVID-19 Epidemic Outbreak in an Online Survey in China: The Age and Gender Differences Matter.

Introduction: The COVID-19 is a highly contagious disease belonging to the family of coronaviruses which can affect a great deal of people shortly. As a devastating event in the world, many people suffer the PTSD from this severe disease. The aim of study is to explore the prevalence and severity of post-traumatic stress disorder (PTSD) symptoms, and discuss the possible factors among the general public in China after the COVID-19 epidemic outbreak. Methods: This is a cross-sectional study. We used the self-designed demographic questionnaire and the Posttraumatic Stress Checklist-Civilian Version (PCL-C) of Chinese version as our screening tools to investigate 4872 subjects living in the communities in China from Nov. 8th, 2020 to Dec. 8th, 2020. Results: Finally, we received 3705 effective respondents. The response rates of the questionnaire can reach 76.97 percentage. Peculiarly, the prevalence of PTSD mild and severe symptoms after the COVID-19 epidemic outbreak was 53.2%. Mild PTSD symptoms accounted for 24.9%, and severe PTSD symptoms (scores above 38) accounted for 28.3%. PCL-C mean scores were 41.4±14.7. The females accounted for 67.7% of the total samples. Participants' mean age was 30.5±11.2 years old. The PCL-C gross scores of females were all higher than males in four subject groups. Meantime, gender and age made differences not only in total PCL-C points but also in the four aspects of PCL-C (P<0.001). The middle-aged group (ages from 45 to 60) got the lowest scores among the four groups. Conclusion: COVID-19 brought tremendous psychological pressure on the public in many ways, including people's work, social contact, study, and daily life. Results of our research discover that symptoms of the PTSD are severe, including the re-experiencing, avoidance/numbing, flashbacks, and hyper-arousal. Actions should be taken at society level to prevent and protect individuals from PTSD suffering. Special attention should be paid to females and young people. Further studies should be conducted to explore the dynamic and other risk and protection factors to prevent PTSD.

Semiquantitative lung ultrasound scores in the evaluation and follow-up of critically ill patients with COVID-19: a single-center study.

RATIONALE AND OBJECTIVES: Chest CT is not suitable for critically ill patients with COVID-19 and lung ultrasound (LUS) may play an important role for these patients. In this study, we summarized the findings of LUS and explore the value of semiquantitative LUS scores in evaluation and follow-up of COVID-19 pneumonia. MATERIALS AND METHODS: Retrospectively studied the LUS and chest CT imaging of 128 critically ill patients with COVID-19. The imaging data were reviewed to acquire the LUS and CT scores. The correlation between LUS scores and CT scores were made to evaluate the accuracy of LUS. A cut-off point of LUS score was calculated to distinguish critical-type patients from severe-type patients. LUS follow-up of 72 patients were compared with the gold standard chest CT. RESULTS: The most common LUS features of COVID-19 pneumonia were crowded or coalescent B-lines with multifocal small consolidations in multi-zone. The mean LUS score was 8.1 points in severe-type patients and 15.7 points in critical-type patients (P<0.05). The correlation between LUS scores and CT scores was high (r=0.891, p<0.01) and it was higher in critical-type patients than that in severe-type patients. The LUS score higher than 10.5 points had a 97.4% sensitivity and 75.0% specificity to distinguish critical-type patients. The consistency of LUS and chest CT in follow-up was 0.596, with higher consistency in diagnosis of lesion progression (Kappa values was 0.774). CONCLUSION: Our scoring system provides a more quantitative use of LUS findings and accurate evaluation of lung damage for critically ill patients with COVID-19.