Increased occurrence of PTSD symptoms in adolescents with major depressive disorder soon after the start of the COVID-19 outbreak in China: a cross-sectional survey.

BACKGROUND: The Coronavirus Disease 2019 (COVID-19) pandemic continues to threaten the physical and mental health of people across the world. This study aimed to understand the psychological impact of this disease on adolescents with major depressive disorder (MDD) at 1 month after the start of the outbreak in China. METHODS: Using the Children's Impact of Event Scale (CRIES-13) questionnaire, we investigated the occurrence of posttraumatic stress disorder (PTSD) in two groups of adolescents: MDD patients who were in continuous antidepressant therapy and healthy controls. Total scores and factor subscores were compared between the two groups and subgroups stratified by sex and school grade. Logistic regression was used to identify variables associated with high total CRIES-13 scores. RESULTS: Compared to controls (n = 107), the MDD group (n = 90) had higher total CRIES-13 scores and a higher proportion with a total score ≥ 30. They also had a lower intrusion subscore and a higher arousal subscore. In the MDD group, males and females did not differ significantly in total CRIES-13 scores or factor subscores, but junior high school students had higher avoidance subscores than senior high school students. Logistic regression showed high total CRIES-13 scores to be associated with MDD and the experience of "flashbacks" or avoidance of traumatic memories associated with COVID-19. CONCLUSIONS: It is crucial to understand the psychological impact of COVID-19 on adolescents with MDD in China, especially females and junior high school students. Long-term monitoring of adolescents with a history of mental illness is required to further understand these impacts. TRIAL REGISTRATION: ChiCTR, ChiCTR2000033402 , Registered 31 May 2020.

Psychological impact and implementation of preventative measures in hemodialysis centers during the COVID-19 pandemic: a provincial questionnaire survey in China.

OBJECTIVES: This study investigated the psychological status of patients and staff, and the implementation of preventative measures in hemodialysis centers in Guangdong province, China, during the 2019 novel coronavirus disease (COVID-19) pandemic. METHODS: An electronic questionnaire survey was carried out anonymously between March 28 and April 3, 2020. All of the 516 hemodialysis centers registered in Guangdong province were invited to participate in the survey. The questionnaires were designed to investigate the psychological status of hemodialysis patients and general staff members (doctors, nurses, technicians, and other staff), and to address the implementation of preventative measures for administrators (directors or head nurses) of the hemodialysis centers. RESULTS: A total of 1782 patients, 3400 staff, and 420 administrators voluntarily participated in this survey. Patients living in rural areas reported a higher incidence of severe anxiety compared to those living in other areas (in rural areas, towns, and cities, the incidence rate was 17.0%, 9.0%, and 8.9%, respectively, P < 0.001). Medical staff were less likely to worry about being infected than non-medical staff (13.1% vs 30.3%, respectively, P < 0.001). With respect to the implementation of preventative measures, hemodialysis centers in general hospitals outperformed stand-alone blood purification centers, while tertiary hospitals outperformed hospitals of other levels. However, restrictions regarding the admission of non-resident patients were lower in tertiary hospitals than in other hospitals. In this situation, only one patient imported from Hubei province was diagnosed with COVID-19. CONCLUSIONS: COVID-19 did not significantly affect the psychological status of most patients and medical staff members. Due to the implementation of comprehensive preventative measures, there were no cluster outbreaks of COVID-19 in hemodialysis centers. This provincial-level survey may provide referential guidance for other countries and regions that are experiencing a similar pandemic.

Assisting scalable diagnosis automatically via CT images in the combat against COVID-19.

The pandemic of Coronavirus Disease 2019 (COVID-19) is causing enormous loss of life globally. Prompt case identification is critical. The reference method is the real-time reverse transcription PCR (RT-PCR) assay, whose limitations may curb its prompt large-scale application. COVID-19 manifests with chest computed tomography (CT) abnormalities, some even before the onset of symptoms. We tested the hypothesis that the application of deep learning (DL) to 3D CT images could help identify COVID-19 infections. Using data from 920 COVID-19 and 1,073 non-COVID-19 pneumonia patients, we developed a modified DenseNet-264 model, COVIDNet, to classify CT images to either class. When tested on an independent set of 233 COVID-19 and 289 non-COVID-19 pneumonia patients, COVIDNet achieved an accuracy rate of 94.3% and an area under the curve of 0.98. As of March 23, 2020, the COVIDNet system had been used 11,966 times with a sensitivity of 91.12% and a specificity of 88.50% in six hospitals with PCR confirmation. Application of DL to CT images may improve both efficiency and capacity of case detection and long-term surveillance.