A New Coronavirus Estimation Global Score for Predicting Mortality During Hospitalization in Patients with COVID-19.

Objective: Coronavirus disease 2019 (COVID-19) exists as a pandemic. Mortality during hospitalization is multifactorial, and there is urgent need for a risk stratification model to predict in-hospital death among COVID-19 patients. Here we aimed to construct a risk score system for early identification of COVID-19 patients at high probability of dying during in-hospital treatment. Methods: In this retrospective analysis, a total of 821 confirmed COVID-19 patients from 3 centers were assigned to developmental (n = 411, between January 14, 2020 and February 11, 2020) and validation (n = 410, between February 14, 2020 and March 13, 2020) groups. Based on demographic, symptomatic, and laboratory variables, a new Coronavirus estimation global (CORE-G) score for prediction of in-hospital death was established from the developmental group, and its performance was then evaluated in the validation group. Results: The CORE-G score consisted of 18 variables (5 demographics, 2 symptoms, and 11 laboratory measurements) with a sum of 69.5 points. Goodness-of-fit tests indicated that the model performed well in the developmental group (H = 3.210, P = 0.880), and it was well validated in the validation group (H = 6.948, P = 0.542). The areas under the receiver operating characteristic curves were 0.955 in the developmental group (sensitivity, 94.1%; specificity, 83.4%) and 0.937 in the validation group (sensitivity, 87.2%; specificity, 84.2%). The mortality rate was not significantly different between the developmental (n = 85,20.7%) and validation (n = 94, 22.9%, P = 0.608) groups. Conclusions: The CORE-G score provides an estimate of the risk of in-hospital death. This is the first step toward the clinical use of the CORE-G score for predicting outcome in COVID-19 patients.

Latent profiles of multi-dimensionality of self-compassion predict youth psychological adjustment outcomes during the COVID-19: A longitudinal mixture regression analysis.

The multi-dimensionality of self-compassion and its influence on college students' adjustments have not been widely examined during the COVID-19 pandemic. The current study aims to explore profiles of self-compassion dimensions in Chinese college students and examine the predictive effects of different profiles on students' adjustment outcomes. A longitudinal online survey of college students was conducted in mainland China. In May of 2020, college students (N = 1361) completed Neff's Self-Compassion Scale-Short Form during the home quarantine period. Six months after the baseline assessment, students (N = 717) reported their level of anxiety symptoms, depression symptoms, insomnia symptoms, complex post-traumatic stress (CPTSD) symptoms, post-traumatic growth (PTG), and positive youth development (PYD). A latent profile analysis was adopted to identify profiles of self-compassion dimensions. A longitudinal regression mixture model was used to examine the predictive effects of different self-compassion profiles on college students' adjustment outcomes. Three classes best characterized the self-compassion dimensions of college students: the compassionate group (54.1%), the uncompassionate group (38.6%), and the extremely uncompassionate group (7.3%). College students in the compassionate group scored significantly higher on positive adjustment indicators (PTG and PYD), and significantly lower on negative adjustment indicators (anxiety, depression, insomnia, and CPTSD symptoms) than students in the other two groups. College students in the uncompassionate group scored significantly lower on negative indicators, and higher on PYD scores than students in the extremely uncompassionate group, but did not differ in PTG levels from students in the extremely uncompassionate group. College students in the compassionate group adjusted best across groups. The limitations that using a composite score to represent the relative balance of self-compassion dimensions were highlighted. Intervention programs need to focus on improving the level of positive self-responses in college students.

Antiviral Abidol is Associated with the Reduction of In-Hospital Mortality in COVID-19 Patients.

OBJECTIVE: Coronavirus disease 2019 (COVID-19) is a global public health crisis. There are no specific antiviral agents for the treatment of SARS-CoV-2. Information regarding the effect of Abidol on in-hospital mortality is scarce. The present study aimed to evaluate the treatment effect of Abidol for patients with COVID-19 before and after propensity score matching (PSM). METHODS: This retrospective cohort study analyzed 1019 patients with confirmed COVID-19 in China from December 22, 2019 to March 13, 2020. Patients were divided to Abidol (200 mg, tid, 5-7 days, n = 788, 77.3%) and No-Abidol (n = 231, 22.7%) groups. The primary outcome was the mortality during hospitalization. RESULTS: Among 1019 COVID-19 patients, the age was (60.4 ±â€Š14.5) years. Abidol-treated patients, compared with No-Abidol-treated patients, had a shorter duration from onset of symptoms to admission, less frequent renal dysfunction, lower white blood cell counts (lymphocytes <0.8) and erythrocyte sending rate, lower interleukin-6, higher platelet counts and plasma IgG and oxygen saturation, and less frequent myocardial injury. The mortality during hospitalization before PSM was 17.9% in Abidol group and 34.6% in No-Abidol (hazard ratio (HR) = 2.610, 95% confident interval (CI): 1.980-3.440), all seen in severe and critical patients. After PSM, the in-hospital death was 13.6% in Abidol and 28.6% in No-Abidol group (HR = 2.728, 95% CI: 1.598-4.659). CONCLUSIONS: Abidol-treatment results in less in-hospital death for severe and critical patients with COVID-19. Further randomized study is warranted to confirm the findings from this study.

Willingness to receive future COVID-19 vaccines following the COVID-19 epidemic in Shanghai, China.

BACKGROUND: There are no pharmacological interventions currently available to prevent the transmission of SARS-CoV-2 or to treat COVID-19. The development of vaccines against COVID-19 is essential to contain the pandemic. we conducted a cross-sectional survey of Shanghai residents to understand residents' willingness to be vaccinated with any future COVID-19 vaccines and take measures to further improve vaccination coverage. METHODS: We conducted a cross-sectional survey using self-administered anonymous questionnaires from 1 July to 8 September 2020. The main outcome was willingness of participants, and any children or older individuals living with them, to receive future COVID-19 vaccines. Logistic regression analyses were used to explore potential factors associated with vaccination willingness. RESULTS: A total of 1071 participants were asked about their willingness to receive future COVID-19 vaccines, for themselves and at least 747 children and 375 older individuals (≥60 years old) living with them. The highest proportion of expected willingness to vaccinate was among participants (88.6%), followed by children (85.3%) and older individuals (84.0%). The main reasons for reluctance to vaccinate among 119 participants were doubts regarding vaccine safety (60.0%) and efficacy (28.8%). Participants with a self-reported history of influenza vaccination were more likely to accept COVID-19 vaccines for themselves [adjusted odds ratio (OR) = 1.83; 95% confidence interval (CI): 1.19-2.82], their children (adjusted OR = 2.08; 95%CI: 1.30-3.33), and older individuals in their household (adjusted OR = 2.12; 95%CI: 1.14-3.99). Participants with older individuals in their families were less willing to vaccinate themselves (adjusted OR = 0.59; 95%CI: 0.40-0.87) and their children (adjusted OR = 0.58; 95%CI: 0.38-0.89). CONCLUSIONS: Participants were more reluctant to accept COVID-19 vaccines for older individuals living with them. The presence of older individuals in the home also affected willingness of participants and their children to be vaccinated.

Impact of the coronavirus disease 2019 epidemic and a free influenza vaccine strategy on the willingness of residents to receive influenza vaccines in Shanghai, China.

The influenza vaccine is not included in China's national immunization program. Here, we assessed influenza vaccine coverage among Shanghai residents and estimated the impacts of the coronavirus disease 2019 (COVID-19) epidemic and a hypothetical free vaccine strategy on the willingness of participants to receive influenza vaccines. The coverage of influenza vaccines among Shanghai residents from 2015 to 2019 was 1.4% (range: 1%-2.4%). A total of 792 adult participants (aged 19-59 years) along with 821 children and 445 older individuals were included in the analysis. The willingness of participants to receive influenza vaccines reached 68.4% following the COVID-19 epidemic. Furthermore, if the vaccine was made available at no cost, 85.9% of participants were willing to be vaccinated. Our data indicated that influenza vaccine coverage is extremely low in Shanghai but that more than two-thirds of participants were willing to receive influenza vaccines following the COVID-19 epidemic. Making influenza vaccines available for free could further increase coverage.

Nanoscale Structural Characterization of Individual Viral Particles Using Atomic Force Microscopy Infrared Spectroscopy (AFM-IR) and Tip-Enhanced Raman Spectroscopy (TERS).

Viruses are infections species that infect a large spectrum of living systems. Although displaying a wide variety of shapes and sizes, they are all composed of nucleic acid encapsulated into a protein capsid. After virions enter the host cell, they replicate to produce multiple copies of themselves. They then lyse the host, releasing virions to infect new cells. The high proliferation rate of viruses is the underlying cause of their fast transmission among living species. Although many viruses are harmless, some of them are responsible for severe diseases such as AIDS, viral hepatitis, and flu. Traditionally, electron microscopy is used to identify and characterize viruses. This approach is time- and labor-consuming, which is problematic upon pandemic proliferation of previously unknown viruses, such as H1N1 and COVID-19. Herein, we demonstrate a novel diagnosis approach for label-free identification and structural characterization of individual viruses that is based on a combination of nanoscale Raman and infrared spectroscopy. Using atomic force microscopy-infrared (AFM-IR) spectroscopy, we were able to probe structural organization of the virions of Herpes Simplex Type 1 viruses and bacteriophage MS2. We also showed that tip-enhanced Raman spectroscopy (TERS) could be used to reveal protein secondary structure and amino acid composition of the virus surface. Our results show that AFM-IR and TERS provide different but complementary information about the structure of complex biological specimens. This structural information can be used for fast and reliable identification of viruses. This nanoscale bimodal imaging approach can be also used to investigate the origin of viral polymorphism and study mechanisms of virion assembly.