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Backgrounds: The COVID-19 pandemic has brought an unprecedented healthy crisis to people worldwide. It is crucial to assess the psychological status of non-frontline nurses. More attention to the mental and physical health of non-frontline nurses during a public health emergency is necessary for a full understanding of the implications. Therefore, this study aims to investigate the factors that influence the acute stress reaction of non-frontline pediatric nurses during the COVID-19 pandemic. Methods: This study aimed to explore factors associated with acute stress reactions of non-frontline pediatric nurses in Hunan province during the COVID-19 pandemic. This was a cross-sectional design. Five hundred eighteen pediatric nurses from Hunan province, China, completed the Stanford Acute Stress Reaction Questionnaire (SASRQ), Depression Anxiety Stress Scales-21 (DASS-21), and Job Withdrawal Behavior Scales (JWB). Multiple linear regression analyses and Pearson's correlation were used to analyze the results. Results: The mean scores of DASS-21, JWB, SASRQ were 1.443 ± 0.500, 1.601 ± 0.544, and 1.858 ± 0.805, respectively. Stress, anxiety, depression (three sub-dimensions of DASS-21), JWB, monthly income and department were the major predictive factors for SASRQ (Adjusted R2 = 0.579, p < 0.001). Pearson's correlation showed that the mean score of SASRQ was positively correlated with JWB, DASS-21, and all its dimensions (p < 0.01). Conclusion: The study indicated that the SASRQ was greater with higher levels of DASS-21 and JWB. It revealed an acute stress reaction in non-frontline pediatric nurses and recommends more focus on the factors influencing the SASRQ.
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Background Human migration is one of the driving forces for amplifying localized infectious disease outbreaks into widespread epidemics. During the outbreak of COVID-19 in China, the travels of the population from Wuhan have furthered the spread of the virus as the period coincided with the world's largest population movement to celebrate the Chinese New Year. Methods We have collected and made public an anonymous and aggregated mobility dataset extracted from mobile phones at the national level, describing the outflows of population travel from Wuhan. We evaluated the correlation between population movements and the virus spread by the dates when the number of diagnosed cases was documented. Results From Jan 1 to Jan 22 of 2020, a total of 20.2 million movements of at-risk population occurred from Wuhan to other regions in China. A large proportion of these movements occurred within Hubei province (84.5%), and a substantial increase of travels was observed even before the beginning of the official Chinese Spring Festival Travel. The outbound flows from Wuhan before the lockdown were found strongly correlated with the number of diagnosed cases in the destination cities (log-transformed). Conclusions The regions with the highest volume of receiving at-risk populations were identified. The movements of the at-risk population were strongly associated with the virus spread. These results together with province-by-province reports have been provided to governmental authorities to aid policy decisions at both the state and provincial levels. We believe that the effort in making this data available is extremely important for COVID-19 modelling and prediction.
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We present a case report of successful treatment with nirmatrelvir/ritonavir (Paxlvoid) for a severe aplastic anemia child with COVID-19, cytopenia, and mixed chimerism of donor hematopoietic cells at 3 months after allogeneic hematopoietic stem cell transplantation. After the 5-day entire course of treatment, the clinical symptoms were relieved, cycle threshold values of ORF1a/b and N genes increased from 22.60 and 22.15 to 34.52 and 33.84, respectively, and the peripheral blood counts gradually recovered without graft failure. Nirmatrelvir/ritonavir can effectively inhibit the replication of SARS-CoV-2 without any significant adverse effects.
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Recently, with the large-scale outbreak of the global financial crisis and public safety incidents (such as COVID-19), high-performance computing has been widely applied to risk prediction, vaccine development, and other fields. In scenarios where high-performance computing infrastructure responds to the instantaneous explosion of computing demands, a crucial issue is to provide large-scale flexible allocation and adjustment of computing capability by rapidly constructing computing clusters. Existing large-scale computing cluster deployment solutions usually utilize source code deployment or other deployment tools. The great challenge of existing deployment methods is to reduce excessive image distribution time and refrain from configuration defects. In this article, we design an intelligent distributed registry deployment (IDRD) architecture based on the OpenStack cloud platform, which adaptively places distributed image repositories using the containerized deployment of multiple registries. We propose a server load priority algorithm to solve multiple registries placement problems in IDRD. Furthermore, we devise a clustering algorithm based on demand density that can optimize the global performance of IDRD and improve large-scale cluster load balancing capabilities, which has been implemented in the TianHe Supercomputing environment. Extensive experimental results demonstrate that IDRD can effectively reduce [Formula Omitted]-[Formula Omitted] of the distribution time of component images and significantly improve the efficiency of large-scale cluster deployment.
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The immunological effectiveness of SARS-CoV-2 mRNA vaccines in lung transplant (LT) recipients is largely unknown. Thus, we assessed the effect of Pfizer-BioNTech and Moderna mRNA vaccine's two-dose (2D) regimen on humoral responses in immunocompromised lung transplant (LT) recipients. About 25% (18/73) of SARS-CoV-2 uninfected-LT patients generated positive spike-IgG response following 2D of vaccines, with 36% (9/25) in the Moderna cohort and only 19% (9/48) in the Pfizer cohort. 2D in LT patients elicited significantly lesser median IgGSP response (1.7 AU/mL, 95% CI: 0.6-7.5 AU/mL) compared to non-transplanted, uninfected naive subjects (14209 AU/mL, 95% CI: 11261-18836 AU/mL) (p<0.0001). In LT patients, Moderna-evoked seropositivity trend was higher by 23-fold than Pfizer. 2D COVID-19 vaccination elicits a dampened serological response in LT patients. Whether assessing other arms of host immunity combined with higher vaccine dose can better capture and elicit improved immunogenicity in this immunocompromised population warrants investigation.
Subject(s)
COVID-19ABSTRACT
Background: A great number of studies have explored the association between frailty and mortality among COVID-19 patients, suggesting inconsistent results. The aim of this meta-analysis was to synthesize the evidence on this issue. MethodsThree databases, including PubMed, Embase, and Cochrane Library from inception to 20th October, 2020 were conducted to search for relevant literature. The Newcastle–Ottawa Scale (NOS) was used to assess quality bias, and STATA was employed to pool the effect size. Additionally, potential publication bias and sensitivity analysis was performed.ResultsThere are 11 studies that were included, with a total of 22105 COVID-19 patients for quantitative analysis. Overall, the pooled prevalence of frailty was 51% (95%CI:42%-60%). Patients infected with COVID-19 with frailty had an increased risk of mortality, compared to those without frailty, and the pooled HR was 2.27 (95%CI:1.79-2.89). In addition, subgroup analysis based on population showed that the pooled HR for hospitalized patients and nursing home residents was 2.24 (95%CI:1.74-2.89) and 2.95 (95%CI:1.19-7.32), respectively. Subgroup analysis using the frailty assessment tool indicated that this association still existed when using the clinical frailty scale (CFS)(HR=2.41;95%CI:1.60-3.62), frailty index(HR=2.95;95%CI:1.19-7.32), hospital frailty risk score (HR=1.96;95%CI:1.79-2.15) and palliative performance scale (HR= 2.89;95%CI:1.42-5.87). ConclusionOur study indicates that frailty was an independent predictor for mortality among patients with COVID-19. Thus, frailty could be a prognostic factor for clinicians to stratify high-risk groups, and remind doctors and nurses to perform early screening and corresponding interventions urgently needed to reduce mortality rates in patients infected by SARS-CoV-2.
Subject(s)
COVID-19 , Newcastle DiseaseABSTRACT
Background: Dental staff were characterized with the tolerance of enduring stress and they are at a high risk to respiratory infectious disease. This study compared the anxiety level of the frontline dental staff (FDS) to the general public in Yichang during the coronavirus disease of 2019 (COVID-19) pandemic and examined potential explanatory factors to the differences. Methods: : Two online questionnaires were used separately to collect data from FDS and the general public. The Chinese version of Beck Anxiety Inventory (BAI) was included for the assessment of anxiety. Firstly, a Chi-square test was conducted to compare the anxiety state between these two groups. Then, a bivariate analysis using Cramer’s V and Eta squared was conducted to find the potential factors. Lastly, a binary logistic regression was performed to examine the association between potential factors and the anxiety state of FDS. Results: : In general, FDS were 4.342 (95% CI: 2.427-7.768) times more likely to suffer from anxiety disorders than the general public. The bivariate analysis showed that age, Level Three Protective Measures (PM-3), conflicts with patients and/or colleagues were moderately associated with the anxiety state of FDS. But the knowledge of COVID-19, the treatment to suspected or confirmed cases both had a weak association with the anxiety among FDS. Conversely, workload, the exposure to potential infectious substance and conducting aerosol generated performance were not significantly related to the anxiety of FDS. As the model indicated, an elder age and PM-3 protective measures could lower the anxiety state of FDS, whereas the conflict with patients or/and colleagues would worsen it. Conclusions: : During the COVID-19 pandemic, FDS were more likely to suffer from anxiety disorders than the general public. An elder age, sufficient personal protective measures and good relationships with colleagues and patients would help them to maintain good mental health.
Subject(s)
Anxiety Disorders , COVID-19 , Communicable DiseasesABSTRACT
Objectives: Evaluation of serostatus against SARS-CoV-2 has emerged as an important tool in identification of exposure to COVID-19. We report on the validation of the Vitros Anti-SARS-CoV-2 Total (CoV2T) assay for qualitative serological testing of SARS-CoV-2 antibodies. Methods: We performed validation studies according to COLA guidelines, using samples previously tested for SARS-CoV-2 by RT-PCR. We evaluated precision, analytical interferences, and cross-reactivity with other viral infections. We also evaluated concordance with molecular and other serological testing, and evaluated seroconversion. Results: The Vitros CoV2T assay exhibited acceptable precision, was resistant to analytical interference, and did not exhibit cross-reactivity with samples positive for other respiratory viruses. The CoV2T assay exhibited 100% negative predictive agreement (56/56) and 71% positive predictive agreement (56/79) with RT-PCR across all patient samples, and was concordant with other serological assays. Concordance with RT-PCR was 97% > 7 days after symptom onset. Conclusions: The Vitros CoV2T assay was successfully validated in our laboratory. We anticipate it will be a useful tool in screening for exposure to SARS-CoV-2, however, the use of the CoV2T and other serological assays in clinical management of COVID-19 patients is yet unknown, and must be evaluated in future studies.
Subject(s)
COVID-19 , Virus DiseasesABSTRACT
Background: A very serious new type of coronavirus infection has recently erupted in China. For new viruses, data and information in all aspects need to be improved.Case Presentations: During the early COVID-19 outbreak, a 38-year-old man experienced COVID-19 infection in Shenzhen (nonendemic area-related personnel) and underwent SARS-CoV-2 nucleic acid screening multiple times due to an initial positive COVID-19 screening at the beginning of the disease. The results of these additional tests were negative, and the initial SARS-CoV-2 nucleic acid screening result for this patient was suspected as being a false positive.Diagnosis: After nearly 17 days of hospitalization in two hospitals, a variety of tests were performed to diagnosis this new coronavirus infection (due to the positive results of the initial screening).Intervention: Early in the onset of the disease, treatment was given to maintain water and electrolyte balance, and antibiotics and proprietary Chinese medicines were given as the treatment. The symptoms were controlled at an early stage.Outcomes: The patient developed symptoms on the first day and had pneumonia in the lungs, as shown by a chest CT examination on the 7th day of onset. The subsequent prognosis was good. The family members living with this patient did not show similar symptoms.Conclusion: The diagnostic process of COVID-19 needs to be improved, and the development of SARS-CoV-2 diagnostic reagents needs to be strengthened under certain conditions. Screening should be performed at an early stage when a COVID-19 infection is suspected and should distinguish between patients with a COVID-19 infection and with a non-COVID-19 infection. Patients are more conducive to controlling the COVID-19 epidemic.
Subject(s)
COVID-19 , Coronavirus Infections , PneumoniaABSTRACT
Objective To explore the clinical features of critical cases of coronavirus disease 2019 (COVID-19). Methods The clinical data of nine patients who were diagnosed with critical COVID-19 in Hainan General Hospital from January 21, 2020 to February 6, 2020 were retrospectively analyzed. RT-PCR testing for 2019 novel coronavirus (2019-nCoV) was performed with multi-sites synchronize specimens including pharyngeal swab, blood, excrement, and urine. The serum levels of leucocyte, C-reactive protein, procalcitonin and lactic acid between the improved group (five cases) and the deteriorated group (four cases) were compared. The t test was used for comparison of normally distributed continuous data between groups. Results There were eight males (88.9%) and 1 female enrolled. The patients aged 28-77 years old, with an age of (52.9±18.0) years. By March 4, 2020, all five cases in improved group were cured and discharged, three cases in deteriorated group died and 1case remained in critical condition. All multi-sites specimens of patients in improved group turned negative in 2-4 weeks of illness onset, while those of cases in deteriorated group showed sustained viral nucleic acid positive (up to 48th day of illness onset). The white blood cell counts ((13.52±8.24)×10 9 /L vs (10.49±4.46) ×10 9 /L), C-reactive protein ((139.71±87.46) mg/L vs (78.60±55.40) mg/L) and procalcitonin ((2.32±4.03) ng/mL vs (0.28±0.58) ng/mL) , lactic acid ((3.70±4.14) mmol/L vs (2.33±0.53) mmol/L) in deteriorated group were all significantly higher than those in improved group ( t =2.908, 5.009, 4.391 and 2.942, respectively, all P <0.01). A rapid rise of serum IL-6 level up to 8 500 pg/mL was observed in one patient three days prior to death. Conclusion Among the patients with critical COVID-19, serum levels of inflammatory cytokines of the death cases are higher than those of improved and discharged cases.
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WHO has declared COVID-19 a pandemic with more than 300,000 confirmed cases and more than 14,000 deaths. There is urgent need for accurate and rapid diagnostic kits. Here we report the development and validation of a COVID-19/SARS-CoV-2 S1 serology ELISA kit for the detection of total anti-virus antibody (IgG+IgM) titers in sera from either the general population or patients suspected to be infected. For indirect ELISA, CHO-expressed recombinant full length SARS-CoV-2-S1 protein with 6*His tag was used as the coating antigen to capture the SARS-CoV-2-S1 antibodies specifically. The specificity of the ELISA kit was determined to be 97.5%, as examined against total 412 normal human sera including 257 samples collected prior to the outbreak and 155 collected during the outbreak. The sensitivity of the ELISA kit was determined to be 97.5% by testing against 69 samples from hospitalized and/or recovered COVID-19 patients. The overall accuracy rate reached 97.3%. Most importantly, in one case study, the ELISA test kit was able to identify an infected person who had previously been quarantined for 14 days after coming into contact with a confirmed COVID-19 patient, and discharged after testing negative twice by nucleic acid test. With the assays developed here, we can screen millions of medical staffs in the hospitals and people in residential complex, schools, public transportations, and business parks in the epidemic centers of the outbreaks to fish out the "innocent viral spreaders", and help to stop the further spreading of the virus.
Subject(s)
COVID-19 , InfectionsABSTRACT
Background Severe cases of coronavirus disease 2019 (COVID-19) rapidly develop acute respiratory distress leading to respiratory failure, with high short-term mortality rates. At present, there is no reliable risk stratification tool for non-severe COVID-19 patients at admission. We aimed to construct an effective model for early identifying cases at high risk of progression to severe COVID-19. Methods SARS-CoV-2 infected patients from one center in Wuhan city and two centers in Guangzhou city, China were included retrospectively. All patients with non-severe COVID-19 during hospitalization were followed for more than 15 days after admission. Patients who deteriorated to severe or critical COVID-19 and patients who kept non-severe state were assigned to the severe and non-severe group, respectively. We compared the demographic, clinical, and laboratory data between severe and non-severe group. Based on baseline data, least absolute shrinkage and selection operator (LASSO) algorithm and logistic regression model were used to construct a nomogram for risk prediction in the train cohort. The predictive accuracy and discriminative ability of nomogram were evaluated by area under the curve (AUC) and calibration curve. Decision curve analysis (DCA) and clinical impact curve analysis (CICA) were conducted to evaluate the clinical applicability of our nomogram. Findings The train cohort consisted of 189 patients, while the two independent validation cohorts consisted of 165 and 18 patients. Among all cases, 72 (19.35%) patients developed severe COVID-19 and 107 (28.76%) patients had one of the following basic disease, including hypertension, diabetes, coronary heart disease, chronic respiratory disease, tuberculosis disease. We found one demographic and six serological indicators (age, serum lactate dehydrogenase, C-reactive protein, the coefficient of variation of red blood cell distribution width (RDW), blood urea nitrogen, albumin, direct bilirubin) are associated with severe COVID-19. Based on these features, we generated the nomogram, which has remarkably high diagnostic accuracy in distinguishing individuals who exacerbated to severe COVID-19 from non-severe COVID-19 (AUC 0.912 [95% CI 0.846-0.978]) in the train cohort with a sensitivity of 85.71 % and specificity of 87.58% ; 0.853 [0.790-0.916] in validation cohort with a sensitivity of 77.5 % and specificity of 78.4%. The calibration curve for probability of severe COVID-19 showed optimal agreement between prediction by nomogram and actual observation. DCA and CICA further indicated that our nomogram conferred significantly high clinical net benefit. Interpretation Our nomogram could help clinicians to early identify patients who will exacerbate to severe COVID-19. And this risk stratification tool will enable better centralized management and early treatment of severe patients, and optimal use of medical resources via patient prioritization and thus significantly reduce mortality rates. The RDW plays an important role in predicting severe COVID-19, implying that the role of RBC in severe disease is underestimated.