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1.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-330390

ABSTRACT

Purpose: To investigate the impact of COVID-19 on the treatment of children with congenital diaphragmatic hernia (CDH). Methods: We retrospectively collected and compared the data of patients with CDH admitted between January 1, 2020 and December 31, 2021 with the CDH patients admitted before the pandemic between January 1, 2018 and December 31, 2019 (control group). Results: During the pandemic, 41 patients with CDH diagnosed prenatally were transferred to our hospital, and 40 underwent surgical repair. The number of patients treated in our hospital increased by 24.2% compared with that before the pandemic. During the pandemic, the overall survival rate, postoperative survival rate and recurrence rate were 85.4%, 87.5% and 7.3%, respectively, and there were no significant differences compared with the control group. The average length of hospital stay in patients admitted during the pandemic was longer than that in the control group, and the incidence of nosocomial infection was higher than that in the control group. Conclusions: CDH patients confirmed to be SARS-CoV-2 infection-free can receive routine treatment. Our data indicate that the implementation of protective measures during the COVID-19 pandemic, along with appropriate screening and case evaluation, do not have a negative impact on the prognosis of children.

2.
J Med Virol ; 93(9): 5487-5504, 2021 09.
Article in English | MEDLINE | ID: covidwho-1733919

ABSTRACT

Along with the control and prevention of coronavirus disease 2019 transmission, infected animals might have potential to carry the virus to spark new outbreaks. However, very few studies explore the susceptibility of animals to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Viral attachment as a crucial step for cross-species infection requires angiotensin-converting enzyme 2 (ACE2) as a receptor and depends on TMPRSS2 protease activity. Here, we searched the genomes of metazoans from different classes using an extensive BLASTP survey and found ACE2 and TMPRSS2 occur in vertebrates, but some vertebrates lack Tmprss2. We identified 6 amino acids among 25 known human ACE2 residues are highly associated with the binding of ACE2 to SARS-CoV-2 (p value < .01) by Fisher exact test, and following this, calculated the probability of viral attachment within each species by the randomForest function from R randomForest library. Furthermore, we observed that Ace2 selected from seven animals based on the above analysis lack the hydrophobic contacts identified on human ACE2, indicating less affinity of SARS-CoV-2 to Ace2 in animals than humans. Finally, the alignment of 3D structure between human ACE2 and other animals by I-TASSER and TM-align displayed a reasonable structure for viral attachment within these species. Taken together, our data may shed light on the human-to-animal transmission of SARS-CoV-2.


Subject(s)
Angiotensin-Converting Enzyme 2/metabolism , COVID-19/virology , Host-Pathogen Interactions , SARS-CoV-2/physiology , Serine Endopeptidases/metabolism , Vertebrates/metabolism , Angiotensin-Converting Enzyme 2/genetics , Animals , COVID-19/genetics , COVID-19/metabolism , Disease Susceptibility , Genetic Predisposition to Disease , Humans , Receptors, Virus/metabolism , SARS-CoV-2/classification , Serine Endopeptidases/genetics , Spike Glycoprotein, Coronavirus/metabolism , Vertebrates/genetics , Virus Attachment , Virus Internalization , Virus Release
3.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-313410

ABSTRACT

The transmission dynamics of COVID-19 is investigated in this study. A SINDy-LM modeling method that can effectively balance model complexity and prediction accuracy is proposed based on data-driven technique. First, the Sparse Identification of Nonlinear Dynamical systems (SINDy) method is used to discover and describe the nonlinear functional relationship between the dynamic terms in the model in accordance with the observation data of the COVID-19 epidemic. Moreover, the Levenberg–Marquardt (LM) algorithm is utilized to optimize the obtained model for improving the accuracy of the SINDy algorithm. Second, the obtained model, which is consistent with the logistic model in mathematical form with small errors and high robustness, is leveraged to review the epidemic situation in China. Otherwise, the evolution of the epidemic in Australia and Egypt is predicted, which demonstrates that this method has universality for constructing the global COVID-19 model. The proposed model is also compared with the extreme learning machine (ELM), which shows that the prediction accuracy of the SINDy-LM method outperforms that of the ELM method and the generated model has higher sparsity.

4.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-313367

ABSTRACT

In December 2019, a novel coronavirus was found in a seafood wholesale market in Wuhan, China. WHO officially named this coronavirus as COVID-19. Since the first patient was hospitalized on December 12, 2019, China has reported a total of 78,824 confirmed CONID-19 cases and 2,788 deaths as of February 28, 2020. Wuhan's cumulative confirmed cases and deaths accounted for 61.1% and 76.5% of the whole China mainland , making it the priority center for epidemic prevention and control. Meanwhile, 51 countries and regions outside China have reported 4,879 confirmed cases and 79 deaths as of February 28, 2020. COVID-19 epidemic does great harm to people's daily life and country's economic development. This paper adopts three kinds of mathematical models, i.e., Logistic model, Bertalanffy model and Gompertz model. The epidemic trends of SARS were first fitted and analyzed in order to prove the validity of the existing mathematical models. The results were then used to fit and analyze the situation of COVID-19. The prediction results of three different mathematical models are different for different parameters and in different regions. In general, the fitting effect of Logistic model may be the best among the three models studied in this paper, while the fitting effect of Gompertz model may be better than Bertalanffy model. According to the current trend, based on the three models, the total number of people expected to be infected is 49852-57447 in Wuhan,12972-13405 in non-Hubei areas and 80261-85140 in China respectively. The total death toll is 2502-5108 in Wuhan, 107-125 in Non-Hubei areas and 3150-6286 in China respetively. COVID-19 will be over p robably in late-April, 2020 in Wuhan and before late-March, 2020 in other areas respectively.

5.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-308297

ABSTRACT

How to model the 2019 CoronaVirus (2019-nCov) spread in China is one of the most urgent and interesting problems in applied mathematics. In this paper, we propose a novel time delay dynamic system with external source to describe the trend of local outbreak for the 2019-nCoV. The external source is introduced in the newly proposed dynamic system, which can be considered as the suspected people travel to different areas. The numerical simulations exhibit the dynamic system with the external source is more reliable than the one without it, and the rate of isolation is extremely important for controlling the increase of cumulative confirmed people of 2019-nCoV. Based on our numerical simulation results with the public data, we suggest that the local government should have some more strict measures to maintain the rate of isolation. Otherwise the local cumulative confirmed people of 2019-nCoV might be out of control.

6.
EuropePMC;
Preprint in English | EuropePMC | ID: ppcovidwho-327486

ABSTRACT

Constantly emerging SARS-CoV-2 variants, such as Omicron BA.1, BA.1.1 and BA.2, pose a severe challenge to COVID-19 control 1–10 . Broad-spectrum antibody therapeutics and vaccines are needed for defending against future SARS-CoV-2 variants and sarbecovirus pandemics 11–14 ;however, we have yet to gain a comprehensive understanding of the epitopes capable of inducing broad sarbecovirus neutralization. Here, we report the identification of 241 anti-RBD broad sarbecovirus neutralizing antibodies isolated from 44 SARS-CoV-2 vaccinated SARS convalescents. Neutralizing efficacy of these antibodies against D614G, SARS-CoV-1, Omicron variants (BA.1, BA.1.1, BA.2), RATG13 and Pangolin-GD is tested, and their binding capability to 21 sarbecovirus RBDs is measured. High-throughput yeast-display mutational screening was further applied to determine each antibody’s RBD escaping mutation profile, and unsupervised epitope clustering based on escaping mutation hotspots was performed 7,15–18 . A total of 6 clusters of broad sarbecovirus neutralizing antibodies with diverse breadth and epitopes were identified, namely Group E1 (S309 19 , BD55-3152 site), E3 (S2H97 20 site), F1 (CR3022 21 , S304 22 site), F2 (DH1047 23 , BD55-3500 site), F3 (ADG-2 24 , BD55-3372 site) and B’ (S2K146 25 site). Members of E1, F2 and F3 demonstrate the highest neutralization potency;yet, Omicron, especially BA.2, has evolved multiple mutations (G339D, N440K, T376A, D405N, R408S) to escape antibodies of these groups. Nevertheless, broad sarbecovirus neutralizing antibodies that survived Omicron would serve as favorable therapeutic candidates. Furthermore, structural analyses of selected drug candidates propose two non-competing antibody pairing strategies, E1-F2 and E1-F3, as broad-spectrum antibody cocktails. Together, our work provides a comprehensive epitope map of broad sarbecovirus neutralizing antibodies and offers critical instructions for designing broad-spectrum vaccines.

8.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-324802

ABSTRACT

Background: : Novel coronavirus disease(COVID-19)has become a worldwide pandemic and precise fatality data by age group are needed urgently. This study to delineate the clinical characteristics and outcome of COVID-19 patients aged ≥75 years and identify the risk factors of in-hospital death. Methods: : A total of 141 consecutive patients aged ≥75 years who were admitted to the hospital between 12 th and 19 th February 2020. In-hospital death, clinical characteristics and laboratory findings on admission were obtained from medical records. The final follow-up observation was 31 st March 2020. Results: : The median age was 81 years (84 female, 59.6%). Thirty-eight (27%) patients were classified as severe or critical cases. 18 (12.8%) patients had died in hospital and the remaining 123 were discharged. Patients who died were more likely to present with fever (38.9% vs. 7.3%);low percutaneous oxygen saturation(SpO 2 ) (55.6% vs. 7.3%);reduced lymphocytes (72.2% vs. 35.8%) and platelets (27.8% vs. 4.1%);and increased D-dimer (94.4% vs. 42.3%), creatinine (50.0% vs. 22.0%), lactic dehydrogenase (LDH) (77.8% vs. 30.1%), high sensitivity troponin I (hs-TnI) (72.2% vs. 14.6%), and N-terminal pro-brain natriuretic peptide (NT-proBNP) (72.2% vs. 6.5%;all P<0.05) than patients who recovered. Male sex (odds ratio [OR]=13.1, 95% confidence interval[CI] 1.1 to 160.1, P=0.044), body temperature >37.3°C (OR=80.5, 95% CI 4.6 to 1407.6, P=0.003), SpO 2 ≤90% (OR=70.1, 95% CI 4.6 to 1060.4, P=0.002), and NT-proBNP>1800ng/L (OR=273.5, 95% CI 14.7 to 5104.8, P<0.0001) were independent risk factors of in-hospital death. Conclusions: : In-hospital fatality among COVID-19 patients can be estimated by sex and on-admission measurements of body temperature, SpO 2 , and NT-proBNP.

9.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-321485

ABSTRACT

Background: COVID-19 can lead to increased psychological symptoms such as post-traumatic stress disorder (PTSD), depression, and anxiety, especially for patients with COVID-19. Studies suggest that mindfulness-based intervention is an effective, easily delivered and non-aggressive online therapy for patients with mental disorders. This study aims to explore the efficacy and possible mechanism of a Mindful Living With Challenge (MLWC) intervention designed for Chinese COVID-19 survivors in alleviating their psychological problems caused by both the disease and the pandemic. Methods: This study is a protocol for a randomized controlled trial. More than 1600 eligible participants will be assigned 1:1 to an online MLWC intervention group or a waitlist control group. All participants will be asked to complete online questionnaires at baseline , post-program, and 3-month follow-up. The primary outcome is mental health status which includes PTSD and other psychological symptoms (i.e. depression, anxiety). The secondary outcomes are related physical symptoms including fatigue and sleeplessness assessed by verified scales such as the Fatigue Scale-14, Pittsburgh Sleep Quality Index. In addition, Five Facets Mindfulness Questionnaire, the Nonattachment Scale, the Stillness Scale, the Resilience Style Questionnaire and the Social Support Scale will be used to assess the mindfulness, stillness, nonattachment level, resilience and perceived social support before and after the intervention, which may be the possible mediators and moderators of the link between the MLWC intervention and target outcomes. Data will be analyzed based on an intention-to-treat approach, and SPSS software will be used to perform statistical analysis. Discussion: This study will provide scientific evidence on the efficacy and possible mechanism of the MLWC intervention in improving the quality of life and psychological status among COVID-19 survivors in China. Findings from this study will contribute to a growing research field that assesses the effectiveness of mobile-based and theoretically guided interventions for improving the psychological status of the COVID-19 survivors. Moreover, findings from this study will also contribute to the prevention and management of the psychological complications patients face during such public health emergencies. Trial registration Chinese Clinical Trial Registry (ChiCTR), ChiCTR2000037524;Registered on August 29, 2020, http://www.chictr.org.cn/showproj.aspx?proj=60034.

10.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-321484

ABSTRACT

Background: College students are a uniquely vulnerable group and may experience high stress levels due to COVID-19. This study aims to identify the the psychological state and related factors on Chinese college students during the initial phases of the COVID-19 pandemic. Methods: From February 23 to March 5, 2020, a cross-sectional online survey was conducted among 3606 college students from seven provinces in China using standard questionnaires measuring adverse psychological outcomes and related factors including Impact of Event Scale-6 (IES-6), Depression, Anxiety and Stress Scale (DASS), Perceived Social Support Scale (PSSS) and Simplified Coping Style Questionnaire (SCSQ). Exploratory factor analysis (EFA) were used to determine underlying constructs of the perceived threat items. Multivariate regression was used to explore the determinants of adverse psychological impact. Results: Posttraumatic stress (PTS) were prevalent in this sample of college students, and 34.22% met the cut-off for posttraumatic stress disorder (PTSD). The proportion of having mild to extremely severe symptoms of depression, anxiety and stress were 15.70%, 13.31% and 7.10%, respectively. The impact of closed-off management on life, perceived threat and passive coping strategies were positively correlated to PTS and DASS scores, while knowledge score, perceived social support and active coping strategies were negatively correlated to DASS scores. Conclusions: In summary, adverse psychological symptoms were prevalent among college students in China during the COVID-19 epidemic. Identifying vulnerable populations and formulating correspondingly psychological interventions would be beneficial to improve the mental health during the COVID-19 epidemic.

11.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-321483

ABSTRACT

Background: College students are a uniquely vulnerable group and may experience high stress levels due to COVID-19, especially for girls. This study aims to identify the post-traumatic stress disorder (PTSD) symptoms and related factors among the target population during the initial phases of the COVID-19 pandemic. Methods: A cross-sectional online survey was conducted during the initial phases of the COVID-19 pandemic in China. A total of 2205 college female students from six provinces enrolled in this study and completed the questions about cognitive status of COVID-19, the Impact of Event Scale-6 (IES-6), the Multidimensional Perceived Social Support Scale (MPSSS) and a self-developed 10-item Perceived threat scale. Univariate and multivariate logistic regression were performed by SPSS software to explore the determinants of PTSD symptoms. Results: PTSD symptoms were prevalent in this sample of college female students, and 34.20% met the cut-off for PTSD. Self-reported fair or poor health (AOR=1.78, 95%CI: 1.22-2.59), high concern about COVID-19 (AOR=1.66, 95%CI: 1.35-2.03), beliefs that 'COVID-19 can cause a global outbreak' (AOR=1.26, 95%CI: 1.02-1.56), the perception of ‘risk of infection’ (AOR=2.46, 95%CI: 2.16-2.81), beliefs that ‘closed management’ and ‘COVID-19 as a public health emergency of international concern’ would have an impact, and the fear of ‘impact on life planning’ were all positively associated with PTSD (AOR=1.37, 1.22 and 1.29, respectively), whereas perceived social support from family (AOR=0.81, 95%CI: 0.70-0.93) was negatively associated with PTSD. Among the significant variables at the bivariate level, multivariate logistic regression revealed that the greatest protector for PTSD was the high knowledge score (AOR=0.73, 95%CI: 0.60-0.90), while had confirmed cases among relatives and friends (AOR=7.70, 95%CI: 1.28-46.25) was the strongest predictor of PTSD. Conclusions: In summary, PTSD symptoms were prevalent among college female students in China during the COVID-19 epidemic. Targeting vulnerable populations to improve their knowledge of COVID-19 and create an atmosphere of social support would be beneficial to improve the mental health of the female students during the COVID-19 epidemic.

12.
Psychol Res Behav Manag ; 15: 193-212, 2022.
Article in English | MEDLINE | ID: covidwho-1666877

ABSTRACT

Purpose: Road safety research is important due to the large number of road traffic fatalities globally. This study investigated the influences of age, driving experience and other covariates on aggressive driving behavior. Methods: A cross-sectional survey was conducted in Yixing City, Wuxi City, Jiangsu Province, China. Regression analysis was applied to explore the influences of age and driving experience and their interactions with other covariates on aggressive driving behavior. Two analyses methodologies were used to assess the simple effect of the interactions. Firstly, the Jamovi automatic analysis classification program was used to calculate the simple slope test. Second, the SPSS macro program was also used to calculate the simple slope test also. Results: A total of 570 drivers (247 males, 282 females) participated in the survey. A negative correlation was found between age and aggressive driving behaviors, and a positive correlation was found between neuroticism and aggressive driving behaviors in the multiple regression analysis. Significant associations were also found between age, driving experience, and depression, as well as age, driving experience, and neuroticism. Simple slope tests showed that depressive symptoms could increase aggressive behaviors in the elderly and experienced drivers. When experiencing neuroticism, individuals with higher driving experience were more aggressive in driving than shorter experienced drivers. Conclusion: Age and neuroticism influenced aggressive driving behaviors. Veteran drivers could be aggressive drivers when experiencing depressive symptoms or neuroticism. Mobile intervention could be sent to the potentially risky drivers, which would be safe and broadly feasible to prevent aggressive driving behavior in the background of COVID-19.

13.
Nucleic Acids Res ; 2022 Jan 31.
Article in English | MEDLINE | ID: covidwho-1662127

ABSTRACT

Omics-based biomedical learning frequently relies on data of high-dimensions (up to thousands) and low-sample sizes (dozens to hundreds), which challenges efficient deep learning (DL) algorithms, particularly for low-sample omics investigations. Here, an unsupervised novel feature aggregation tool AggMap was developed to Aggregate and Map omics features into multi-channel 2D spatial-correlated image-like feature maps (Fmaps) based on their intrinsic correlations. AggMap exhibits strong feature reconstruction capabilities on a randomized benchmark dataset, outperforming existing methods. With AggMap multi-channel Fmaps as inputs, newly-developed multi-channel DL AggMapNet models outperformed the state-of-the-art machine learning models on 18 low-sample omics benchmark tasks. AggMapNet exhibited better robustness in learning noisy data and disease classification. The AggMapNet explainable module Simply-explainer identified key metabolites and proteins for COVID-19 detections and severity predictions. The unsupervised AggMap algorithm of good feature restructuring abilities combined with supervised explainable AggMapNet architecture establish a pipeline for enhanced learning and interpretability of low-sample omics data.

14.
Inquiry ; 58: 469580211059953, 2021.
Article in English | MEDLINE | ID: covidwho-1598094

ABSTRACT

BACKGROUND: College students are vulnerable and may experience high stress due to COVID-19, especially girls. This study aims to identify posttraumatic stress disorder (PTSD) and related factors among the target population during the initial phases of the COVID-19 pandemic. METHODS: In the initial phase of COVID-19 epidemic (February 23 to March 5, 2020), 2205 female college students from six provinces in mainland China were enrolled in this study and completed the online survey about the cognitive status of COVID-19, including the Impact of Event Scale-6, the Multidimensional Perceived Social Support Scale and a self-developed 10-item Perceived threat scale. Univariate and multivariate logistic regression were performed using SPSS software to explore the determinants of PTSD symptoms. RESULTS: PTSD symptoms were prevalent in female college students, and 34.20% met the cut-off for PTSD. Self-reported fair or poor health (AOR = 1.78, 95% CI: 1.22-2.59), high concern about COVID-19 (AOR = 1.66, 95% CI: 1.35-2.03), beliefs that "COVID-19 can cause a global outbreak" (AOR = 1.26, 95% CI: 1.02-1.56), the perception of "risk of infection" (AOR = 2.46, 95% CI: 2.16-2.81), beliefs that "closed management" and "COVID-19 as a public health emergency of international concern" would have an impact, and the fear of "impact on life planning" were all positively associated with PTSD (AOR = 1.37, 1.22, and 1.29, respectively); however, perceived social support from family (AOR = 0.81, 95% CI: 0.70-0.93) was negatively associated with PTSD. Among the significant variables at the bivariate level, multivariate logistic regression revealed that the greatest protector for PTSD was the high knowledge score (AOR = 0.73, 95% CI: 0.60-0.90), while had confirmed cases among relatives and friends (AOR = 7.70, 95% CI: 1.28-46.25) was the strongest predictor of PTSD. CONCLUSIONS: In summary, PTSD symptoms were prevalent among female college students in China during the COVID-19 epidemic. Targeting vulnerable populations to improve their knowledge about COVID-19 and create an atmosphere of social support would be beneficial. Moreover, the joint efforts from family, school administrators, and policymakers are essential to improve the mental health of the female students during the COVID-19 epidemic.


Subject(s)
COVID-19 , Stress Disorders, Post-Traumatic , Anxiety , China/epidemiology , Cross-Sectional Studies , Depression , Female , Humans , Pandemics , Prevalence , SARS-CoV-2 , Stress Disorders, Post-Traumatic/epidemiology , Students , Surveys and Questionnaires
15.
Signal Transduct Target Ther ; 6(1): 438, 2021 12 24.
Article in English | MEDLINE | ID: covidwho-1585880

ABSTRACT

Messenger RNA (mRNA) vaccine technology has shown its power in preventing the ongoing COVID-19 pandemic. Two mRNA vaccines targeting the full-length S protein of SARS-CoV-2 have been authorized for emergency use. Recently, we have developed a lipid nanoparticle-encapsulated mRNA (mRNA-LNP) encoding the receptor-binding domain (RBD) of SARS-CoV-2 (termed ARCoV), which confers complete protection in mouse model. Herein, we further characterized the protection efficacy of ARCoV in nonhuman primates and the long-term stability under normal refrigerator temperature. Intramuscular immunization of two doses of ARCoV elicited robust neutralizing antibodies as well as cellular response against SARS-CoV-2 in cynomolgus macaques. More importantly, ARCoV vaccination in macaques significantly protected animals from acute lung lesions caused by SARS-CoV-2, and viral replication in lungs and secretion in nasal swabs were completely cleared in all animals immunized with low or high doses of ARCoV. No evidence of antibody-dependent enhancement of infection was observed throughout the study. Finally, extensive stability assays showed that ARCoV can be stored at 2-8 °C for at least 6 months without decrease of immunogenicity. All these promising results strongly support the ongoing clinical trial.


Subject(s)
COVID-19 Vaccines/pharmacology , COVID-19/immunology , Immunogenicity, Vaccine , SARS-CoV-2/immunology , Spike Glycoprotein, Coronavirus/immunology , /pharmacology , Animals , Antibodies, Neutralizing/immunology , Antibodies, Viral/immunology , COVID-19/prevention & control , COVID-19 Vaccines/immunology , Chlorocebus aethiops , Humans , Macaca fascicularis , Vero Cells , /immunology
16.
BMC Infect Dis ; 21(1): 737, 2021 Aug 03.
Article in English | MEDLINE | ID: covidwho-1435227

ABSTRACT

BACKGROUND: The serum surfactant protein D (SP-D) level is suggested to be a useful biomarker for acute lung injuries and acute respiratory distress syndrome. Whether the serum SP-D level could identify the severity of coronavirus disease 2019 (COVID-19) in the early stage has not been elucidated. METHODS: We performed an observational study on 39 laboratory-confirmed COVID-19 patients from The Fourth People's Hospital of Yiyang, Hunan, China. Receiver operating characteristic (ROC) curve analysis, correlation analysis, and multivariate logistic regression model analysis were performed. RESULTS: In the acute phase, the serum levels of SP-D were elevated significantly in severe COVID-19 patients than in mild cases (mean value ± standard deviation (SD), 449.7 ± 125.8 vs 245.9 ± 90.0 ng/mL, P<0.001), while the serum levels of SP-D in the recovery period were decreased dramatically than that in the acute phase (mean value ± SD, 129.5 ± 51.7 vs 292.9 ± 130.7 ng/ml, P<0.001), and so were for the stratified patients. The chest CT imaging scores were considerably higher in the severe group compared with those in the mild group (median value, 10.0 vs 9.0, P = 0.011), while markedly lower in the recovery period than those in the acute phase (median value, 2.0 vs 9.0, P<0.001), and so were for the stratified patients. ROC curve analysis revealed that areas under the curve of lymphocyte counts (LYM), C-reaction protein (CRP), erythrocyte sedimentation rate (ESR), interleukin-6 (IL-6), and SP-D for severe COVID-19 were 0.719, 0.833, 0.817, 0.837, and 0.922, respectively. Correlation analysis showed that the SP-D levels were negatively correlated with LYM (r = - 0.320, P = 0.047), while positively correlated with CRP (r = 0.658, P<0.001), IL-6 (r = 0.471, P = 0.002), the duration of nucleic acid of throat swab turning negative (r = 0.668, P<0.001), chest CT imaging score on admission (r = 0.695, P<0.001) and length of stay (r = 0.420, P = 0.008). Multivariate logistic regression model analysis showed that age (P = 0.041, OR = 1.093) and SP-D (P = 0.008, OR = 1.018) were risk factors for severe COVID-19. CONCLUSIONS: Elevated serum SP-D level was a potential biomarker for the severity of COVID-19; this may be useful in identifying patients whose condition worsens at an early stage.


Subject(s)
COVID-19 , Pulmonary Surfactant-Associated Protein D , Humans , Prognosis , ROC Curve , Retrospective Studies , SARS-CoV-2 , Severity of Illness Index
17.
Nonlinear Dyn ; 105(3): 2775-2794, 2021.
Article in English | MEDLINE | ID: covidwho-1372807

ABSTRACT

The transmission dynamics of COVID-19 is investigated in this study. A SINDy-LM modeling method that can effectively balance model complexity and prediction accuracy is proposed based on data-driven technique. First, the Sparse Identification of Nonlinear Dynamical systems (SINDy) method is used to discover and describe the nonlinear functional relationship between the dynamic terms in the model in accordance with the observation data of the COVID-19 epidemic. Moreover, the Levenberg-Marquardt (LM) algorithm is utilized to optimize the obtained model for improving the accuracy of the SINDy algorithm. Second, the obtained model, which is consistent with the logistic model in mathematical form with small errors and high robustness, is leveraged to review the epidemic situation in China. Otherwise, the evolution of the epidemic in Australia and Egypt is predicted, which demonstrates that this method has universality for constructing the global COVID-19 model. The proposed model is also compared with the extreme learning machine (ELM), which shows that the prediction accuracy of the SINDy-LM method outperforms that of the ELM method and the generated model has higher sparsity.

18.
World J Clin Cases ; 9(19): 5266-5269, 2021 Jul 06.
Article in English | MEDLINE | ID: covidwho-1314996

ABSTRACT

BACKGROUND: Since the initial recognition of coronavirus disease 2019 (COVID-19) in Wuhan, this infectious disease has spread to most areas of the world. The pathogenesis of COVID-19 is yet unclear. Hepatitis B virus (HBV) reactivation occurring in COVID-19 patients has not yet been reported. CASE SUMMARY: A 45-year-old hepatitis B man with long-term use of adefovir dipivoxil and entecavir for antiviral therapy had HBV reactivation after being treated with methylprednisolone for COVID-19 for 6 d. CONCLUSION: COVID-19 or treatment associated immunosuppression may trigger HBV reactivation.

19.
China CDC Wkly ; 3(27): 576-580, 2021 Jul 02.
Article in English | MEDLINE | ID: covidwho-1296412

ABSTRACT

What is already known on this topic? The demand for containing the virus and protecting the economy is high on the agenda of policymakers during the coronavirus disease 2019 (COVID-19) pandemic. Modelling studies indicated that highly effective contact tracing and case isolation were enough to contain the spread of COVID-19 at the early stages, but this has not been validated in real world contexts. What is added by this report? Integrated case finding approaches, including outpatient monitoring, exposed people quarantining, and contact tracing, effectively contained the spread of COVID-19 in a densely populated district in Shanghai Municipality, China. Active case-finding involving quarantine of exposed persons and contact tracing could reduce the time from symptom onset to COVID-19 diagnosis, thus reducing the risk of local transmission. What are the implications for public health practice? Active case-finding should be prioritized as an effective approach to minimize the risk of local transmission in future pandemics. Integrated COVID-19 case finding approaches applied in Shanghai may inform public health policy in other regions where strict lockdown is not applicable.

20.
Infect Dis Poverty ; 10(1): 69, 2021 May 17.
Article in English | MEDLINE | ID: covidwho-1232440

ABSTRACT

BACKGROUND: COVID-19 can lead to increased psychological symptoms such as post-traumatic stress disorder (PTSD), depression, and anxiety among patients with COVID-19. Based on the previous mindfulness-based interventions proved to be effective, this protocol reports a design of a randomized controlled trial aiming to explore the efficacy and possible mechanism of a mindful living with challenge (MLWC) intervention developed for COVID-19 survivors in alleviating their psychological problems caused by both the disease and the pandemic. METHODS: In April 2021, more than 1600 eligible participants from Hubei Province of China will be assigned 1:1 to an online MLWC intervention group or a waitlist control group. All participants will be asked to complete online questionnaires at baseline, post-program, and 3-month follow-up. The differences of mental health status (e.g. PTSD) and physical symptoms including fatigue and sleeplessness between the COVID-19 survivors who receiving the online MLWC intervention and the control group will be assessed. In addition, the possible mediators and moderators of the link between the MLWC intervention and target outcomes will be evaluated by related verified scales, such as the Five Facets Mindfulness Questionnaire. Data will be analyzed based on an intention-to-treat approach, and SPSS software will be used to perform statistical analysis. DISCUSSION: The efficacy and potential mechanism of MLWC intervention in improving the quality of life and psychological status of COVID-19 survivors in China are expected to be reported. Findings from this study will shed light on a novel and feasible model in improving the psychological well-being of people during such public health emergencies. Trial registration Chinese Clinical Trial Registry (ChiCTR), ChiCTR2000037524; Registered on August 29, 2020, http://www.chictr.org.cn/showproj.aspx?proj=60034 .


Subject(s)
Anxiety , COVID-19/psychology , Depression , Internet-Based Intervention , Mindfulness , Stress Disorders, Post-Traumatic , Anxiety/etiology , Anxiety/therapy , China/epidemiology , Depression/etiology , Depression/therapy , Humans , Mental Health , Quality of Life , Randomized Controlled Trials as Topic , Stress Disorders, Post-Traumatic/etiology , Stress Disorders, Post-Traumatic/therapy , Surveys and Questionnaires
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