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1.
Computer Methods and Programs in Biomedicine ; : 106838, 2022.
Article in English | ScienceDirect | ID: covidwho-1803791

ABSTRACT

Background and Objective : Social media sentiment analysis based on Twitter data can facilitate real-time monitoring of COVID-19 vaccine-related concerns. Thus, the governments can adopt proactive measures to address misinformation and inappropriate behaviors surrounding the COVID-19 vaccine, threatening the success of the national vaccination campaign. This study aims to identify the correlation between COVID-19 vaccine sentiments expressed on Twitter and COVID-19 vaccination coverage, case increase, and case fatality rate in Indonesia. Methods : We retrieved COVID-19 vaccine-related tweets collected from Indonesian Twitter users between October 15, 2020, to April 12, 2021, using Drone Emprit Academic (DEA) platform. We collected the daily trend of COVID-19 vaccine coverage and the rate of case increase and case fatality from the Ministry of Health (MoH) official website and the KawalCOVID19 database, respectively. We identified the public sentiments, emotions, word usage, and trend of all filtered tweets 90 days before and after the national vaccination rollout in Indonesia. Results : Using a total of 555,892 COVID-19 vaccine-related tweets, we observed the negative sentiments outnumbered positive sentiments for 59 days (65.50%), with the predominant emotion of anticipation among 90 days of the beginning of the study period. However, after the vaccination rollout, the positive sentiments outnumbered negative sentiments for 56 days (62.20%) with the growth of trust emotion, which is consistent with the positive appeals of the recent news about COVID-19 vaccine safety and the government's proactive risk communication. In addition, there was a statistically significant trend of vaccination sentiment scores, which strongly correlated with the increase of vaccination coverage (r = 0.71, P<.0001 both first and second doses) and the decreasing of case increase rate (r = -0.70, P<.0001) and case fatality rate (r = -0.74, P<.0001). Conclusions : Our results highlight the utility of social media sentiment analysis as government communication strategies to build public trust, affecting individual willingness to get vaccinated. This finding will be useful for countries to identify and develop strategies for speed up the vaccination rate by monitoring the dynamic netizens' reactions and expression in social media, especially Twitter, using sentiment analysis.

2.
Talanta ; : 123486, 2022.
Article in English | ScienceDirect | ID: covidwho-1796081

ABSTRACT

Cancer is the leading cause of death in many countries. The development of new methods for early screening of cancers is highly desired. Targeted metallomics has been successfully applied in the screening of cancers through quantification of elements in the matrix, which is time consuming and requires combined techniques for the quantification due to the large elemental difference in the matrix. This work proposed a non-targeted metallomics (NTM) approach through synchrotron radiation based X-ray fluorescence (SRXRF) and machine learning algorithms (MLAs) for the screening of cancers. One hundred serum samples were collected from cancer patients who were confirmed by pathological examination with 100 matched serum samples from healthy volunteers. The serum samples were studied with SRXRF and the spectra from both groups were directly clarified through MLAs, which did not require the quantification of elements. The NTM approach through SRXRF and MLAs is fast (5s for data collection for one sample) and accurate (over 96% accuracy) for cancer screening. Besides, this approach can also identify the most affected elements in cancer samples like Ca, Zn and Ti as we found, which may shed lights on the drug development for cancer treatment. This NTM approach can also be applied through commercially available XRF instruments or ICP-TOF-MS with MLAs. It has the potential for the screening and prediction of other diseases like COVID-19 and neurodegenerative diseases in a high throughput and least invasive way.

3.
Chemical science ; 13(11):3216-3226, 2022.
Article in English | EuropePMC | ID: covidwho-1782305

ABSTRACT

The ongoing COVID-19 pandemic caused by SARS-CoV-2 highlights the urgent need to develop sensitive methods for diagnosis and prognosis. To achieve this, multidimensional detection of SARS-CoV-2 related parameters including virus loads, immune response, and inflammation factors is crucial. Herein, by using metal-tagged antibodies as reporting probes, we developed a multiplex metal-detection based assay (MMDA) method as a general multiplex assay strategy for biofluids. This strategy provides extremely high multiplexing capability (theoretically over 100) compared with other reported biofluid assay methods. As a proof-of-concept, MMDA was used for serologic profiling of anti-SARS-CoV-2 antibodies. The MMDA exhibits significantly higher sensitivity and specificity than ELISA for the detection of anti-SARS-CoV-2 antibodies. By integrating the high dimensional data exploration/visualization tool (tSNE) and machine learning algorithms with in-depth analysis of multiplex data, we classified COVID-19 patients into different subgroups based on their distinct antibody landscape. We unbiasedly identified anti-SARS-CoV-2-nucleocapsid IgG and IgA as the most potently induced types of antibodies for COVID-19 diagnosis, and anti-SARS-CoV-2-spike IgA as a biomarker for disease severity stratification. MMDA represents a more accurate method for the diagnosis and disease severity stratification of the ongoing COVID-19 pandemic, as well as for biomarker discovery of other diseases. A MMDA platform is developed by using metal-tagged antibodies as reporting probes combined with machine learning algorithms, as a general strategy for highly multiplexed biofluid assay.

5.
J Affect Disord ; 307: 142-148, 2022 Mar 22.
Article in English | MEDLINE | ID: covidwho-1783445

ABSTRACT

BACKGROUND: The COVID-19 pandemic is associated with an increased risk of mental health problems including suicide in many subpopulations, but its influence on stable patients with major depressive disorder (MDD) has been studied fleetingly. This study examined the one-year prevalence of suicidality including suicidal ideation (SI), suicide plans (SP), and suicide attempts (SA) as well as their correlates in clinically stable MDD patients during the COVID-19 pandemic. METHODS: A cross-sectional, observational study was conducted between October 1, 2020, and October 15, 2021, in six tertiary psychiatric hospitals. Socio-demographic information, clinical data and one-year prevalence of suicidality were recorded. RESULTS: Altogether, 1718 participants who met the eligibility criteria were included. The overall one-year prevalence of suicidality during the COVID-19 pandemic was 68.04% (95% confidence intervals (CI) =65.84-70.25%), with one-year SI prevalence of 66.4% (95%CI = 64.18-68.65%), SP prevalence of 36.26% (95%CI = 33.99-38.54%), and SA prevalence of 39.35% (95%CI = 37.04-41.66%). Binary logistic regression analyses revealed male gender, married marital status, college education level and above and age were negatively associated with risk of suicidality. Urban residence, unemployed work status, experiences of cyberbullying, a history of suicide among family members or friends, and more severe fatigue, physical pain, and residual depressive symptoms were positively associated with risk of suicidality. CONCLUSIONS: Suicidality is common among clinically stable MDD patients during the COVID-19 pandemic. Regular suicide screening and preventive measures should be provided to clinically stable MDD patients during the pandemic.

6.
Adv Sci (Weinh) ; : e2104333, 2022 Apr 11.
Article in English | MEDLINE | ID: covidwho-1782562

ABSTRACT

Coronavirus disease 2019 (COVID-19) remains a global public health threat. Hence, more effective and specific antivirals are urgently needed. Here, COVID-19 hyperimmune globulin (COVID-HIG), a passive immunotherapy, is prepared from the plasma of healthy donors vaccinated with BBIBP-CorV (Sinopharm COVID-19 vaccine). COVID-HIG shows high-affinity binding to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike (S) protein, the receptor-binding domain (RBD), the N-terminal domain of the S protein, and the nucleocapsid protein; and blocks RBD binding to human angiotensin-converting enzyme 2 (hACE2). Pseudotyped and authentic virus-based assays show that COVID-HIG displays broad-spectrum neutralization effects on a wide variety of SARS-CoV-2 variants, including D614G, Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Kappa (B.1.617.1), Delta (B.1.617.2), and Omicron (B.1.1.529) in vitro. However, a significant reduction in the neutralization titer is detected against Beta, Delta, and Omicron variants. Additionally, assessments of the prophylactic and treatment efficacy of COVID-HIG in an Adv5-hACE2-transduced IFNAR-/- mouse model of SARS-CoV-2 infection show significantly reduced weight loss, lung viral loads, and lung pathological injury. Moreover, COVID-HIG exhibits neutralization potency similar to that of anti-SARS-CoV-2 hyperimmune globulin from pooled convalescent plasma. Overall, the results demonstrate the potential of COVID-HIG against SARS-CoV-2 infection and provide reference for subsequent clinical trials.

7.
Chem Sci ; 13(11): 3216-3226, 2022 Mar 16.
Article in English | MEDLINE | ID: covidwho-1764224

ABSTRACT

The ongoing COVID-19 pandemic caused by SARS-CoV-2 highlights the urgent need to develop sensitive methods for diagnosis and prognosis. To achieve this, multidimensional detection of SARS-CoV-2 related parameters including virus loads, immune response, and inflammation factors is crucial. Herein, by using metal-tagged antibodies as reporting probes, we developed a multiplex metal-detection based assay (MMDA) method as a general multiplex assay strategy for biofluids. This strategy provides extremely high multiplexing capability (theoretically over 100) compared with other reported biofluid assay methods. As a proof-of-concept, MMDA was used for serologic profiling of anti-SARS-CoV-2 antibodies. The MMDA exhibits significantly higher sensitivity and specificity than ELISA for the detection of anti-SARS-CoV-2 antibodies. By integrating the high dimensional data exploration/visualization tool (tSNE) and machine learning algorithms with in-depth analysis of multiplex data, we classified COVID-19 patients into different subgroups based on their distinct antibody landscape. We unbiasedly identified anti-SARS-CoV-2-nucleocapsid IgG and IgA as the most potently induced types of antibodies for COVID-19 diagnosis, and anti-SARS-CoV-2-spike IgA as a biomarker for disease severity stratification. MMDA represents a more accurate method for the diagnosis and disease severity stratification of the ongoing COVID-19 pandemic, as well as for biomarker discovery of other diseases.

8.
Nanomaterials (Basel) ; 12(6)2022 Mar 17.
Article in English | MEDLINE | ID: covidwho-1753655

ABSTRACT

Coronavirus disease 2019 (COVID-19) has spread rapidly and led to over 5 million deaths to date globally. Due to the successively emerging mutant strains, therapeutics and prevention against the causative virus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), are urgently needed. Prevention of SARS-CoV-2 infection in public and hospital areas is essential to reduce the frequency of infections. Silver nanoparticles (AgNPs) with virucidal effects have been reported. Therefore, we investigated the virucidal activity and safety of ten types of AgNPs with different surface modifications and particle sizes, in cells exposed to SARS-CoV-2 in vitro. The AgNPs could effectively inhibit the activity of SARS-CoV-2, and different surface modifications and particle sizes conferred different virucidal effects, of which 50-nm BPEI showed the strongest antiviral effect. We concluded that the efficacy of each type of AgNP type was positively correlated with the corresponding potential difference (R2 = 0.82). These in vitro experimental data provide scientific support for the development of therapeutics against COVID-19, as well as a research basis for the development of broad-spectrum virucides. Given the increasing acquired resistance of pathogens against conventional chemical and antibody-based drugs, AgNPs may well be a possible solution for cutting off the route of transmission, either as an external material or a potential medicine.

9.
Frontiers in public health ; 10, 2022.
Article in English | EuropePMC | ID: covidwho-1749552

ABSTRACT

Introduction Modeling on infectious diseases is significant to facilitate public health policymaking. There are two main mathematical methods that can be used for the simulation of the epidemic and prediction of optimal early warning timing: the logistic differential equation (LDE) model and the more complex generalized logistic differential equation (GLDE) model. This study aimed to compare and analyze these two models. Methods We collected data on (coronavirus disease 2019) COVID-19 and four other infectious diseases and classified the data into four categories: different transmission routes, different epidemic intensities, different time scales, and different regions, using R2 to compare and analyze the goodness-of-fit of LDE and GLDE models. Results Both models fitted the epidemic curves well, and all results were statistically significant. The R2 test value of COVID-19 was 0.924 (p < 0.001) fitted by the GLDE model and 0.916 (p < 0.001) fitted by the LDE model. The R2 test value varied between 0.793 and 0.966 fitted by the GLDE model and varied between 0.594 and 0.922 fitted by the LDE model for diseases with different transmission routes. The R2 test values varied between 0.853 and 0.939 fitted by the GLDE model and varied from 0.687 to 0.769 fitted by the LDE model for diseases with different prevalence intensities. The R2 test value varied between 0.706 and 0.917 fitted by the GLDE model and varied between 0.410 and 0.898 fitted by the LDE model for diseases with different time scales. The GLDE model also performed better with nation-level data with the R2 test values between 0.897 and 0.970 vs. 0.731 and 0.953 that fitted by the LDE model. Both models could characterize the patterns of the epidemics well and calculate the acceleration weeks. Conclusion The GLDE model provides more accurate goodness-of-fit to the data than the LDE model. The GLDE model is able to handle asymmetric data by introducing shape parameters that allow it to fit data with various distributions. The LDE model provides an earlier epidemic acceleration week than the GLDE model. We conclude that the GLDE model is more advantageous in asymmetric infectious disease data simulation.

11.
Acta Pharmacol Sin ; 2022 Mar 16.
Article in English | MEDLINE | ID: covidwho-1747246

ABSTRACT

VV116 (JT001) is an oral drug candidate of nucleoside analog against SARS-CoV-2. The purpose of the three phase I studies was to evaluate the safety, tolerability, and pharmacokinetics of single and multiple ascending oral doses of VV116 in healthy subjects, as well as the effect of food on the pharmacokinetics and safety of VV116. Three studies were launched sequentially: Study 1 (single ascending-dose study, SAD), Study 2 (multiple ascending-dose study, MAD), and Study 3 (food-effect study, FE). A total of 86 healthy subjects were enrolled in the studies. VV116 tablets or placebo were administered per protocol requirements. Blood samples were collected at the scheduled time points for pharmacokinetic analysis. 116-N1, the metabolite of VV116, was detected in plasma and calculated for the PK parameters. In SAD, AUC and Cmax increased in an approximately dose-proportional manner in the dose range of 25-800 mg. T1/2 was within 4.80-6.95 h. In MAD, the accumulation ratio for Cmax and AUC indicated a slight accumulation upon repeated dosing of VV116. In FE, the standard meal had no effect on Cmax and AUC of VV116. No serious adverse event occurred in the studies, and no subject withdrew from the studies due to adverse events. Thus, VV116 exhibited satisfactory safety and tolerability in healthy subjects, which supports the continued investigation of VV116 in patients with COVID-19.

12.
Biochem Biophys Res Commun ; 606: 23-28, 2022 Mar 14.
Article in English | MEDLINE | ID: covidwho-1739556

ABSTRACT

Coronavirus disease 2019 (COVID-19) caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a newly emerging infectious disease currently spreading across the world. The spike (S) protein plays a key role in the receptor recognition and cell membrane fusion, making it an important target for developing vaccines, therapeutic antibodies and diagnosis. In this study, we constructed a baculovirus surface display system that efficiently presents both SARS-CoV and SARS-CoV-2 S proteins (including ectodomain, S1 subunit and receptor-binding-domain, RBD) on the surface of recombinant baculoviruses, utilizing transmembrane anchors from gp64 (signal peptide) and vesicular stomatitis virus (VSV). These recombinant baculoviruses were capable of transducing engineered HEK 293T cells overexpressing ACE2 receptors with significantly higher transduction efficiencies, indicating that S proteins displayed on baculovirus surface have antigenicity and can recognize and bind ACE2 receptors. Additionally, the transduction of SARS-CoV-2 S proteins can be inhibited by an antibody against the SARS-CoV-2 RBD. These results demonstrate that this baculovirus surface display system is a promising tool for developing antibodies, vaccines and recombinant protein production.

13.
Chem Commun (Camb) ; 58(24): 3925-3928, 2022 Mar 22.
Article in English | MEDLINE | ID: covidwho-1730326

ABSTRACT

Adjuvants are important components in vaccines to increase the immunogenicity of proteins and induce optimal immunity. In this study, we designed a novel ternary adjuvant system Alum + c-GAMP + poly(I:C) with STING agonist 3,3'-c-GAMP (c-GAMP) and TLR3 agonist poly(I:C) co-adsorbed on the conventional adjuvant aluminum gel (Alum), and further constructed an S1 protein vaccine. Two doses of vaccination with the ternary adjuvant vaccine were sufficient to induce a balanced Th1/Th2 immune response and robust humoral and cellular immunity. Additionally, the ternary adjuvant group had effective neutralizing activity against live virus SARS-CoV-2 and pseudovirus of all variants of concern (alpha, beta, gamma, delta and omicron). These results indicate that the ternary adjuvants have a significant synergistic effect and can rapidly trigger potent immune responses; the combination of the ternary adjuvant system with S1 protein is a promising COVID-19 vaccine candidate.


Subject(s)
COVID-19 , SARS-CoV-2 , Adjuvants, Immunologic/pharmacology , Alum Compounds , Aluminum , Animals , Antibodies, Viral , COVID-19/prevention & control , COVID-19 Vaccines/pharmacology , Humans , Immunity, Cellular , Mice , Mice, Inbred BALB C , Poly I
14.
Lancet Microbe ; 3(3): e193-e202, 2022 Mar.
Article in English | MEDLINE | ID: covidwho-1721237

ABSTRACT

Background: Safe and effective vaccines are urgently needed to end the COVID-19 pandemic caused by SARS-CoV-2 infection. We aimed to assess the preliminary safety, tolerability, and immunogenicity of an mRNA vaccine ARCoV, which encodes the SARS-CoV-2 spike protein receptor-binding domain (RBD). Methods: This single centre, double-blind, randomised, placebo-controlled, dose-escalation, phase 1 trial of ARCoV was conducted at Shulan (Hangzhou) hospital in Hangzhou, Zhejiang province, China. Healthy adults aged 18-59 years negative for SARS-CoV-2 infection were enrolled and randomly assigned using block randomisation to receive an intramuscular injection of vaccine or placebo. Vaccine doses were 5 µg, 10 µg, 15 µg, 20 µg, and 25 µg. The first six participants in each block were sentinels and along with the remaining 18 participants, were randomly assigned to groups (5:1). In block 1 sentinels were given the lowest vaccine dose and after a 4-day observation with confirmed safety analyses, the remaining 18 participants in the same dose group proceeded and sentinels in block 2 were given their first administration on a two-dose schedule, 28 days apart. All participants, investigators, and staff doing laboratory analyses were masked to treatment allocation. Humoral responses were assessed by measuring anti-SARS-CoV-2 RBD IgG using a standardised ELISA and neutralising antibodies using pseudovirus-based and live SARS-CoV-2 neutralisation assays. SARS-CoV-2 RBD-specific T-cell responses, including IFN-γ and IL-2 production, were assessed using an enzyme-linked immunospot (ELISpot) assay. The primary outcome for safety was incidence of adverse events or adverse reactions within 60 min, and at days 7, 14, and 28 after each vaccine dose. The secondary safety outcome was abnormal changes detected by laboratory tests at days 1, 4, 7, and 28 after each vaccine dose. For immunogenicity, the secondary outcome was humoral immune responses: titres of neutralising antibodies to live SARS-CoV-2, neutralising antibodies to pseudovirus, and RBD-specific IgG at baseline and 28 days after first vaccination and at days 7, 15, and 28 after second vaccination. The exploratory outcome was SARS-CoV-2-specific T-cell responses at 7 days after the first vaccination and at days 7 and 15 after the second vaccination. This trial is registered with www.chictr.org.cn (ChiCTR2000039212). Findings: Between Oct 30 and Dec 2, 2020, 230 individuals were screened and 120 eligible participants were randomly assigned to receive five-dose levels of ARCoV or a placebo (20 per group). All participants received the first vaccination and 118 received the second dose. No serious adverse events were reported within 56 days after vaccination and the majority of adverse events were mild or moderate. Fever was the most common systemic adverse reaction (one [5%] of 20 in the 5 µg group, 13 [65%] of 20 in the 10 µg group, 17 [85%] of 20 in the 15 µg group, 19 [95%] of 20 in the 20 µg group, 16 [100%] of 16 in the 25 µg group; p<0·0001). The incidence of grade 3 systemic adverse events were none (0%) of 20 in the 5 µg group, three (15%) of 20 in the 10 µg group, six (30%) of 20 in the 15 µg group, seven (35%) of 20 in the 20 µg group, five (31%) of 16 in the 25 µg group, and none (0%) of 20 in the placebo group (p=0·0013). As expected, the majority of fever resolved in the first 2 days after vaccination for all groups. The incidence of solicited systemic adverse events was similar after administration of ARCoV as a first or second vaccination. Humoral immune responses including anti-RBD IgG and neutralising antibodies increased significantly 7 days after the second dose and peaked between 14 and 28 days thereafter. Specific T-cell response peaked between 7 and 14 days after full vaccination. 15 µg induced the highest titre of neutralising antibodies, which was about twofold more than the antibody titre of convalescent patients with COVID-19. Interpretation: ARCoV was safe and well tolerated at all five doses. The acceptable safety profile, together with the induction of strong humoral and cellular immune responses, support further clinical testing of ARCoV at a large scale. Funding: National Key Research and Development Project of China, Academy of Medical Sciences China, National Natural Science Foundation China, and Chinese Academy of Medical Sciences.

15.
Journal of Applied Statistics ; : 1-17, 2022.
Article in English | Taylor & Francis | ID: covidwho-1713330
16.
Comput Methods Programs Biomed ; 218: 106715, 2022 May.
Article in English | MEDLINE | ID: covidwho-1702300

ABSTRACT

INTRODUCTION: Currently, several countries are facing severe public health and policy challenges when designing their COVID-19 screening strategy. A quantitative analysis of the potential impact that combing the Rapid Antigen Test (RAT; Wet screening) and digital checker (Dry screening) can have on the healthcare system is lacking. METHOD: We created a hypothetical COVID-19 cohort for the analysis. The population size was set as 10 million with three levels of disease prevalence (10%, 1%, or 0.1%) under the assumption that a positive test result will lead to quarantine. A digital checker and two RATs are used for analysis. We further hypothesized two scenarios: RAT only and RAT plus digital checker. We then calculated the number of quarantined in both scenarios and compared the two to understand the benefits of sequential coupling of a digital checker with a RAT. RESULT: Sequential coupling of the digital checker and RAT can significantly reduce the number of individuals quarantined to 0.95-1.33M, 0.86-1.29M, and 0.86-1.29M, respectively, under the three different prevalence levels. CONCLUSION: Sequential coupling of digital checker and RAT at a population level for COVID-19 positive test to reduce the number of people who require quarantine and alleviating stress on the overburdened healthcare systems during the COVID-19 pandemic.


Subject(s)
COVID-19 , COVID-19/epidemiology , Humans , Mass Screening , Pandemics/prevention & control , Quarantine , SARS-CoV-2
17.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-325512

ABSTRACT

Background: The coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 isspreading all over the world.The main symptoms of COVID-19 include fever, cough,fatigue, and myalgia. However, there are few reports onolfactoryand gustatory dysfunctions in patients with COVID-19. Objective: To investigate the incidence of olfactory and gustatory dysfunctions in patients with confirmed COVID-19 infection, in Wuhan, China. Methods: : In this retrospective study,we collected 81 confirmed cases of COVID-19 from the Renmin Hospital of Wuhan University, from February 2020 to March 2020, and analyzed the demographic characteristics, clinical manifestations (including olfactory and gustatory dysfunctions), laboratory findings,and comorbidities. Results: : A total of 81 confirmed COVID-19 patients were enrolledin this study (38 males). The most prevalent symptoms include cough, myalgia, and loss of appetite. On admission, 25 (30.9%) of all patients reported either olfactory dysfunction (OD) or gustatory dysfunction (GD), and 7 (8.6%) reported both OD and GD. 13.6% and 25.9% of allpatients reported OD and GD, respectively. OD and GD were not associated with disease severity. Pearson correlation analysisidentified some factors are positively correlated with OD and GD, including headache or dizziness (r = 0.342, P = 0.002), dark urine (r = 0.256, P = 0.021), IgM titer (r = 0.305, P = 0.01), and diabetes (r = 0.275, P = 0.013). In 81.8% of the cases with OD and 28.6% of the cases with GD, the symptomslasted for at least 1 month after discharge.3.6% of inpatients without OD developed OD after discharge. Conclusion: OD and GDare common in COVID-19.These symptoms appear early during thecourse of disease, and may last for at least 1 month.The incidence of OD and GDisrelated to neurological manifestations, diabetics, and IgM titers.

18.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-325303

ABSTRACT

Background: Exploring new ways to improve the efficiency of nursing work for patients with severe new coronavirus pneumonia. Methods A total of 372 clinical nursing shifts from February 9, 2020 to April 11, 2020 were analyzed in this study. Shifts were divided into a control group (186 shifts before reorganization) and an observation group (186 shifts after reorganization). Following improvements were applied: wearing the protective equipment, communication between inside and outside the contaminated area, and time needed to restock the bedside consumables. Results After the new method was applied, changing of protective equipment during worktime was reduced (5% (9/186) in the observation group vs. 15% (27/186) in the control group;P = 0.003). Moreover, the time needed to transfer items between inside and outside contaminated area and time for replenishment consumables for bedside treatment was shorter in the observation group compared to the control group (1.98 ± 1.41, 6.86 ± 2.25 vs. 2.52 ± 1.97, 10.81 ± 4.45, respectively;all P < 0.002). Conclusion The new applied measures have improved the nursing efficiency in patients with severe novel coronavirus pneumonia.

19.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-325099

ABSTRACT

Objectives: To analyze the findings of computed tomography (CT) imaging in critically ill patients diagnosed with coronavirus disease 2019 (COVID-19). Methods: This retrospective study reviewed 60 critically ill patients (43 males and 17 females, mean age 64.4±11.0 years) with COVID-19 pneumonia who were admitted to two different clinical centers. Their clinical and medical records were analyzed, and the chest CT images were assessed to determine the involvement of lobes and the distribution of lesions in the lungs between the patients who recovered from the illness and those who died. Results: Patients were significantly older in the death group (10/60, 16.67%) than in the recovery group (50/60, 83.33%) (p=0.044). C-reactive protein (CRP) (67.9±50.5 mg/L) was significantly elevated in the death group as opposed to the recovery group (p<0.001). The neutrophil-to-lymphocyte ratio (NLR) was higher in the death group when compared with the recovery group (p=0.030). Involvement of five lung lobes was found in 98% of the patients, with medial or parahilar area involvement observed in all the death patients. Ground-glass opacities (97%), crazy-paving pattern (92%) and air bronchogram (93%) were the most common radiological findings. Presence of emphysema was more prevalent in the death group than in the recovery group (30% vs 2%, p=0.011). Conclusions: The degree of lung involvement and lesion distribution with dominance in the medial and parahilar pulmonary areas were more severe in the death patients than in those who recovered. Patient’s age, emphysema, CRP and NLR could be combined with CT to predict the disease outcomes.

20.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-324964

ABSTRACT

Background: COVID-19 had caused more than 2.8 million deaths globally, and the epidemic will persist for an extended period of time. We analyzed clinical features of patients in the early stage of the epidemic, so as to deepen the understanding of the disease. Methods: : In this retrospective study, we included 84 confirmed cases of COVID-19 during February 1, 2020 and March 31, 2020. Baseline data were used to classify patients as moderate (57%) or severe/critical based on Chinese protocol. We focused on analyzing the differences in chest computed tomography (CT) between the two groups. Results: Of the 84 cases, 50 were male and the median age was 69 years. 55 (65%) patients had comorbidities at admission, more in the severe/critical group (P=0.040). 94% patients had bilateral lesions on CT, up to 68% had lesions involving all lobes. Ground glass opacification (GGO) (96%), consolidation (44%), Linear opacities (50%) and Air bronchogram (23%) were the mainly lesions. The lesion was gradually absorbed over time, but imaging abnormalities can persist for a long time. Compared with moderate cases, the severe/critical group had more pulmonary consolidation changes (P=0.044) and significantly higher CT severity Score (CTSS) (P=0.040). Lymphocyte counts were significantly lower (P=0.011) and NLR were higher (P=0.029) in severe/critical cases. Conclusions: : Chest CT showed bilateral and multiple GGO and consolidation mainly. After treatment, pulmonary lesions were gradually absorbed over time, and imaging abnormalities can be persistent for a long time. Lung consolidation, CTSS, comorbidity, lymphocyte counts, and NLR may be predictors of severe COVID-19.

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