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1.
Psychol Med ; 51(11): 1952-1954, 2021 08.
Article in English | MEDLINE | ID: covidwho-1882703

ABSTRACT

BACKGROUND: Due to the drastic surge of COVID-19 patients, many countries are considering or already graduating health professional students early to aid professional resources. We aimed to assess outbreak-related psychological distress and symptoms of acute stress reaction (ASR) in health professional students and to characterize individuals with potential need for interventions. METHODS: We conducted a prospective cohort study of 1442 health professional students at Sichuan University, China. At baseline (October 2019), participants were assessed for childhood adversity, stressful life events, internet addiction, and family functioning. Using multivariable logistic regression, we examined associations of the above exposures with subsequent psychological distress and ASR in response to the outbreak. RESULTS: Three hundred and eighty-four (26.63%) participants demonstrated clinically significant psychological distress, while 160 (11.10%) met the criterion for a probable ASR. Individuals who scored high on both childhood adversity and stressful life event experiences during the past year were at increased risks of both distress (ORs 2.00-2.66) and probable ASR (ORs 2.23-3.10), respectively. Moreover, internet addiction was associated with elevated risks of distress (OR 2.05, 95% CI 1.60-2.64) and probable ASR (OR 2.15, 95% CI 1.50-3.10). By contrast, good family functioning was associated with decreased risks of distress (OR 0.43, 95% CI 0.33-0.55) and probable ASR (OR 0.48, 95% CI 0.33-0.69). All associations were independent of baseline psychological distress. CONCLUSIONS: Our findings suggest that COVID-19 related psychological distress and high symptoms burden of ASR are common among health professional students. Extended family and professional support should be considered for vulnerable individuals during these unprecedented times.


Subject(s)
COVID-19 , Psychological Distress , Stress Disorders, Traumatic, Acute/epidemiology , Students, Health Occupations/psychology , Adverse Childhood Experiences/psychology , Adverse Childhood Experiences/statistics & numerical data , Anxiety/epidemiology , Anxiety/psychology , China/epidemiology , Cohort Studies , Depression/epidemiology , Depression/psychology , Family Relations/psychology , Humans , Internet Addiction Disorder/epidemiology , Internet Addiction Disorder/psychology , Logistic Models , Multivariate Analysis , Prospective Studies , SARS-CoV-2 , Stress Disorders, Traumatic, Acute/psychology , Stress, Psychological/epidemiology , Stress, Psychological/psychology
2.
Front Cell Infect Microbiol ; 12: 882661, 2022.
Article in English | MEDLINE | ID: covidwho-1855322

ABSTRACT

We have witnessed the 2-year-long global rampage of COVID-19 caused by the wide spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, knowledge about biomarkers of the entire COVID-19 process is limited. Identification of the systemic features of COVID-19 will lead to critical biomarkers and therapeutic targets for early intervention and clinical disease course prediction. Here, we performed a comprehensive analysis of clinical measurements and serum metabolomics in 199 patients with different stages of COVID-19. In particular, our study is the first serum metabolomic analysis of critical rehabilitation patients and critical death patients. We found many differential metabolites in the comparison of metabolomic results between ordinary, severe, and critical patients and uninfected patients. Through the metabolomic results of COVID-19 patients in various stages, and critical rehabilitation patients and critical death patients, we identified a series of differential metabolites as biomarkers, a separate queue and precise distinction, and predicted COVID-19 verification. These differentially expressed metabolites, included 1,2-di-(9Z,12Z-octadecadienoyl)-sn-glycero-3-phosphate, propylparaben, 20-hydroxyeicosatetraenoic acid, triethanolamine, chavicol, disialosyl galactosyl globoside, 1-arachidonoylglycerophosphoinositol, and alpha-methylstyrene, all of which have been identified for the first time as biomarkers in COVID-19 progression. These biomarkers are involved in many pathological and physiological pathways of COVID-19, for example, immune responses, platelet degranulation, and metabolism which might result in pathogenesis. Our results showed valuable information about metabolites obviously altered in COVID-19 patients with different stages, which could shed light on the pathogenesis as well as serve as potential therapeutic agents of COVID-19.


Subject(s)
COVID-19 , Biomarkers , Humans , Immunity , Metabolomics/methods , SARS-CoV-2
4.
iScience ; 25(6): 104415, 2022 Jun 17.
Article in English | MEDLINE | ID: covidwho-1851360

ABSTRACT

COVID-19 outbreaks have crushed our healthcare systems, which requires clinical guidance for the healthcare following the outbreaks. We conducted retrospective cohort studies with Pearson's pattern-based analysis of clinical parameters of 248 hospitalized patients with COVID-19. We found that dysregulated neutrophil densities were correlated with hospitalization duration before death (p = 0.000066, r = -0.45 for % neutrophil; p = 0.0001, r = -0.47 for neutrophil count). As such, high neutrophil densities were associated with mortality (p = 4.23 × 10-31 for % neutrophil; p = 4.14 × 10-27 for neutrophil count). These findings were further illustrated by a representative "second week crash" pattern and validated by an independent cohort (p = 5.98 × 10-11 for % neutrophil; p = 1.65 × 10-7 for neutrophil count). By contrast, low aspartate aminotransferase (AST) or lactate dehydrogenase (LDH) levels were correlated with quick recovery (p ≤ 0.00005). Collectively, these correlational at-admission findings may provide healthcare guidance for patients with COVID-19 in the absence of targeted therapy.

5.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-334346

ABSTRACT

Background: Previous studies demonstrate a reduced risk of thrombosis and mortality with anticoagulant treatment in patients with COVID-19 than those without anticoagulation treatment. However, an open question regarding the efficacy and safety of therapeutic anticoagulation (T-AC) versus a lower dose, prophylaxis anticoagulation (P-AC) in COVID-19 patients is still controversial. Methods: : We systematically reviewed currently available randomized clinical trials (RCTs) and observational studies (OBs) from January 8, 2019, to January 8, 2022, and compared prophylactic and therapeutic anticoagulant treatment in COVID-19 patients. The primary outcomes were risk of mortality, major bleeding, and the secondary outcomes included venous and arterial thromboembolism. Subgroup analysis was also performed between critically ill and non-critically ill patients with COVID-19 and between patients with higher and lower levels of D-dimer. Sensitive analysis was performed to decrease the bias and the impact of population heterogeneity. Results: : We identified 11 RCTs and 17 OBs fulfilling our inclusion criteria. In the RCTs analyses, there was no statistically significant difference in the relative risk of mortality between COVID-19 patients with T-AC treatment and those treated with P-AC (RR 0.95, 95% CI, 0.78–1.16, P = 0.61). Similar results were also found in the OBs analyses (RR 1.21, 95% CI, 0.98-1.49, P = 0.08). The pooling meta-analysis using a random-effects model combined with effect sizes showed that in the RCTs and OBs analyses, patients with COVID-19 who received T-AC treatment had a significantly higher relative risk of the major bleeding event than those with P-AC treatment in COVID-19 patients (RCTs: RR 1.76, 95% CI, 1.19-2.62, P = 0.005;OBs: RR 2.39, 95% CI, 1.56-3.68, P < 0.0001). Compared with P-AC treatment in COVID-19 patients, patients with T-AC treatment significantly reduced the incidence of venous thromboembolism (RR 0.51, 95%, 0.39-0.67, P <0.00001), but it is not associated with arterial thrombosis events (RR 0.97, 95%, 0.66-1.42, P = 0.88). The subgroup analysis of OBs shows that the mortality risk significantly reduces in critically ill COVID-19 patients treated with T-AC compared with those with P-AC treatment (RR 0.58, 95% CI, 0.39-0.86, P = 0.007), while the mortality risk significantly increases in non-critically ill COVID-19 patients treated with T-AC (RR 1.56, 95% CI, 1.34-1.80, P < 0.00001). In addition, T-AC treatment does not reduce the risk of mortality in COVID-19 patients with high d-dimer levels in RCTs. Finally, the overall sensitivity analysis after excluding two RCTs studies remains consistent with the previous results. Conclusions: : A comprehensive meta-analysis of OBs demonstrated that T-AC treatment in critically ill patients with COVID-19 significantly increased survival compared with those treated with P-AC, which was not found in the RCTs analyses. Meanwhile, P-AC treatment showed survival superiority in non-critically ill patients with COVID-19. In both RCTs and OBs, T-AC treatment in COVID-19 patients significantly reduced the incidence of venous thromboembolism but showed a higher risk of bleeding than those with P-AC treatment. Protocol registration PROSPERO (CRD42021293294). Registered 24 November 2021.

6.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-334172

ABSTRACT

BACKGROUND Viral persistence is a crucial factor that influences the communicability of SARS-CoV-2 infection. However, the impacts of vaccination status and physiological variables on viral RNA shedding have not been adequately clarified. METHODS In this study, we retrospectively collected the clinical records of 377 hospitalized COVID-19 patients, which contained unvaccinated patients and patients received two doses of an inactivated vaccine or an mRNA vaccine. Firstly, we analyzed the impacts of vaccination on disease severity and viral RNA persistence. Next, to clarify the impacts of physiological variables on viral RNA shedding in COVID-19 patients, we retrieved 49 laboratory variables and analyzed their correlations with the duration of viral RNA shedding. Finally, we established a multivariate regression model to predict the duration of viral RNA shedding. RESULTS Our results showed that both inactivated and mRNA vaccines significantly reduced the rate of moderate cases, while the vaccine related shortening of viral RNA shedding were only observed in moderate patients. Correlation analysis showed that 10 significant laboratory variables were shared by the unvaccinated mild patients and mild patients inoculated with an inactivated vaccine, but not by the mild patients inoculated with an mRNA vaccine. Moreover, we demonstrated that a multivariate regression model established based on the variables correlating with viral persistence in unvaccinated mild patients could predict the duration of viral shedding for all groups of patients. CONCLUSIONS Vaccination contributed limitedly to the clearance viral RNA in COVID-19 patients. While, laboratory variables in early infection could predict the persistence of viral RNA.

7.
Preprint in English | medRxiv | ID: ppmedrxiv-22273860

ABSTRACT

BACKGROUNDViral persistence is a crucial factor that influences the communicability of SARS-CoV-2 infection. However, the impacts of vaccination status and physiological variables on viral RNA shedding have not been adequately clarified. METHODSIn this study, we retrospectively collected the clinical records of 377 hospitalized COVID-19 patients, which contained unvaccinated patients and patients received two doses of an inactivated vaccine or an mRNA vaccine. Firstly, we analyzed the impacts of vaccination on disease severity and viral RNA persistence. Next, to clarify the impacts of physiological variables on viral RNA shedding in COVID-19 patients, we retrieved 49 laboratory variables and analyzed their correlations with the duration of viral RNA shedding. Finally, we established a multivariate regression model to predict the duration of viral RNA shedding. RESULTSOur results showed that both inactivated and mRNA vaccines significantly reduced the rate of moderate cases, while the vaccine related shortening of viral RNA shedding were only observed in moderate patients. Correlation analysis showed that 10 significant laboratory variables were shared by the unvaccinated mild patients and mild patients inoculated with an inactivated vaccine, but not by the mild patients inoculated with an mRNA vaccine. Moreover, we demonstrated that a multivariate regression model established based on the variables correlating with viral persistence in unvaccinated mild patients could predict the duration of viral shedding for all groups of patients. CONCLUSIONSVaccination contributed limitedly to the clearance viral RNA in COVID-19 patients. While, laboratory variables in early infection could predict the persistence of viral RNA.

8.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-331424

ABSTRACT

Background: The emergence of COVID-19 brought unparalleled changes in peoples lifestyle, including sleep. We aimed to assess the bidirectional association between sleep quality and mental health and describe how sleep and mental health were affected in Sweden during the COVID-19 pandemic (between June 2020 and September 2021). Methods: Data were obtained from the Omtanke2020 study. Participants who completed the baseline survey and 8 monthly follow-up surveys were included (N=9035). We described the distribution of sleep and mental health in the different Swedish regions using maps and over the study period with longitudinal graphs adjusting for sex, age, recruitment type (self-recruitment or invitation), and COVID-19 status. The inner relationships between mental health, sleep and covid infection were described through relative importance networks. Finally, we modelled how mental health affects sleep and vice versa using generalized estimating equations with different adjustments. Results: Seasonal and north-south regional variations were found in sleep and mental health outcomes at baseline and attenuated over time. The seasonal variation of sleep and mental health correlated moderately with the incidence rate of COVID-19 in the sample. Networks indicate that the relationship between COVID-19 incidence and mental health varies over time. We observed a bidirectional relationship between sleep quality and quantity at baseline and mental health at follow-up and vice versa. Conclusion: Sleep quality and quantity at baseline was associated with adverse symptom trajectories of mental health at follow-up, and vice versa, during the COVID-19 pandemic. There is also a weak relationship between COVID-19 incidence, sleep, and mental health.

9.
Preprint in English | medRxiv | ID: ppmedrxiv-22273027

ABSTRACT

BackgroundThe emergence of COVID-19 brought unparalleled changes in peoples lifestyle, including sleep. We aimed to assess the bidirectional association between sleep quality and mental health and describe how sleep and mental health were affected in Sweden during the COVID-19 pandemic (between June 2020 and September 2021). MethodsData were obtained from the Omtanke2020 study. Participants who completed the baseline survey and 8 monthly follow-up surveys were included (N=9035). We described the distribution of sleep and mental health in the different Swedish regions using maps and over the study period with longitudinal graphs adjusting for sex, age, recruitment type (self-recruitment or invitation), and COVID-19 status. The inner relationships between mental health, sleep and covid infection were described through relative importance networks. Finally, we modelled how mental health affects sleep and vice versa using generalized estimating equations with different adjustments. ResultsSeasonal and north-south regional variations were found in sleep and mental health outcomes at baseline and attenuated over time. The seasonal variation of sleep and mental health correlated moderately with the incidence rate of COVID-19 in the sample. Networks indicate that the relationship between COVID-19 incidence and mental health varies over time. We observed a bidirectional relationship between sleep quality and quantity at baseline and mental health at follow-up and vice versa. ConclusionSleep quality and quantity at baseline was associated with adverse symptom trajectories of mental health at follow-up, and vice versa, during the COVID-19 pandemic. There is also a weak relationship between COVID-19 incidence, sleep, and mental health.

10.
Lancet Public Health ; 7(5): e406-e416, 2022 05.
Article in English | MEDLINE | ID: covidwho-1740344

ABSTRACT

BACKGROUND: Long-term mental and physical health consequences of COVID-19 (long COVID) are a persistent public health concern. Little is still known about the long-term mental health of non-hospitalised patients with COVID-19 with varying illness severities. Our aim was to assess the prevalence of adverse mental health symptoms among individuals diagnosed with COVID-19 in the general population by acute infection severity up to 16 months after diagnosis. METHODS: This observational follow-up study included seven prospectively planned cohorts across six countries (Denmark, Estonia, Iceland, Norway, Sweden, and the UK). Participants were recruited from March 27, 2020, to Aug 13, 2021. Individuals aged 18 years or older were eligible to participate. In a cross-sectional analysis, we contrasted symptom prevalence of depression, anxiety, COVID-19-related distress, and poor sleep quality (screened with validated mental health instruments) among individuals with and without a diagnosis of COVID-19 at entry, 0-16 months from diagnosis. In a cohort analysis, we further used repeated measures to estimate the change in mental health symptoms before and after COVID-19 diagnosis. FINDINGS: The analytical cohort consisted of 247 249 individuals, 9979 (4·0%) of whom were diagnosed with COVID-19 during the study period. Mean follow-up was 5·65 months (SD 4·26). Participants diagnosed with COVID-19 presented overall with a higher prevalence of symptoms of depression (prevalence ratio [PR] 1·18 [95% CI 1·03-1·36]) and poorer sleep quality (1·13 [1·03-1·24]) but not symptoms of anxiety (0·97 [0·91-1·03]) or COVID-19-related distress (1·05 [0·93-1·20]) compared with individuals without a COVID-19 diagnosis. Although the prevalence of depression and COVID-19-related distress attenuated with time, individuals diagnosed with COVID-19 but never bedridden due to their illness were consistently at lower risk of depression (PR 0·83 [95% CI 0·75-0·91]) and anxiety (0·77 [0·63-0·94]) than those not diagnosed with COVID-19, whereas patients who were bedridden for more than 7 days were persistently at higher risk of symptoms of depression (PR 1·61 [95% CI 1·27-2·05]) and anxiety (1·43 [1·26-1·63]) than those not diagnosed throughout the study period. INTERPRETATION: Severe acute COVID-19 illness-indicated by extended time bedridden-is associated with long-term mental morbidity among recovering individuals in the general population. These findings call for increased vigilance of adverse mental health development among patients with a severe acute disease phase of COVID-19. FUNDING: Nordforsk, Horizon2020, Wellcome Trust, and Estonian Research Council.


Subject(s)
COVID-19 , COVID-19/complications , COVID-19/epidemiology , COVID-19 Testing , Cross-Sectional Studies , Follow-Up Studies , Humans , Mental Health , Morbidity
11.
Med Phys ; 49(5): 3213-3222, 2022 May.
Article in English | MEDLINE | ID: covidwho-1729178

ABSTRACT

PURPOSE: To develop a deep learning model design that integrates radiomics analysis for enhanced performance of COVID-19 and non-COVID-19 pneumonia detection using chest x-ray images. METHODS: As a novel radiomics approach, a 2D sliding kernel was implemented to map the impulse response of radiomic features throughout the entire chest x-ray image; thus, each feature is rendered as a 2D map in the same dimension as the x-ray image. Based on each of the three investigated deep neural network architectures, including VGG-16, VGG-19, and DenseNet-121, a pilot model was trained using x-ray images only. Subsequently, two radiomic feature maps (RFMs) were selected based on cross-correlation analysis in reference to the pilot model saliency map results. The radiomics-boosted model was then trained based on the same deep neural network architecture using x-ray images plus the selected RFMs as input. The proposed radiomics-boosted design was developed using 812 chest x-ray images with 262/288/262 COVID-19/non-COVID-19 pneumonia/healthy cases, and 649/163 cases were assigned as training-validation/independent test sets. For each model, 50 runs were trained with random assignments of training/validation cases following the 7:1 ratio in the training-validation set. Sensitivity, specificity, accuracy, and ROC curves together with area-under-the-curve (AUC) from all three deep neural network architectures were evaluated. RESULTS: After radiomics-boosted implementation, all three investigated deep neural network architectures demonstrated improved sensitivity, specificity, accuracy, and ROC AUC results in COVID-19 and healthy individual classifications. VGG-16 showed the largest improvement in COVID-19 classification ROC (AUC from 0.963 to 0.993), and DenseNet-121 showed the largest improvement in healthy individual classification ROC (AUC from 0.962 to 0.989). The reduced variations suggested improved robustness of the model to data partition. For the challenging non-COVID-19 pneumonia classification task, radiomics-boosted implementation of VGG-16 (AUC from 0.918 to 0.969) and VGG-19 (AUC from 0.964 to 0.970) improved ROC results, while DenseNet-121 showed a slight yet insignificant ROC performance reduction (AUC from 0.963 to 0.949). The achieved highest accuracy of COVID-19/non-COVID-19 pneumonia/healthy individual classifications were 0.973 (VGG-19)/0.936 (VGG-19)/ 0.933 (VGG-16), respectively. CONCLUSIONS: The inclusion of radiomic analysis in deep learning model design improved the performance and robustness of COVID-19/non-COVID-19 pneumonia/healthy individual classification, which holds great potential for clinical applications in the COVID-19 pandemic.


Subject(s)
COVID-19 , Deep Learning , COVID-19/diagnostic imaging , Humans , Pandemics , SARS-CoV-2 , X-Rays
12.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-329553

ABSTRACT

Importance The role of COVID-19 vaccination on the mental health of the general population remains poorly understood. Objective To assess the short-term change of depressive and anxiety symptoms in relation to COVID-19 vaccination among Swedish adults. Design A prospective cohort study with monthly data collections on self-reported depressive and anxiety symptoms from December 2020 to October 2021 and COVID-19 vaccination from July to October 2021. Setting The Omtanke2020 Study, Sweden. Participants 7,925 participants of the Omtanke2020 study with complete data on depressive and anxiety symptoms and vaccination status. Intervention(s) or Exposure(s) Receiving the first or second dose of a COVID-19 vaccine. Main outcomes(s) and Measure(s) Binary measures of depression (PHQ-9, cut-off ≥10) and anxiety (GAD-7, cut-off ≥10) one month before the first dose, one month after the first dose, and, if applicable, one month after the second dose. For individuals not vaccinated or chose to not report vaccination status (unvaccinated individuals), we selected three monthly measures of PHQ-9 and GAD-7 with 2-month intervals in-between based on data availability. Results 5,079 (64.1%) individuals received two doses of COVID-19 vaccine, 1,977 (24.9%) received one dose, 305 (3.9%) were not vaccinated, and 564 (7.1%) chose not to report vaccination status. There was a lower prevalence of depression and anxiety among vaccinated, compared with unvaccinated, individuals, especially after the second dose. Among individuals receiving two doses of vaccine, the prevalence of depression and anxiety was lower after both first (aRR=0.82, 95%CI 0.76-0.88 for depression;aRR=0.81, 95%CI 0.73-0.89 for anxiety) and second (aRR=0.79, 95%CI 0.73-0.85 for depression;aRR=0.73, 95%CI 0.66-0.81 for anxiety) dose, compared with before vaccination. Similar results were observed among individuals receiving only one dose (aRR=0.76, 95%CI 0.68-0.84 for depression;aRR=0.82, 95%CI 0.72-0.94 for anxiety, comparing after first dose to before vaccination). These results were independent of age, sex, recruitment type, body mass index, smoking, relationship status, history of psychiatric disorder, number of comorbidities, COVID-19 infection status, and seasonality. Conclusions and Relevance We observed a positive short-term change in depressive and anxiety symptoms among adults receiving a COVID-19 vaccine in the current pandemic. Key points Question Is COVID-19 vaccination associated with a short-term change in mental health? Findings This longitudinal study included 7,925 Swedish adults with self-reported COVID-19 vaccination and symptoms of mental health responding from December 2020 to October 2021. The prevalence of depressive or anxiety symptoms was lower one month after vaccination compared to one month before vaccination. The effect size was greater among individuals receiving two doses of vaccine, compared with those receiving only one dose. Meaning Receiving vaccination against COVID-19 is associated with short-term improvement in mental health.

13.
Preprint in English | medRxiv | ID: ppmedrxiv-22271327

ABSTRACT

ImportanceThe role of COVID-19 vaccination on the mental health of the general population remains poorly understood. ObjectiveTo assess the short-term change of depressive and anxiety symptoms in relation to COVID-19 vaccination among Swedish adults. DesignA prospective cohort study with monthly data collections on self-reported depressive and anxiety symptoms from December 2020 to October 2021 and COVID-19 vaccination from July to October 2021. SettingThe Omtanke2020 Study, Sweden. Participants7,925 participants of the Omtanke2020 study with complete data on depressive and anxiety symptoms and vaccination status. Intervention(s) or Exposure(s)Receiving the first or second dose of a COVID-19 vaccine. Main outcomes(s) and Measure(s)Binary measures of depression (PHQ-9, cut-off [≥]10) and anxiety (GAD-7, cut-off [≥]10) one month before the first dose, one month after the first dose, and, if applicable, one month after the second dose. For individuals not vaccinated or chose to not report vaccination status (unvaccinated individuals), we selected three monthly measures of PHQ-9 and GAD-7 with 2-month intervals in-between based on data availability. Results5,079 (64.1%) individuals received two doses of COVID-19 vaccine, 1,977 (24.9%) received one dose, 305 (3.9%) were not vaccinated, and 564 (7.1%) chose not to report vaccination status. There was a lower prevalence of depression and anxiety among vaccinated, compared with unvaccinated, individuals, especially after the second dose. Among individuals receiving two doses of vaccine, the prevalence of depression and anxiety was lower after both first (aRR=0.82, 95%CI 0.76-0.88 for depression; aRR=0.81, 95%CI 0.73-0.89 for anxiety) and second (aRR=0.79, 95%CI 0.73-0.85 for depression; aRR=0.73, 95%CI 0.66-0.81 for anxiety) dose, compared with before vaccination. Similar results were observed among individuals receiving only one dose (aRR=0.76, 95%CI 0.68-0.84 for depression; aRR=0.82, 95%CI 0.72-0.94 for anxiety, comparing after first dose to before vaccination). These results were independent of age, sex, recruitment type, body mass index, smoking, relationship status, history of psychiatric disorder, number of comorbidities, COVID-19 infection status, and seasonality. Conclusions and RelevanceWe observed a positive short-term change in depressive and anxiety symptoms among adults receiving a COVID-19 vaccine in the current pandemic. Key pointsO_ST_ABSQuestionC_ST_ABSIs COVID-19 vaccination associated with a short-term change in mental health? FindingsThis longitudinal study included 7,925 Swedish adults with self-reported COVID-19 vaccination and symptoms of mental health responding from December 2020 to October 2021. The prevalence of depressive or anxiety symptoms was lower one month after vaccination compared to one month before vaccination. The effect size was greater among individuals receiving two doses of vaccine, compared with those receiving only one dose. MeaningReceiving vaccination against COVID-19 is associated with short-term improvement in mental health.

14.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-325015

ABSTRACT

Background: Sepsis-associated acute lung injury (ALI) is a potentially lethal complication associated with a poor prognosis and high mortality worldwide, especially in the outbreak of COVID-19. However, the fundamental mechanisms of this complication were still not fully elucidated. Thus, we conducted this study to identify hub genes and biological pathways of sepsis-associated ALI, mainly focus on two pathways of LPS and HMGB1. Methods: : Gene expression profile GSE3037 were downloaded from Gene Expression Omnibus (GEO) database, including 8 patients with sepsis-induced acute lung injury, with 8 unstimulated blood neutrophils, 8 LPS- induced neutrophils and 8 HMGB1-induced neutrophils. Differentially expressed genes (DEGs) identifications, Gene Ontology (GO) function analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis, Gene Set Enrichment Analysis (GSEA) and protein-protein interaction (PPI) network constructions were performed to obtain hub genes and relevant biological pathways. Results: : We identified 534 and 317 DEGs for LPS- and HMGB1-induced ALI, respectively. The biological pathways involved in LPS- and HMGB1-induced ALI were also identified accordingly. By PPI network analysis, we found that ten hub genes for LPS-induced ALI (CXCL8, TNF, IL6, IL1B, ICAM1, CXCL1, CXCL2, IL1A, IL1RN and CXCL3) and another ten hub genes for HMGB1-induced ALI (CCL20, CXCL2, CXCL1, CCL4, CXCL3, CXCL9, CCL21, CXCR6, KNG1 and SST). Furthermore, by combining analysis, the results revealed that genes of TNF, CCL20, IL1B, NFKBIA, CCL4, PTGS2, TNFAIP3, CXCL2, CXCL1 and CXCL3 were potential biomarkers for sepsis-associated ALI. Conclusions: : Our study revealed that ten hub genes associated with sepsis-induced ALI were TNF, CCL20, IL1B, NFKBIA, CCL4, PTGS2, TNFAIP3, CXCL2, CXCL1 and CXCL3, which may serve as genetic biomarkers and be further verified in prospective experimental trials.

15.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-323765

ABSTRACT

Background: Coronavirus disease 2019 (COVID-19) has affected over 100 countries thus far. The increasing number of patients might lead to enormous changes in psychological status of medical staff. Aims: The aim of this study was to understand the psychological status of medical staff during the COVID-19 outbreak. Method: Medical staff working in hospitals in Wuhan and the Yangtze River Delta were invited to complete an online questionnaire, which was composed of basic demographic data, the Athens Insomnia Scale (AIS) for sleep disturbances, the Generalized Anxiety Disorder (GAD-7) for anxiety, and the Self-Rating Depression Scale (SDS) for depressive symptoms. Results: Among the 1225 invited medical staff, 686 participants (64 males, 9.33% and 622 females, 90.67%;average age 33.13±7.82 years) responded to the survey (response rate was 56.00%). 482 (67.35%) respondents reported sleep disturbances, 224 (32.65%) reported anxiety and 204 (29.74%) reported depressive symptoms. Multivariable linear regression analysis showed that occupation (doctor), department (respiratory, ICU), workplace (areas in Wuhan), marital status (married), and medical history (anxiety, depression or sleep disorders) were significantly correlated with AIS, GAD-7 and SDS scores (P<0.01). Conclusions: COVID-19 imposes a significant burden on mental health of medical staff. Gender, marital status, occupation, department, workplace and a specific medical history were major influencing factors for sleep disorders, anxiety and depressive symptoms among these front-line medical staff. More attention needs to be paid to the psychological care of medical staff during the COVID-19 pandemic.Funding Statement: None.Declaration of Interests: The authors declare that they have no competing interests.Ethics Approval Statement: The ethics committee of Shanghai General Hospital approved this study, under the principles of voluntary participation, anonymity and strict confidentiality. When participants chose to complete the survey, their consent was presumed.

16.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-319163

ABSTRACT

It is shown how the secondary structure of proteins, musical forms and verses of poems are approximately ruled by universal laws relying on graph coverings. In this direction, one explores the group structure of a variant of the SARS-Cov-2 spike protein and the group structure of apolipoprotein-H, passing from the primary code with amino acids to the secondary structures organizing the foldings. Then one look at the musical forms employed in the classical and contemporary periods. Finally, one investigates in much detail the group structure of a small poem in prose by Charles Baudelaire and that of the Bateau Ivre by Arthur Rimbaud.

17.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-315212

ABSTRACT

Background: Multiorgan damage by SARS-CoV-2 results in alterations of many clinical measures associated with mortality of COVID-19. This research discussed the pioneering pathogenicity factors that lead to the extensive damage elusive. Objectives: A cohort of COVID-19 patients. Methods: : We conducted a correlational analysis of hospital outcomes with an independent cohort of COVID-19 patients and we also presented a death case to illustrate for time course of immune cell density. Results: : The results showed that dysregulated immune cell densities were correlated with hospitalization duration before death, not before discharge. High neutrophil densities allowed sorting out one third of total death cases while a density of less than 70% of the white blood cells allowed sorting out 70% of surviving cases. Conclusion: Collectively surged neutrophil was a top trigger for mortality in patients with COVID-19.

18.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-315211

ABSTRACT

Background: Worldwide spread of the novel coronavirus disease 2019 (COVID-19) has made hundreds of thousands people sick and fortunately many of them have been treated and discharged. However, it remains unclear how well the discharged patients were recovering. Chest CT scan, with demonstrated high sensitivity to COVID-19, was used here to examine clinical manifestations in patients at discharge. Methods: This study registered retrospectively single-center case series of 180 discharged patients, all confirmed with COVID-19 at Wuhan Red Cross Hospital in Wuhan, China. Epidemiological, demographic, clinical, laboratory and treatment data were collected. CT imaging features of absorption vs progressive stage were compared and analyzed. Results: Five pulmonary lobes were affected in 54 (30%) of the 180 patients at the absorption stage, comparing to 66% of them at the progressive stage ( P=1.45×10 -11 ). Forty five (25%) patients had pleural effusion on admission and 13 of them still carried hydrothorax when discharged as per standard discharge criteria( P=4.48×10 -6 ). Besides, compared with those at progressive stage, 97 (54%) discharged patients had interlobular thickening ( P=6.95×10 -3 ) and 43% of them still presented adjacent pleura thickening ( P=5.58×10 -5 ). The median total CT score of discharged patients at absorption stage was lower than progressive stage (3 vs 12.5 ). The median total CT score recovery rate was 67% (range, 0-100%) and 139 (77%) patients showed less than 90% improvement at discharge. Conclusions: A majority (77%) of the discharged patients had not recovered completely. The current discharge criteria may need to include 90% or higher CT score-based recovery rate.Authors Jingwen Li, Xi Long, Fang Fang, and Xuefei Lv contributed equally to this work.Authors Zhicheng Lin and Nian Xiong are joint last coauthors.

19.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-312678

ABSTRACT

To develop a deep-learning model that integrates radiomics analysis for enhanced performance of COVID-19 and Non-COVID-19 pneumonia detection using chest X-ray image, two deep-learning models were trained based on a pre-trained VGG-16 architecture: in the 1st model, X-ray image was the sole input;in the 2nd model, X-ray image and 2 radiomic feature maps (RFM) selected by the saliency map analysis of the 1st model were stacked as the input. Both models were developed using 812 chest X-ray images with 262/288/262 COVID-19/Non-COVID-19 pneumonia/healthy cases, and 649/163 cases were assigned as training-validation/independent test sets. In 1st model using X-ray as the sole input, the 1) sensitivity, 2) specificity, 3) accuracy, and 4) ROC Area-Under-the-Curve of COVID-19 vs Non-COVID-19 pneumonia detection were 1) 0.90$\pm$0.07 vs 0.78$\pm$0.09, 2) 0.94$\pm$0.04 vs 0.94$\pm$0.04, 3) 0.93$\pm$0.03 vs 0.89$\pm$0.03, and 4) 0.96$\pm$0.02 vs 0.92$\pm$0.04. In the 2nd model, two RFMs, Entropy and Short-Run-Emphasize, were selected with their highest cross-correlations with the saliency maps of the 1st model. The corresponding results demonstrated significant improvements (p<0.05) of COVID-19 vs Non-COVID-19 pneumonia detection: 1) 0.95$\pm$0.04 vs 0.85$\pm$0.04, 2) 0.97$\pm$0.02 vs 0.96$\pm$0.02, 3) 0.97$\pm$0.02 vs 0.93$\pm$0.02, and 4) 0.99$\pm$0.01 vs 0.97$\pm$0.02. The reduced variations suggested a superior robustness of 2nd model design.

20.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-310721

ABSTRACT

Background: There are growing evidence demonstrating that coronavirus disease 2019 (COVID-19) is companied by acute myocardial injury. However, the association of SARS-CoV-2-induced myocardial injury with death risk of COVID-19 is unclear. Methods: : This prospective case-cohort study analyzed 355 COVID-19 patients from two hospitals in different regions. Clinical and demographic information were collected. Myocardial injury was evaluated and its prognosis was followed up. Results: Of 355 hospitalized patients with COVID-19, 213 were mild, 90 severe and 52 critically ill patients. On admission, 220 (62.0%) patients were with myocardial injury. Myocardial injury was more popular in critically ill patients. Using multivariate logistic regression, male, older age and comorbidity with hypertension were three crucial independent risk factors predicting myocardial injury of COVID-19 patients. Among 220 COVID-19 patients with myocardial injury, 33 (15.0%) died on mean 10.9 day after hospitalization. Mortality was increased among COVID-19 patients with myocardial injury (15.0% vs 1.74%, RR =8.625, P <0.001). Follow-up study observed that at least one myocardial index of 21.3% patients remained abnormal 14 days after discharge. Conclusion: Myocardial injury at early stage elevates mortality of COVID-19 patients. Male elderly patients with hypertension are more vulnerable to myocardial injury. SARS-CoV-2-induced myocardial injury has not completely recovered 14 days after discharge.

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