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Adverse Drug Reactions Journal ; 24(4):169-174, 2022.
Article Dans Chinois | EMBASE | ID: covidwho-2302121

Résumé

Objective To explore the occurrence and influencing factors of serum uric acid elevation in patients with coronavirus disease 2019 (COVID-19) treated with favipiravir. Methods Medical records of patients with COVID-19 who were hospitalized in Beijing Ditan Hospital between June 1, 2020 and June 30, 2021 and treated with the 5- or 10-day regimen of favipiravir were collected and retrospectively analyzed. After favipiravir withdrawal, if the elevation in serum uric acid was >=30% of baseline level, it was defined as serum uric acid elevation. Then patients were divided into serum uric acid elevation group and non-serum uric acid elevation group. The clinical characteristics such as gender, age, body mass index, comorbidities, smoking and drinking behavior, COVID-19 grade, favipiravir regimen, and serum uric acid level and renal function before treatment in patients between the 2 groups were compared. Influencing factors of favipiravir-associated serum uric acid elevation was analyzed using multivariate logistic regression method. Results A total of 179 patients were included in the analysis, including 104 (58.1%) males and 75 (41.9%) females, aged from 19 to 70 years with a median age of 43 years. The level of serum uric acid in 179 patients after favipiravir treatment was significantly higher than before [(451+/-119) mumol/L vs. (332+/-94) mumol/L, P<0.001]. The change rate of serum uric acid from baseline level ranged from -57.1% to 157.8% with the median of 38.6%. The elevation in serum uric acid of >= 30% of baseline level occurred in 108 (60.3%) patients. The incidences of serum uric acid elevation in patients treated with 5-day and 10-day regi- mens of favipiravir were 46.8% (36/77) and 70.6% (72/102), respectively, and the difference between them was significant (P=0.001). Multivariate logistic regression analysis showed that body mass index 24.0 to <28.0 kg/m2 (OR=3.109, 95%CI: 1.209-7.994, P=0.019) and 10-day regimen of favipiravir (OR=3.017, 95%CI: 1.526-5.964, P=0.001) were independent risk factors for favipiravir-associated serum uric acid elevation. Conclusions More than half of COVID-19 patients treated with favipiravir can develop serum uric acid elevation. Overweight and 10-day regimen of favipiravir are independent risk factors for serum uric acid elevation in patients.Copyright © 2022 Adverse Drug Reactions Journal.

2.
Infectious Medicine ; 2023.
Article Dans Anglais | Scopus | ID: covidwho-2246699

Résumé

Background: Global evidence on the transmission of asymptomatic SARS-CoV-2 infection needs to be synthesized. Methods: A search of 4 electronic databases (PubMed, EMBASE, Cochrane Library, and Web of Science databases) as of January 24, 2021 was performed. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. Studies which reported the transmission rate among close contacts with asymptomatic SARS-CoV-2 cases were included, and transmission activities occurred were considered. The transmission rates were pooled by zero-inflated beta distribution. The risk ratios (RRs) were calculated using random-effects models. Results: Of 4923 records retrieved and reviewed, 15 studies including 3917 close contacts with asymptomatic indexes were eligible. The pooled transmission rates were 1.79 per 100 person-days (or 1.79%, 95% confidence interval [CI] 0.41%–3.16%) by asymptomatic index, which is significantly lower than by presymptomatic (5.02%, 95% CI 2.37%–7.66%;p<0.001), and by symptomatic (5.27%, 95% CI 2.40%–8.15%;p<0.001). Subgroup analyses showed that the household transmission rate of asymptomatic index was (4.22%, 95% CI 0.91%–7.52%), four times significantly higher than non-household transmission (1.03%, 95% CI 0.73%–1.33%;p=0.03), and the asymptomatic transmission rate in China (1.82%, 95% CI 0.11%–3.53%) was lower than in other countries (2.22%, 95% CI 0.67%–3.77%;p=0.01). Conclusions: People with asymptomatic SARS-CoV-2 infection are at risk of transmitting the virus to their close contacts, particularly in household settings. The transmission potential of asymptomatic infection is lower than symptomatic and presymptomatic infections. This meta-analysis provides evidence for predicting the epidemic trend and promulgating vaccination and other control measures. Registered with PROSPERO International Prospective Register of Systematic Reviews, CRD42021269446;https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=269446. © 2022 The Author(s)

3.
Adverse Drug Reactions Journal ; 24(4):169-174, 2022.
Article Dans Chinois | Scopus | ID: covidwho-1875842

Résumé

Objective To explore the occurrence and influencing factors of serum uric acid elevation in patients with coronavirus disease 2019 (COVID⁃19) treated with favipiravir. Methods Medical records of patients with COVID⁃19 who were hospitalized in Beijing Ditan Hospital between June 1, 2020 and June 30, 2021 and treated with the 5- or 10-day regimen of favipiravir were collected and retrospectively analyzed. After favipiravir withdrawal, if the elevation in serum uric acid was ≥30% of baseline level, it was defined as serum uric acid elevation. Then patients were divided into serum uric acid elevation group and non-serum uric acid elevation group. The clinical characteristics such as gender, age, body mass index, comorbidities, smoking and drinking behavior, COVID⁃19 grade, favipiravir regimen, and serum uric acid level and renal function before treatment in patients between the 2 groups were compared. Influencing factors of favipiravir⁃associated serum uric acid elevation was analyzed using multivariate logistic regression method. Results A total of 179 patients were included in the analysis, including 104 (58.1%) males and 75 (41.9%) females, aged from 19 to 70 years with a median age of 43 years. The level of serum uric acid in 179 patients after favipiravir treatment was significantly higher than before [(451±119) μmol/L vs. (332±94) μmol/L, P<0.001]. The change rate of serum uric acid from baseline level ranged from -57.1% to 157.8% with the median of 38.6%. The elevation in serum uric acid of ≥ 30% of baseline level occurred in 108 (60.3%) patients. The incidences of serum uric acid elevation in patients treated with 5-day and 10-day regi⁃ mens of favipiravir were 46.8% (36/77) and 70.6% (72/102), respectively, and the difference between them was significant (P=0.001). Multivariate logistic regression analysis showed that body mass index 24.0 to <28.0 kg/m2 (OR=3.109, 95%CI: 1.209-7.994, P=0.019) and 10-day regimen of favipiravir (OR=3.017, 95%CI: 1.526-5.964, P=0.001) were independent risk factors for favipiravir⁃associated serum uric acid elevation. Conclusions More than half of COVID⁃19 patients treated with favipiravir can develop serum uric acid elevation. Overweight and 10-day regimen of favipiravir are independent risk factors for serum uric acid elevation in patients. © 2022 Adverse Drug Reactions Journal.

4.
Computer Systems Science and Engineering ; 41(1):255-269, 2022.
Article Dans Anglais | Scopus | ID: covidwho-1527146

Résumé

Since the outbreak of the world-wide novel coronavirus pandemic, crowd counting in public areas, such as in shopping centers and in commercial streets, has gained popularity among public health administrations for preventing the crowds from gathering. In this paper, we propose a novel adaptive method for crowd counting based on Wi-Fi channel state information (CSI) by using common commercial wireless routers. Compared with previous researches on device-free crowd counting, our proposed method is more adaptive to the change of environment and can achieve high accuracy of crowd count estimation. Because the distance between access point (AP) and monitor point (MP) is typically non-fixed in real-world applications, the strength of received signals varies and makes the traditional amplitude-related models to perform poorly in different environments. In order to achieve adaptivity of the crowd count estimation model, we used convolutional neural network (ConvNet) to extract features from correlation coefficient matrix of subcarriers which are insensitive to the change of received signal strength. We conducted experiments in university classroom settings and our model achieved an overall accuracy of 97.79% in estimating a variable number of participants. © 2022 CRL Publishing. All rights reserved.

5.
Embo Journal ; 39(24):23, 2020.
Article Dans Anglais | Web of Science | ID: covidwho-1059806

Résumé

COVID-19 is characterized by dysregulated immune responses, metabolic dysfunction and adverse effects on the function of multiple organs. To understand host responses to COVID-19 pathophysiology, we combined transcriptomics, proteomics, and metabolomics to identify molecular markers in peripheral blood and plasma samples of 66 COVID-19-infected patients experiencing a range of disease severities and 17 healthy controls. A large number of expressed genes, proteins, metabolites, and extracellular RNAs (exRNAs) exhibit strong associations with various clinical parameters. Multiple sets of tissue-specific proteins and exRNAs varied significantly in both mild and severe patients suggesting a potential impact on tissue function. Chronic activation of neutrophils, IFN-I signaling, and a high level of inflammatory cytokines were observed in patients with severe disease progression. In contrast, COVID-19-infected patients experiencing milder disease symptoms showed robust T-cell responses. Finally, we identified genes, proteins, and exRNAs as potential biomarkers that might assist in predicting the prognosis of SARS-CoV-2 infection. These data refine our understanding of the pathophysiology and clinical progress of COVID-19. SYNOPSIS image Proteomics, metabolomics and RNAseq data map immune responses in COVID-19 patients with different disease severity, revealing molecular makers associated with disease progression and alterations of tissue-specific proteins. A multi-omics profiling of the host response to SARS-CoV2 infection in 66 clinically diagnosed and laboratory confirmed COVID-19 patients and 17 uninfected controls. Significant correlations between multi-omics data and key clinical parameters. Alteration of tissue-specific proteins and exRNAs. Enhanced activation of immune responses is associated with COVID-19 pathogenesis. Biomarkers to predict COVID-19 clinical outcomes pending clinical validation as prospective marker.

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