The Association Between Inhaled Corticosteroid and the Risks of SARS-COV-2 infection: A systematic review and meta-analysis

Background The effect of inhaled corticosteroid (ICS) on the risk of severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) infection is unclear. Methods We performed a systematic review and meta-analysis of clinical studies that assessed the association between the use of ICS and the risk of SARS-COV-2 infection. PubMed, Web of Science, Scopus, Cochrane Library and Google Scholar were searched to January 1st, 2023. ROBINS-I was used to assess risk of bias of included studies. The outcome of interest was the risk of SARS-COV-2 infection in patients and odds ratio (OR) with 95% confidence interval (95% CI) were calculated using Comprehensive Meta-analysis software version 3. Results Twelve studies involving seven observational cohort studies, three case-control studies, and two cross-sectional studies were included in this meta-analysis. Overall, compared to non-ICS use, the pooled odds ratio (OR) of the risk of SARS-COV-2 infection was 0.997 (95% confidence interval [CI] 0.664-1.499;p=0.987) for patients with ICS use. Subgroup analyses demonstrated no statistical significance in the increased risk of SARS-COV-2 infection in patients with ICS monotherapy or in combination with bronchodilators (pooled OR=1.408;95% CI=0.693-2.858;p=0.344 in ICS monotherapy, and pooled OR=1.225;95% CI=0.533-2.815;p=0.633 in ICS combination, respectively). In addition, no significant association was observed between ICS use and the risk of SARS-COV-2 infection for patients with COPD (pooled OR=0.715;95% CI=0.415-1.230;p=0.225) and asthma (pooled OR=1.081;95% CI=0.970-1.206;p=0.160). Conclusions The use of ICS, either monotherapy or in combination with bronchodilators, does not have impact on the risk of SARS-COV-2 infection. Data availability The datasets used and analysed in the current study are available from the corresponding author on reasonable request.

The association between inhaled corticosteroid and the risks of SARS-COV-2 infection: A systematic review and meta-analysis.

BACKGROUND: The effect of inhaled corticosteroid (ICS) on the risk of severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) infection is unclear. METHODS: We performed a systematic review and meta-analysis of clinical studies that assessed the association between the use of ICS and the risk of SARS-COV-2 infection. PubMed, Web of Science, Scopus, Cochrane Library and Google Scholar were searched to January 1st, 2023. ROBINS-I was used to assess risk of bias of included studies. The outcome of interest was the risk of SARS-COV-2 infection in patients and odds ratio (OR) with 95% confidence interval (95% CI) were calculated using Comprehensive Meta-analysis software version 3. RESULTS: Twelve studies involving seven observational cohort studies, three case-control studies, and two cross-sectional studies were included in this meta-analysis. Overall, compared to non-ICS use, the pooled odds ratio (OR) of the risk of SARS-COV-2 infection was 0.997 (95% confidence interval [CI] 0.664-1.499; p = 0.987) for patients with ICS use. Subgroup analyses demonstrated no statistical significance in the increased risk of SARS-COV-2 infection in patients with ICS monotherapy or in combination with bronchodilators (pooled OR=1.408; 95% CI=0.693-2.858; p = 0.344 in ICS monotherapy, and pooled OR=1.225; 95% CI=0.533-2.815; p = 0.633 in ICS combination, respectively). In addition, no significant association was observed between ICS use and the risk of SARS-COV-2 infection for patients with COPD (pooled OR=0.715; 95% CI=0.415-1.230; p = 0.225) and asthma (pooled OR=1.081; 95% CI=0.970-1.206; p = 0.160). CONCLUSIONS: The use of ICS, either monotherapy or in combination with bronchodilators, does not have impact on the risk of SARS-COV-2 infection.

A Robust Design-Based Expert System for Feature Selection and COVID-19 Pandemic Prediction in Japan.

Expert systems are frequently used to make predictions in various areas. However, the practical robustness of expert systems is not as good as expected, mainly due to the fact that finding an ideal system configuration from a specific dataset is a challenging task. Therefore, how to optimize an expert system has become an important issue of research. In this paper, a new method called the robust design-based expert system is proposed to bridge this gap. The technical process of this system consists of data initialization, configuration generation, a genetic algorithm (GA) framework for feature selection, and a robust mechanism that helps the system find a configuration with the highest robustness. The system will finally obtain a set of features, which can be used to predict a pandemic based on given data. The robust mechanism can increase the efficiency of the system. The configuration for training is optimized by means of a genetic algorithm (GA) and the Taguchi method. The effectiveness of the proposed system in predicting epidemic trends is examined using a real COVID-19 dataset from Japan. For this dataset, the average prediction accuracy was 60%. Additionally, 10 representative features were also selected, resulting in a selection rate of 67% with a reduction rate of 33%. The critical features for predicting the epidemic trend of COVID-19 were also obtained, including new confirmed cases, ICU patients, people vaccinated, population, population density, hospital beds per thousand, middle age, aged 70 or older, and GDP per capital. The main contribution of this paper is two-fold: Firstly, this paper has bridged the gap between the pandemic research and expert systems with robust predictive performance. Secondly, this paper proposes a feature selection method for extracting representative variables and predicting the epidemic trend of a pandemic disease. The prediction results indicate that the system is valuable to healthcare authorities and can help governments get hold of the epidemic trend and strategize their use of healthcare resources.

The Clinical Efficacy and Safety of Anti-Viral Agents for Non-Hospitalized Patients with COVID-19: A Systematic Review and Network Meta-Analysis of Randomized Controlled Trials.

This network meta-analysis compared the clinical efficacy and safety of anti-viral agents for the prevention of disease progression among non-hospitalized patients with COVID-19. PubMed, Embase, Web of Science, Cochrane Library, ClinicalTrials.gov and the WHO International Clinical Trials Registry Platform were searched from their inception to 28 May 2022. Only randomized controlled trials (RCTs) that investigated the clinical efficacy of anti-viral agents for non-hospitalized patients with COVID-19 were included. Three RCTs involving 4241 patients were included. Overall, anti-viral agents were associated with a significantly lower risk of COVID-19 related hospitalization or death compared with the placebo (OR, 0.23; 95% CI: 0.06-0.96; p = 0.04). Compared with the placebo, patients receiving nirmatrelvir plus ritonavir had the lowest risk of hospitalization or death (OR, 0.12; 95% CI: 0.06-0.24), followed by remdesivir (OR, 0.13; 95% CI: 0.03-0.57) and then molnupiravir (OR, 0.67; 95% CI: 0.46-0.99). The rank probability for each treatment calculated using the P-score revealed that nirmatrelvir plus ritonavir was the best anti-viral treatment, followed by remdesivir and then molnupiravir. Finally, anti-viral agents were not associated with an increased risk of adverse events compared with the placebo. For non-hospitalized patients with COVID-19 who are at risk of disease progression, the currently recommended three anti-viral agents, nirmatrelvir plus ritonavir, molnupiravir and remdesivir, should continue to be recommended for the prevention of disease progression. Among them, oral nirmatrelvir plus ritonavir and intravenous remdesivir seem to be the better choice, followed by molnupiravir, as determined by this network meta-analysis. Additionally, these three anti-viral agents were shown to be as tolerable as the placebo in this clinical setting.

The effect of inhaled corticosteroids on the outcomes of patients with COVID-19: A systematic review and meta-analysis of randomized controlled trials.

BACKGROUND: The effect of inhaled corticosteroids (ICS) on the clinical outcomes of patients with coronavirus disease 2019 (COVID-19) was not known. RESEARCH DESIGN AND METHODS: Only phase 2 and 3 randomized clinical trials (RCTs) from electronic databases that investigated ICS in the treatment of COVID-19 patients were included. The outcomes of interest were the resolution of symptoms, risk of hospitalization or urgent medical visit, mortality, and the incidence of adverse events (AEs). RESULTS: Five RCTs involving 1243 patients who received ICS and 1526 patients with placebo or usual care were included. The ICS group had a higher rate of symptom resolution than the control group at day 14 (risk ratio [RR], 1.21; 95% confidence interval [CI], 1.12-1.30, p < 0.00001) and day 28 (RR, 1.12; 95% CI, 1.06-1.18, p < 0.0001). Additionally, the ICS group had a significantly lower risk of needing urgent medical care or hospitalization than the control group (RR, 0.15; 95% CI, 0.05-0.50; I2 = 0, p = 0.002). However, no significant difference in the 28-day mortality rate. CONCLUSIONS: In patients with mild-to-moderate COVID-19, ICS therapy improved symptom resolution, and decreased the risk of needing urgent medical care or hospitalization.

The impact of neutralizing monoclonal antibodies on the outcomes of COVID-19 outpatients: A systematic review and meta-analysis of randomized controlled trials.

To assess the clinical efficacy and safety of neutralizing monoclonal antibodies (mABs) for outpatients with coronavirus disease 2019 (COVID-19). PubMed, Embase, Web of Science, Cochrane Library, ClinicalTrials.gov, and World Health Organization International Clinical Trials Registry Platform (ICTRP) databases were searched from inception to July 19, 2021. Only randomized controlled trials (RCTs) that assessed the clinical efficacy and safety of neutralizing mABs in the treatment of COVID-19 outpatients were included. The Cochrane risk-of-bias tool was used to assess the quality of the included RCTs. The primary outcome was the risk of COVID-19-related hospitalization or emergency department (ED) visits. The secondary outcomes were the risk of death and adverse events (AEs). Five articles were included, in which 3309 patients received neutralizing mAB and 2397 patients received a placebo. A significantly lower rate of hospitalization or ED visits was observed among patients who received neutralizing mABs than those who received a placebo (1.7% vs. 6.5%, odds ratios (OR): 0.26; 95% confidence interval (CI): 0.19-0.36; I2 = 0%). In addition, the rate of hospitalization was significantly lower in the patients who received neutralizing mABs than in the control group (OR: 0.24; 95% CI: 0.17-0.34; I2 = 0%). The mortality rate was also significantly lower in the patients who received neutralizing mABs than in the control group (OR: 0.16; 95% CI: 0.05-0.58; I2 = 3%). Neutralizing mABs were associated with a similar risk of any AE (OR: 0.81; 95% CI: 0.64-1.01; I2 = 52%) and a lower risk of serious AEs (OR: 0.37; 97% CI: 0.19-0.72; I2 = 45%) compared with a placebo. Neutralizing mABs can help reduce the risk of hospitalization or ED visits in COVID-19 outpatients. For these patients, neutralizing mABs are safe and not associated with a higher risk of AEs than a placebo.

Humoral Immunogenicity and Reactogenicity of the Standard ChAdOx1 nCoV-19 Vaccination in Taiwan.

BACKGROUND: The ChAdOx1 nCoV-19 vaccine has been widely administered against SARS-CoV-2 infection; however, data regarding its immunogenicity, reactogenicity, and potential differences in responses among Asian populations remain scarce. METHODS: 270 participants without prior COVID-19 were enrolled to receive ChAdOx1 nCoV-19 vaccination with a prime-boost interval of 8-9 weeks. Their specific SARS-CoV-2 antibodies, neutralizing antibody titers (NT50), platelet counts, and D-dimer levels were analyzed before and after vaccination. RESULTS: The seroconversion rates of anti-RBD and anti-spike IgG at day 28 after a boost vaccination (BD28) were 100% and 95.19%, respectively. Anti-RBD and anti-spike IgG levels were highly correlated (r = 0.7891), which were 172.9 ± 170.4 and 179.3 ± 76.88 BAU/mL at BD28, respectively. The geometric mean concentrations (GMCs) of NT50 for all participants increased to 132.9 IU/mL (95% CI 120.0-147.1) at BD28 and were highly correlated with anti-RBD and anti-spike IgG levels (r = 0.8248 and 0.7474, respectively). Body weight index was statistically significantly associated with anti-RBD IgG levels (p = 0.035), while female recipients had higher anti-spike IgG levels (p = 0.038). The GMCs of NT50 declined with age (p = 0.0163) and were significantly different across age groups (159.7 IU/mL for 20-29 years, 99.4 IU/mL for ≥50 years, p = 0.0026). Injection-site pain, fever, and fatigue were the major reactogenicity, which were more pronounced after prime vaccination and in younger participants (<50 years). Platelet counts decreased and D-dimer levels increased after vaccination but were not clinically relevant. No serious adverse events or deaths were observed. CONCLUSION: The vaccine is well-tolerated and elicited robust humoral immunity against SARS-CoV-2 after standard prime-boost vaccination in Taiwanese recipients.

The effect of tocilizumab on COVID-19 patient mortality: A systematic review and meta-analysis of randomized controlled trials.

OBJECTIVES: This systematic review and meta-analysis of randomized controlled trials (RCTs) aimed to investigate the clinical efficacy and safety of tocilizumab for treating patients with COVID-19. METHODS: The PubMed, Embase, Cochrane Library, Clinicaltrials.gov, WHO International Clinical Trials Registry Platform and the preprint server of medRxiv.org were searched from their inception to February 20, 2021. Only RCTs that compared the treatment efficacy and safety of tocilizumab with the placebo or the standard of care for adult patients with COVID-19 were included in this meta-analysis. The primary outcome was 28-day mortality. RESULTS: This meta-analysis included eight RCTs which enrolled a total of 6314 patients for randomization, in which 3267 and 3047 patients were assigned to the tocilizumab and control groups, respectively. The mortality at day 28 was 24.4% and 29.9% in patients in the tocilizumab and control groups, respectively, meaning there was no significant difference observed between these two groups (OR, 0.92; 95% CI, 0.66-1.28; I2 = 62). This finding did not change in the subgroup analysis according to the initial use of MV or steroid while enrollment. The patients receiving tocilizumab had a lower rate of mechanical ventilation (MV) and intensive care unit (ICU) admission at day 28 compared with the control group (MV use: OR, 0.75; 95% CI, 0.62-0.90; I2 = 11; ICU admission: OR, 0.51; 95% CI, 0.28-0.92; I2 = 30). There were no significant differences between these two treatment groups in terms of the risk of treatment-emergent adverse events (AEs) (OR, 1.03; 95% CI, 0.71-1.49; I2 = 43), serious AEs (OR, 0.86; 95% CI, 0.67-1.12; I2 = 0) or infection (OR, 0.87; 95% CI, 0.63-1.20; I2 = 0). CONCLUSIONS: Tocilizumab does not provide a survival benefit for patients with COVID-19, but it may help reduce the risk of MV and ICU admission. In addition, tocilizumab is a safe agent to use for the treatment of COVID-19.

Clinical efficacy and safety of remdesivir in patients with COVID-19: a systematic review and network meta-analysis of randomized controlled trials.

OBJECTIVES: We performed a systematic review and network meta-analysis of randomized controlled trials (RCTs) to provide updated information regarding the clinical efficacy of remdesivir in treating coronavirus disease 2019 (COVID-19). METHODS: PubMed, Embase, Cochrane Library, clinical trial registries of ClinicalTrials.gov and the WHO International Clinical Trials Registry Platform were searched for relevant articles published up to 18 November 2020. RESULTS: Five RCTs, including 13 544 patients, were included in this meta-analysis. Among them, 3839 and 391 patients were assigned to the 10 day and 5 day remdesivir regimens, respectively. Patients receiving 5 day remdesivir therapy presented greater clinical improvement than those in the control group [OR = 1.68 (95% CI 1.18-2.40)], with no significant difference observed between the 10 day and placebo groups [OR = 1.23 (95% CI 0.90-1.68)]. Patients receiving remdesivir revealed a greater likelihood of discharge [10 day remdesivir versus control: OR = 1.32 (95% CI 1.09-1.60); 5 day remdesivir versus control: OR = 1.73 (95% CI 1.28-2.35)] and recovery [10 day remdesivir versus control: OR = 1.29 (95% CI 1.03-1.60); 5 day remdesivir versus control: OR = 1.80 (95% CI 1.31-2.48)] than those in the control group. In contrast, no mortality benefit was observed following remdesivir therapy. Furthermore, no significant association was observed between remdesivir treatment and an increased risk of adverse events. CONCLUSIONS: Remdesivir can help improve the clinical outcome of hospitalized patients with COVID-19 and a 5 day regimen, instead of a 10 day regimen, may be sufficient for treatment. Moreover, remdesivir appears as tolerable as other comparators or placebo.

In vitro diagnostics of coronavirus disease 2019: Technologies and application.

Laboratory-based diagnostic measures including virological and serological tests are essential for detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Real-time reverse transcription-polymerase chain reactions (rRT-PCR) can detect SARS-COV-2 by targeting open reading frame-1 antibodies (ORF1ab), envelope protein, nucleocapsid protein, RNA-dependent RNA polymerase genes, and the N1, N2, and N3 (3N) target genes. Therefore, rRT-PCR remains the primary method of diagnosing SARS-CoV-2 despite being limited by false-negative results, long turnaround, complex protocols, and a need for skilled personnel. Serological diagnosis of coronavirus disease 2019 (COVID-19) is simple and does not require complex techniques and equipment, rendering it suitable for rapid detection and massive screening. However, serological tests cannot confirm SARS-CoV-2, and results will be false-negative when antibody concentrations fall below detection limits. Balancing the increased use of laboratory tests, risk of testing errors, need for tests, burden on healthcare systems, benefits of early diagnosis, and risk of unnecessary exposure is a significant and persistent challenge in diagnosing COVID-19.

Co-infections among patients with COVID-19: The need for combination therapy with non-anti-SARS-CoV-2 agents?

Co-infection has been reported in patients with severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome, but there is limited knowledge on co-infection among patients with coronavirus disease 2019 (COVID-19). The prevalence of co-infection was variable among COVID-19 patients in different studies, however, it could be up to 50% among non-survivors. Co-pathogens included bacteria, such as Streptococcus pneumoniae, Staphylococcus aureus, Klebsiella pneumoniae, Mycoplasma pneumoniae, Chlamydia pneumonia, Legionella pneumophila and Acinetobacter baumannii; Candida species and Aspergillus flavus; and viruses such as influenza, coronavirus, rhinovirus/enterovirus, parainfluenza, metapneumovirus, influenza B virus, and human immunodeficiency virus. Influenza A was one of the most common co-infective viruses, which may have caused initial false-negative results of real-time reverse-transcriptase polymerase chain reaction for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Laboratory and imaging findings alone cannot help distinguish co-infection from SARS-CoV-2 infection. Newly developed syndromic multiplex panels that incorporate SARS-CoV-2 may facilitate the early detection of co-infection among COVID-19 patients. By contrast, clinicians cannot rule out SARS-CoV-2 infection by ruling in other respiratory pathogens through old syndromic multiplex panels at this stage of the COVID-19 pandemic. Therefore, clinicians must have a high index of suspicion for coinfection among COVID-19 patients. Clinicians can neither rule out other co-infections caused by respiratory pathogens by diagnosing SARS-CoV-2 infection nor rule out COVID-19 by detection of non-SARS-CoV-2 respiratory pathogens. After recognizing the possible pathogens causing co-infection among COVID-19 patients, appropriate antimicrobial agents can be recommended.

Global coronavirus disease 2019: What has daily cumulative index taught us?

In addition to the absolute case number, a rapid increase in the number of COVID-19 cases within a short time results in insufficiency of healthcare systems and further negatively affects patient outcomes. This study was conducted to investigate the association between the outcomes of COVID-19 patients and daily cumulative index (DCI), which was defined as the average daily number of new cases of COVID-19 and calculated by cumulative cases/number of days between the first reported case and March 6, 2020, by country. Spearman's rank correlation analyses were conducted to evaluate the relationship between mortality, incidence, and DCI. In this study, DCI was positively correlated with incidence (adjusted risk ratio [aRR] = 1.01, 95% confidence interval [CI] = 1.00-1.02, P < 0.01). Higher correlation was observed between mortality and DCI (mortality rate: r = 0.397, P = 0.018; mortality per 1 000 000 people: r = 0.0.428, P = 0.004) than between disease incidence and DCI. DCI remained statistically significantly associated with mortality per 1 000 000 people after adjustment of Health Care Index (aRR = 1.02, 95% CI = 1.01-1.03, P < 0.001) or Healthcare Access and Quality Index (aRR = 1.02, 95% CI = 1.01-1.04, P < 0.01. Reducing DCI through strict infection control measures can help slow the number of new COVID-19 cases and further improve outcomes in COVID-19 patients.

Global epidemiology of coronavirus disease 2019 (COVID-19): disease incidence, daily cumulative index, mortality, and their association with country healthcare resources and economic status.

It has been 2 months since the first case of coronavirus disease 2019 (COVID-19) was reported in Wuhan, China. So far, COVID-19 has affected 85 403 patients in 57 countries/territories and has caused 2924 deaths in 9 countries. However, epidemiological data differ between countries. Although China had higher morbidity and mortality than other sites, the number of new daily cases in China has been lower than outside of China since 26 February 2020. The incidence ranged from 61.44 per 1 000 000 people in the Republic of Korea to 0.0002 per 1 000 000 people in India. The daily cumulative index (DCI) of COVID-19 (cumulative cases/no. of days between the first reported case and 29 February 2020) was greatest in China (1320.85), followed by the Republic of Korea (78.78), Iran (43.11) and Italy (30.62). However, the DCIs in other countries/territories were <10 per day. Several effective measures including restricting travel from China, controlling the distribution of masks, extensive investigation of COVID-19 spread, and once-daily press conferences by the government to inform and educate people were aggressively conducted in Taiwan. This is probably the reason why there was only 39 cases (as of 29 February 2020) with a DCI of 1 case per day in Taiwan, which is much lower than that of nearby countries such as the Republic of Korea and Japan. In addition, the incidence and mortality were correlated with the DCI. However, further study and continued monitoring are needed to better understand the underlying mechanism of COVID-19.

Asymptomatic carrier state, acute respiratory disease, and pneumonia due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2): Facts and myths.

Since the emergence of coronavirus disease 2019 (COVID-19) (formerly known as the 2019 novel coronavirus [2019-nCoV]) in Wuhan, China in December 2019, which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), more than 75,000 cases have been reported in 32 countries/regions, resulting in more than 2000 deaths worldwide. Despite the fact that most COVID-19 cases and mortalities were reported in China, the WHO has declared this outbreak as the sixth public health emergency of international concern. The COVID-19 can present as an asymptomatic carrier state, acute respiratory disease, and pneumonia. Adults represent the population with the highest infection rate; however, neonates, children, and elderly patients can also be infected by SARS-CoV-2. In addition, nosocomial infection of hospitalized patients and healthcare workers, and viral transmission from asymptomatic carriers are possible. The most common finding on chest imaging among patients with pneumonia was ground-glass opacity with bilateral involvement. Severe cases are more likely to be older patients with underlying comorbidities compared to mild cases. Indeed, age and disease severity may be correlated with the outcomes of COVID-19. To date, effective treatment is lacking; however, clinical trials investigating the efficacy of several agents, including remdesivir and chloroquine, are underway in China. Currently, effective infection control intervention is the only way to prevent the spread of SARS-CoV-2.