Background A serious allergic reaction that may occur in response to medical products is anaphylaxis, which potentially can lead to anaphylactic shock. In the light of recent COVID-19 pandemic, much public attention had been paid to the severe allergic reactions occurring after COVID-19 vaccination. Therefore, in our study we would like to investigate the risk of authorized COVID-19 vaccines to induce anaphylactic reaction, anaphylactoid reaction, anaphylactic shock and anaphylactoid shock. Methods We searched databases, such as PubMed, Web of Science and Embase and found eight articles about the incidence of anaphylactic and anaphylactoid reactions. Also, we used data from four databases from Canada, the U.S., the European Union and the United Kingdom. To calculate effect sizes, we used random effects model with inverse variance method. The risk ratio with 95% confidence interval were used for dichotomous outcomes. Statistical analysis was prepared in R. Results were considered statistically significant at p < 0.05. Results The most cases of anaphylactic reaction, anaphylactoid reaction, anaphylactic shock and anaphylactoid shock were reported in female aged 18–85 years after BNT162b2 vaccine according to data from the EU. Analyzed COVID-19 vaccines can cause the anaphylaxis/anaphylactic reaction with risk of 106.99 (95% CI [39.95; 286.57], p < 0.0001, I2 = 59%), whereas the anaphylactoid reaction, anaphylactic and anaphylactoid shocks with risk of 113.3 (95% CI [28.11; 456.53], p < 0.0001), 344.2 (95% CI [85.77; 1381.39], p < 0.0001), 14.9, 95% CI [1.96; 112.79], p = 0.009), respectively. Conclusions Our meta-analysis shows that the risk of anaphylactic reaction, anaphylactoid reaction, anaphylactic shock and anaphylactoid shock do not occur only after mRNA COVID-19 vaccines. Therefore, vaccination centers should be prepared to render assistance in the event of a reaction in all cases.
Background New vaccines are being developed to fight the ongoing COVID-19 pandemic. In our study we compared the efficacy of COVID-19 vaccines to prevent COVID-19-related infections and mortality. Methods 17 randomized clinical trials of COVID-19 vaccines were included after search in databases. We compared COVID-19 vaccines based on symptomatic and severe infections, number of deaths and hospitalizations related to COVID-19. Also, we analyzed the efficacy of COVID-19 against different variants of SARS-CoV-2 as well as according to different age groups. Random effects model using Mantel–Haenzeal method was used to pool relative risk (RR). Results Our meta-analysis shows that full vaccination could decrease not only the risk of symptomatic or severe COVID-19, the risk of hospitalization and death caused by COVID-19. COVID-19 vaccines were also effective against variants of SARS-CoV-2 (RR = 0.36; 95% CI [0.25; 0.53], p < 0.0001). However, efficacy of vaccination varied in COVID-19 variant-dependent manner. Moreover, the analysis in different age groups showed that COVID-19 vaccines had the similar results: the risk was slightly lower in adults compared to elderly cohort $$(\ge$$ ( ≥ 65 years): (RR = 0.16, 95% CI [0.11; 0.23]) and (RR = 0.19, 95% CI [0.12; 0.30]), respectively. Conclusions Data obtained from clinical trials of COVID-19 vaccines looks promising, in order to fully investigate efficacy of the vaccines further clinical examination is required especially considering new SARS-CoV-2 variants.
Background The COVID-19 pandemic has caused increased mortality worldwide. We noticed a tendency for higher number of deaths in Eastern European countries. Therefore, we decided to investigate whether any common factor that might be responsible for the increased COVID-19 mortality exists. Methods In our cross-sectional study, we conducted the correlation and multiple regression analysis using R basing on the data gathered in publicly available databases. In the analysis, we included variables such as: number of deaths, number of new cases, number of hospitalizations, number of ICU (intensive care units) patients, number of vaccinations, number of boosters, number of fully vaccinated individuals, stringency index, number of reported COVID-19 variant cases, and number of flights. Additionally, we analyzed the influence of population density and median age in particular European countries on total number of COVID-19 deaths. Analyzed data represents periods from start of the COVID-19 pandemic in particular Eastern European Countries: Bulgaria, Croatia, Czech Republic, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia and Slovenia, while as the end of the study the day of January 31, 2022 is considered. Results were considered statistically significant at p < 0.05. Results Our study showed that mortality rate reflects the number of COVID-19 cases (e.g. for Poland was 0.0058, p < 0.001), number of hospitalized patients (e.g. for Poland 0.0116, p < 0.001), and patients in intensive care (e.g. for Slovakia 0.2326, p < 0.001). Stringency index corresponding to level of introduced restrictions and vaccination can affect the mortality rate of COVID-19 in a country-dependent manner: e.g. for Romania 0.0006, p < 0.001; whereas in Lithuania − 0.0002, p < 0.001. Moreover, occurrence of B.1.1.7 and B.1.617.2 variants increased COVID-19 mortality rates. Conclusion Our analysis showed that crucial factor for decreasing mortality is proper healthcare joined by accurate restriction policy. Additionally, our study shows that COVID-19 vaccination proven successful in COVID-19 mortality prevention.
The COVID-19 pandemic still goes on. The increasing number of COVID-19 cases has been observed since the start of summer 2022, although this was not in summer 2021. Therefore, we would like to compare factors that were responsible for this trend in five selected countries in the European Union (Greece, Italy, Slovenia, Austria and Germany) using the data from publicly available databases for the analyzed period of weeks 22–30 in 2021 and 2022. The multiple factor analysis was conducted in R, using mean or median score. Our cross-sectional study showed that analyzed countries had similar profiles in 2021 characterized by restrictions and health system policies, as well as B.1.351, B.1.1.7, B.1.617.2 and P.1 variants. Similarly, these countries had similar profiles in 2022, but described by other variables: number of new COVID-19 cases per million, number people fully vaccinated per hundred, number of total boosters administered per hundred and also occurrence of Omicron variant and its sub-lineages. Although the COVID-19 vaccination rate is relatively high in the European Union, during the summer of 2022, the number of COVID-19 cases sharply increased daily, which seems to be connected with the presence of the Omicron variant and its sub-lineages.
Vitamin D is commonly known for its properties of airway remodeling inhibition. Due to this, we decided to analyze the action of calcitriol with anti-asthmatic drugs in airway remodeling. The HFL1 cell line was treated with calcitriol, beclomethasone 17-propionate, montelukast sodium, LTD4 and TGF-β in different combinations. Real-time PCR was used to analyzed the expression of ACTA2, CDH-1, Vimentin, ADAM33, MMP-9 and CysLTR1 on the mRNA level, whereas Western blot was used to analyze gene expression on the protein level. One-way analysis variants, the Kruskal-Wallis test, Student’s t-test or Welch’s t-test were used for statistical analysis. Concerning the results, pre-treatment with calcitriol increased the inhibitory effect of beclomethasone 17-propionate and montelukast sodium on the expression of ACTA2 (p = 0.0072), Vimentin (p = 0.0002) and CysLTR1 (p = 0.0204), and 1,25(OH)2D3 had an influence on the effects of beclomethasone 17-propionate and montelukast sodium and of CDH1 expression (p = 0.0076). On the protein level, pre-treatment with calcitriol with beclomethasone 17-propionate and montelukast sodium treatment decreased ACTA2 expression in comparison to the LT (LTD4 and TGF-β) control group (p = 0.0191). Hence, our study not only confirms that vitamin D may inhibit airway remodeling, but also shows that vitamin D has a synergistic effect with anti-asthmatic drugs.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.