Effect of chloroquine and hydroxychloroquine on COVID-19 virological outcomes: An updated meta-analysis

Safety and tolerance of vaccines against SARS-CoV-2 infection in systemic lupus erythematosus: results from the COVAD study

OBJECTIVE

To determine COVID-19 vaccine-related adverse events (AEs) in the seven-day post-vaccination period in patients with SLE vs autoimmune rheumatic diseases (AIRDs), non-rheumatic autoimmune diseases (nrAIDs), and healthy controls (HC).

METHODS

Data were captured through the COVID-19 Vaccination in Autoimmune Diseases (COVAD) questionnaire (March-December 2021). Multivariable regression models accounted for age, gender, ethnicity, vaccine type and background treatment.

RESULTS

Among 9462 complete respondents, 583 (6.2%) were SLE patients (mean age: 40.1 years; 94.5% females; 40.5% Asian; 42.9% Pfizer-recipients). Minor AEs were reported by 83.0% of SLE patients, major by 2.6%, hospitalization by 0.2%. AE and hospitalization frequencies were similar between patients with active and inactive SLE. Rashes were more frequent in SLE patients vs HC (OR; 95% CI: 1.2; 1.0, 1.5), chills less frequent in SLE vs AIRDs (0.6; 0.4, 0.8) and nrAIDs (0.5; 0.3, 0.8), and fatigue less frequent in SLE vs nrAIDs (0.6; 0.4, 0.9). Pfizer-recipients reported higher overall AE (2.2; 1.1, 4.2) and injection site pain (2.9; 1.6, 5.0) frequencies than recipients of other vaccines, Oxford/AstraZeneca-recipients more body ache, fever, chills (OR: 2.5, 3.0), Moderna-recipients more body ache, fever, chills, rashes (OR: 2.6, 4.3). Hospitalization frequencies were similar across vaccine types. AE frequencies were similar across treatment groups, although chills were less frequent in antimalarial users vs non-users (0.5; 0.3, 0.9).

CONCLUSION

While COVID-19 vaccination-related AEs were reported by four-fifths of SLE patients, those were mostly minor and comparable to AEs reported by healthy individuals, providing reassurance regarding COVID-19 vaccination safety in SLE.

COVID-19 Pandemic Between Severity Facts and Prophylaxis

Before COVID-19, many viruses have infected humans, so what caused COVID-19 to be considered as a pandemic? COVID-19 belongs to the coronavirus family that includes severe acute respiratory syndrome (SARS) and Middle East Respiratory Syndrome (MERS). This family has caused a large number of deaths all over the world. How risky is the novel coronavirus? People and their careers were disrupted, and many businesses all over the world are now closed. From here, it seems to us that this virus is something that can make people feel afraid. In this article, we will try to understand the severity of this virus, and then disclose the available ways to confront it and ways that might improve the ability to face it, either now or in the future. Upon comparing COVID-19 with seasonal flu, we have found that COVID-19 is about 10 times more deadly, although it is not the most infectious virus. In this review, we will discuss how healthy nutrition and lifestyle may help to prevent and treat diseases, and especially COVID-19. We will focus on how to follow healthy nutrition habits and lifestyles to stop the dangers of COVID-19.

Keeping Meta-Analyses Hygienic During the COVID-19 Pandemic

Despite the massive distribution of different vaccines globally, the current pandemic has revealed the crucial need for an efficient treatment against COVID-19. Meta-analyses have historically been extremely useful to determine treatment efficacy but recent debates about the use of hydroxychloroquine for COVID-19 patients resulted in contradictory meta-analytical results. Different factors during the COVID-19 pandemic have impacted key features of conducting a good meta-analysis. Some meta-analyses did not evaluate or treat substantial heterogeneity (I² > 75%); others did not include additional analysis for publication bias; none checked for evidence of p–hacking in the primary studies nor used recent methods (i.e., p-curve or p-uniform) to estimate the average population-size effect. These inconsistencies may contribute to contradictory results in the research evaluating COVID-19 treatments. A prominent example of this is the use of hydroxychloroquine, where some studies reported a large positive effect, whereas others indicated no significant effect or even increased mortality when hydroxychloroquine was used with the antibiotic azithromycin. In this paper, we first recall the benefits and fundamental steps of good quality meta-analysis. Then, we examine various meta-analyses on hydroxychloroquine treatments for COVID-19 patients that led to contradictory results and causes for this discrepancy. We then highlight recent tools that contribute to evaluate publication bias and p-hacking (i.e., p-curve, p-uniform) and conclude by making technical recommendations that meta-analyses should follow even during extreme global events such as a pandemic.