Background And Aims: Coronavirus disease (COVID-19) is a major danger to world health and has been linked to periodontitis in a number of epidemiological observational studies. However, it is unclear whether COVID-19 causes periodontitis. COVID-19's causal influence on periodontitis was determined using bidirectional Mendelian randomization (MR).
Methods: Large-scale COVID-19 and periodontitis genome wide association study data were analyzed. Inverse variance weighting, MR-Egger, weighted median, and MR-PRESSO were used to estimate causal effects. Sensitivity studies were conducted using the Cochran's Q test, the MR-Egger intercept test, the MR-PRESSO, and the leave-one-out (LOO) analysis. Further investigation of potential mediating factors was performed using risk factor analysis.
Results: The MR presented no causal relationship between periodontitis and hospitalization for COVID-19 (odds ratio [OR] = 0.97, 95% confidence interval [CI] 0.78-1.20; = 0.76), vulnerability to COVID-19 (OR = 1.04, 95% CI 0.88-1.21; = 0.65), COVID-19 disease severity (OR = 1.01, 95% CI 0.92-1.11; = 0.81). Meanwhile, a noncausal effect of genetic hospitalization for COVID-19, illness severity, and vulnerability to periodontitis was detected. Other MR methods yielded identical results to inverse variance weighting. According to sensitivity analysis, horizontal pleiotropy is unlikely to affect causal estimation.
Conclusion: Periodontitis had no link to the risk of COVID-19 hospitalization, susceptibility, or severity. However, the substance in COVID-19 that is responsible for this effect must be studied further.
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http://dx.doi.org/10.1002/hsr2.1413 | DOI Listing |
BMC Public Health
January 2025
Murdoch Children's Research Institute, 50 Flemington Road, Parkville, VIC, 3052, Australia.
Background: In a world confronted with new and connected challenges, novel strategies are needed to help children and adults achieve their full potential, to predict, prevent and treat disease, and to achieve equity in services and outcomes. Australia's Generation Victoria (GenV) cohorts are designed for multi-pronged discovery (what could improve outcomes?) and intervention research (what actually works, how much and for whom?). Here, we describe the key features of its protocol.
View Article and Find Full Text PDFInt J Emerg Med
January 2025
Men's Health and Reproductive Health Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Background: Anticoagulants increase the risk of cardiac tamponade in patients with pericardial effusion (PE). Therefore, inappropriate administration of them in the presence of PE can lead to a catastrophic outcome. This study presents a patient with a provisional misdiagnosis of venous thromboembolism (VTE).
View Article and Find Full Text PDFBMC Psychiatry
January 2025
Research Center of Psychiatry and Behavioral Sciences, Tabriz University of Medical Sciences, Tabriz, Islamic Republic of Iran.
Introduction: Mental disorders, such as anxiety and depression, significantly impacted global populations in 2019 and 2020, with COVID-19 causing a surge in prevalence. They affect 13.4% of the people worldwide, and 21% of Iranians have experienced them.
View Article and Find Full Text PDFBMC Infect Dis
January 2025
Department of Cardiac Surgery, Second Hospital of Hebei Medical University, No.215 of Heping West Road,Xinhua District, Shijiazhuang, 050000, China.
Objective: To evaluate the effects of different SARS-CoV-2 inactivation methods on the blood concentration of colistin sulfate.
Methods: A colistin sulfate reference substance, a quality control plasma sample, and a clinically measured sample were transferred and heated in a 56 °C water batch for 30 min or irradiated under an ultraviolet (UV) lamp for 60 min to examine the stability of the reference solution and quality control plasma sample. Statistical analysis was conducted for the concentration of the clinically measured sample before and after inactivation with the intraclass correlation coefficient (ICC) method, the Passing-Bablok regression, and the Bland-Altman analysis.
BMC Med Res Methodol
January 2025
Systems Engineering & Operations Research, George Mason University, Fairfax, VA, 22030, USA.
Background: In this work, we implement a data-driven approach using an aggregation of several analytical methods to study the characteristics of COVID-19 daily infection and death time series and identify correlations and characteristic trends that can be corroborated to the time evolution of this disease. The datasets cover twelve distinct countries across six continents, from January 22, 2020 till March 1, 2022. This time span is partitioned into three windows: (1) pre-vaccine, (2) post-vaccine and pre-omicron (BA.
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