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: Myocarditis and pericarditis are recognised risks following COVID-19 vaccination, including the mRNA-1273 vaccine. Most cases occur shortly following the second dose of this vaccine, and incidence is highest among young males. However, little is known about risk factors beyond age and sex and about the longer-term clinical course. This study aims to identify possible risk factors for myocarditis and pericarditis following mRNA-1273 vaccination, to characterise the clinical course of myocarditis and pericarditis, both associated with mRNA-1273 vaccination and not associated with vaccination, and to identify risk factors for severe outcomes (i.e., cardiac or thromboembolic complications, severe hospital outcomes, all-cause hospital readmission, and death). : This study is being conducted within the Vaccine Monitoring Collaboration for Europe (VAC4EU) association using routinely collected healthcare data from five data sources from four European countries (Denmark, Norway, Spain, and the United Kingdom). The study is being performed using a common data model, and all analyses are performed separately in each data source in a federated manner following a common protocol. A case-cohort analysis set is identified within each data source for identifying potential risk factors for myocarditis and pericarditis following mRNA-1273 vaccination using logistic regression analysis. The clinical course of myocarditis and pericarditis is being assessed using a cohort study design and describes all cases (i.e., cases associated with mRNA-1273 and unexposed cases). Cox regression analysis is applied to assess the associations between risk factors and several follow-up outcomes. : This protocol describes the study methodology of an international collaborative initiative with the aim of assessing the risk factors and clinical course of myocarditis and pericarditis following mRNA-1273 vaccination using a federated network of five European data sources.
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http://dx.doi.org/10.3390/vaccines13070755 | DOI Listing |
World J Pediatr Congenit Heart Surg
September 2025
Postgraduate Program in Health Sciences, Medical School, Federal University of Amazonas (UFAM), Manaus, Amazonas, Brazil.
To analyze in-hospital mortality in children undergoing congenital heart interventions in the only public referral center in Amazonas, North Brazil, between 2014 and 2022. This retrospective cohort study included 1041 patients undergoing cardiac interventions for congenital heart disease, of whom 135 died during hospitalization. Records were reviewed to obtain demographic, clinical, and surgical data.
View Article and Find Full Text PDFJAMA Netw Open
September 2025
Social and Behavioral Sciences Branch, Division of Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, Maryland.
Importance: Higher intellectual abilities have been associated with lower mortality risk in several longitudinal cohort studies. However, these studies did not fully account for early life contextual factors or test whether the beneficial associations between higher neurocognitive functioning and mortality extend to children exposed to early adversity.
Objective: To explore how the associations of child neurocognition with mortality changed according to the patterns of adversity children experienced.
Int J Surg
September 2025
Department of Gynecology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, Hainan, China.
Background: Ovarian cancer remains the most lethal gynecological cancer, with fewer than 50% of patients surviving more than five years after diagnosis. This study aimed to analyze the global epidemiological trends of ovarian cancer from 1990 to 2021 and also project its prevalence to 2050, providing insights into these evolving patterns and helping health policymakers use healthcare resources more effectively.
Methods: This study comprehensively analyzes the original data related to ovarian cancer from the GBD 2021 database, employing a variety of methods including descriptive analysis, correlation analysis, age-period-cohort (APC) analysis, decomposition analysis, predictive analysis, frontier analysis, and health inequality analysis.