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1.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-22270020

RESUMO

ObjectivesTo investigate the association between SARS-CoV-2 mRNA vaccines, BNT162b2 and mRNA-1273, and myocarditis/pericarditis. DesignSelf-Controlled Case Series study (SCCS) using national data on COVID-19 vaccination and emergency care/hospital admissions. SettingItalian Regions (Lombardia, Friuli Venezia Giulia, Veneto, Lazio). Participants2,861,809 individuals, aged 12-39 years, vaccinated with the first doses of mRNA vaccines (2,405,759 BNT162b2 and 456,050 mRNA-1273) between 27 December 2020 and 30 September 2021. Main outcome measuresFirst diagnosis of myocarditis/pericarditis within the study period. The incidence of events in the exposure risk periods (0-21 days from the vaccination day, subdivided in three equal intervals) for first and second dose was compared with baseline period. The SCCS model was fitted using conditional Poisson regression to estimate Relative Incidences (RI) and Excess of Cases (EC) per 100,000 vaccinated by dose, age, gender and brand. ResultsDuring the study period, 441 participants aged 12-39 years developed myocarditis/pericarditis (346 BNT162b2 and 95 mRNA-1273). During the 21-day risk interval there were 114 cases of myocarditis/pericarditis (74 BNT162b2 and 40 mRNA-1273) corresponding to a RI of 1.27 (0.87-1.85) and 2.16 (1.50-3.10) after first and second dose, respectively. An increased risk of myocarditis/pericarditis at [0-7) days was observed after first [RI=6.55; 95% Confidence Interval (2.73-15.72); EC per 100,000 vaccinated=2.0 (1.5-2.3)] and second dose [RI=7.59 (3.26-17.65); EC=5.5 (4.4-5.9)] of mRNA-1273 and after second dose of BNT162b2 [RI=3.39 (2.02-5.68); EC=0.8 (0.6-1.0)]. In males, an increased risk at [0-7) days was observed after first [RI=12.28, 4.09-36.83; EC=3.8 (3.1-4.0)] and second dose [RI=11.91 (3.88-36.53); EC=8.8 (7.2-9.4)] of mRNA-1273 and after second dose of BNT162b2 [RI=3.45 (1.78-6.68); EC=1.0 (0.6-1.2)]. In females, an increased risk at [0-7) days was observed after second dose of BNT162b2 [RI=3.38 (1.47-7.74); EC=0.7 (0.3-0.9)]. At [0-7) days an increased risk following second dose of BNT162b2 was observed in the 12-17 years old [RI=5.74, (1.52-21.72); EC=1.7 (0.7-1.9)] and in 18-29 years old [RI=4.02 (1.81-8.91); EC=1.1 (0.6-1.3)]. At [0-7) days an increased risk after first [RI=7.58 (2.62-21.94); EC=3.5 (2.4-3.8)] and second [RI=9.58 (3.32-27.58); EC=8.3 (6.7-9.2)] dose of mRNA-1273 was found in 18-29 years old and after first dose in 30-39 years old [RI=6.57 (1.32-32.63); EC=1.0 (0.3-1.1)]. ConclusionsThis population-based study indicates that mRNA vaccines were associated with myocarditis/pericarditis in the population younger than 40 years, whereas no association was observed in older subjects. The risk increased after the second dose and in the youngest for both vaccines, remained moderate following vaccination with BNT162b2, while was higher in males following vaccination with mRNA-1273. The public health implication of these findings should be weighed in the light of the overall efficacy and safety profile of both vaccines.

2.
J Biomed Inform ; 42(1): 1-10, 2009 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-18620077

RESUMO

A test of the performance of two probabilistic classifiers (random forests and multinomial logit models) in automatically defining cancer cases has been carried out on 5608 subjects, registered by the Venetian Tumour Registry (RTV) during the years 1987-1996 and manually checked for possible second cancers that occurred during the 1997-1999 period. An eightfold cross-validation was performed to estimate the classification error; 63 predictive variables were entered into the model fitting. The random forest allows to automatically classify 45% of subjects with a classification error lower than 5%, while the corresponding error is 31% for the multilogit model. The performance of the former classifier is appealing, indicating a potential drop of manually checked cases from 1750 to 960 per incidence year with a moderate error rate. This result suggests to refine the approach and extend it to other categories of manually treated cases.


Assuntos
Modelos Logísticos , Neoplasias/classificação , Neoplasias/epidemiologia , Sistema de Registros , Inteligência Artificial , Humanos , Itália , Segunda Neoplasia Primária/classificação , Segunda Neoplasia Primária/epidemiologia , Reconhecimento Automatizado de Padrão , Valor Preditivo dos Testes , Reprodutibilidade dos Testes
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