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1.
MMWR Morb Mortal Wkly Rep ; 71(14): 517-523, 2022 Apr 08.
Article in English | MEDLINE | ID: covidwho-1780340

ABSTRACT

Cardiac complications, particularly myocarditis and pericarditis, have been associated with SARS-CoV-2 (the virus that causes COVID-19) infection (1-3) and mRNA COVID-19 vaccination (2-5). Multisystem inflammatory syndrome (MIS) is a rare but serious complication of SARS-CoV-2 infection with frequent cardiac involvement (6). Using electronic health record (EHR) data from 40 U.S. health care systems during January 1, 2021-January 31, 2022, investigators calculated incidences of cardiac outcomes (myocarditis; myocarditis or pericarditis; and myocarditis, pericarditis, or MIS) among persons aged ≥5 years who had SARS-CoV-2 infection, stratified by sex (male or female) and age group (5-11, 12-17, 18-29, and ≥30 years). Incidences of myocarditis and myocarditis or pericarditis were calculated after first, second, unspecified, or any (first, second, or unspecified) dose of mRNA COVID-19 (BNT162b2 [Pfizer-BioNTech] or mRNA-1273 [Moderna]) vaccines, stratified by sex and age group. Risk ratios (RR) were calculated to compare risk for cardiac outcomes after SARS-CoV-2 infection to that after mRNA COVID-19 vaccination. The incidence of cardiac outcomes after mRNA COVID-19 vaccination was highest for males aged 12-17 years after the second vaccine dose; however, within this demographic group, the risk for cardiac outcomes was 1.8-5.6 times as high after SARS-CoV-2 infection than after the second vaccine dose. The risk for cardiac outcomes was likewise significantly higher after SARS-CoV-2 infection than after first, second, or unspecified dose of mRNA COVID-19 vaccination for all other groups by sex and age (RR 2.2-115.2). These findings support continued use of mRNA COVID-19 vaccines among all eligible persons aged ≥5 years.


Subject(s)
COVID-19 , Myocarditis , Pericarditis , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19 Vaccines/adverse effects , Female , Humans , Male , Myocarditis/epidemiology , Pericarditis/epidemiology , Pericarditis/etiology , RNA, Messenger , SARS-CoV-2 , United States/epidemiology , Vaccination/adverse effects
2.
JAMA Netw Open ; 5(2): e2147053, 2022 02 01.
Article in English | MEDLINE | ID: covidwho-1669328

ABSTRACT

Importance: New symptoms and conditions can develop following SARS-CoV-2 infection. Whether they occur more frequently among persons with SARS-CoV-2 infection compared with those without is unclear. Objective: To compare the prevalence of new diagnoses of select symptoms and conditions between 31 and 150 days after testing among persons who tested positive vs negative for SARS-CoV-2. Design, Setting, and Participants: This cohort study analyzed aggregated electronic health record data from 40 health care systems, including 338 024 persons younger than 20 years and 1 790 886 persons aged 20 years or older who were tested for SARS-CoV-2 during March to December 2020 and who had medical encounters between 31 and 150 days after testing. Main Outcomes and Measures: International Statistical Classification of Diseases, Tenth Revision, Clinical Modification codes were used to capture new symptoms and conditions that were recorded 31 to 150 days after a SARS-CoV-2 test but absent in the 18 months to 7 days prior to testing. The prevalence of new symptoms and conditions was compared between persons with positive and negative SARS-CoV-2 tests stratified by age (20 years or older and young than 20 years) and care setting (nonhospitalized, hospitalized, or hospitalized and ventilated). Results: A total of 168 701 persons aged 20 years or older and 26 665 younger than 20 years tested positive for SARS-CoV-2, and 1 622 185 persons aged 20 years or older and 311 359 younger than 20 years tested negative. Shortness of breath was more common among persons with a positive vs negative test result among hospitalized patients (≥20 years: prevalence ratio [PR], 1.89 [99% CI, 1.79-2.01]; <20 years: PR, 1.72 [99% CI, 1.17-2.51]). Shortness of breath was also more common among nonhospitalized patients aged 20 years or older with a positive vs negative test result (PR, 1.09 [99% CI, 1.05-1.13]). Among hospitalized persons aged 20 years or older, the prevalence of new fatigue (PR, 1.35 [99% CI, 1.27-1.44]) and type 2 diabetes (PR, 2.03 [99% CI, 1.87-2.19]) was higher among those with a positive vs a negative test result. Among hospitalized persons younger than 20 years, the prevalence of type 2 diabetes (PR, 2.14 [99% CI, 1.13-4.06]) was higher among those with a positive vs a negative test result; however, the prevalence difference was less than 1%. Conclusions and Relevance: In this cohort study, among persons hospitalized after a positive SARS-CoV-2 test result, diagnoses of certain symptoms and conditions were higher than among those with a negative test result. Health care professionals should be aware of symptoms and conditions that may develop after SARS-CoV-2 infection, particularly among those hospitalized after diagnosis.


Subject(s)
COVID-19/physiopathology , Symptom Assessment/statistics & numerical data , Adolescent , Adult , Age Factors , Aged , Aged, 80 and over , COVID-19/epidemiology , Child , Child, Preschool , Cohort Studies , Female , Humans , Infant , Infant, Newborn , Male , Middle Aged , Prevalence , SARS-CoV-2 , Socioeconomic Factors , Time Factors , Young Adult
3.
J Biomed Semantics ; 12(1): 13, 2021 07 18.
Article in English | MEDLINE | ID: covidwho-1484319

ABSTRACT

BACKGROUND: Effective response to public health emergencies, such as we are now experiencing with COVID-19, requires data sharing across multiple disciplines and data systems. Ontologies offer a powerful data sharing tool, and this holds especially for those ontologies built on the design principles of the Open Biomedical Ontologies Foundry. These principles are exemplified by the Infectious Disease Ontology (IDO), a suite of interoperable ontology modules aiming to provide coverage of all aspects of the infectious disease domain. At its center is IDO Core, a disease- and pathogen-neutral ontology covering just those types of entities and relations that are relevant to infectious diseases generally. IDO Core is extended by disease and pathogen-specific ontology modules. RESULTS: To assist the integration and analysis of COVID-19 data, and viral infectious disease data more generally, we have recently developed three new IDO extensions: IDO Virus (VIDO); the Coronavirus Infectious Disease Ontology (CIDO); and an extension of CIDO focusing on COVID-19 (IDO-COVID-19). Reflecting the fact that viruses lack cellular parts, we have introduced into IDO Core the term acellular structure to cover viruses and other acellular entities studied by virologists. We now distinguish between infectious agents - organisms with an infectious disposition - and infectious structures - acellular structures with an infectious disposition. This in turn has led to various updates and refinements of IDO Core's content. We believe that our work on VIDO, CIDO, and IDO-COVID-19 can serve as a model for yielding greater conformance with ontology building best practices. CONCLUSIONS: IDO provides a simple recipe for building new pathogen-specific ontologies in a way that allows data about novel diseases to be easily compared, along multiple dimensions, with data represented by existing disease ontologies. The IDO strategy, moreover, supports ontology coordination, providing a powerful method of data integration and sharing that allows physicians, researchers, and public health organizations to respond rapidly and efficiently to current and future public health crises.


Subject(s)
Biological Ontologies/statistics & numerical data , COVID-19/prevention & control , Communicable Disease Control/statistics & numerical data , Communicable Diseases/therapy , Computational Biology/statistics & numerical data , SARS-CoV-2/isolation & purification , COVID-19/epidemiology , COVID-19/virology , Communicable Disease Control/methods , Communicable Diseases/epidemiology , Communicable Diseases/transmission , Computational Biology/methods , Data Mining/methods , Data Mining/statistics & numerical data , Epidemics , Humans , Information Dissemination/methods , Public Health/methods , Public Health/statistics & numerical data , SARS-CoV-2/physiology , Semantics
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