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For example, Rao et al [28] leveraged PEDSnet’s geographical and clinical breadth to identify risk factors such as age, severity of acute COVID-19 infection, and comorbid conditions. Potential biological variables that are well-defined in EHRs and therefore, more reliably available for application in adjusted analyses include age, sex, BMI, and blood pressure, and, indeed, these variables have been shown to confound the evaluation of causal pathways for long COVID [49-51].
J Med Internet Res 2025;27:e59217
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Public Health Messaging on Twitter During the COVID-19 Pandemic: Observational Study
We leverage methods introduced in the study by Rao et al [13] to identify posts about 7 important COVID-19 pandemic–related issues: origins of the virus, lockdowns and stay-at-home orders, masking mandates, online schooling and education, health care, alternative treatments and therapeutics, and vaccines. We use state-of-the-art classifiers [77,78] to analyze the emotional and moral language used in posts.
J Med Internet Res 2025;27:e63910
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