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Binomial logistic regression analysis.

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NIAID Data Ecosystem2026-05-01 收录
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https://figshare.com/articles/dataset/Binomial_logistic_regression_analysis_/25076998
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Early in the pandemic, the spread of the emerging virus SARS-CoV-2 was causing mild illness lasting less than two weeks for most people, with a small proportion of people developing serious illness or death. However, as the pandemic progressed, many people reported suffering from symptoms for weeks or months after their initial infection. Persistence of COVID-19 symptoms beyond one month, or what is known as long COVID-19, is recognized as a risk of acute infection. Up to date, information on long COVID-19 among Jordanian patients has not been reported. Therefore, we sought to conduct this cross-sectional study utilizing a self-administered survey. The survey asks a series of questions regarding participant demographics, long COVID-19 symptoms, information about pre-existing medical history, supplements, vaccination history, and symptoms recorded after vaccination. Chi square analysis was conducted on 990 responders, and the results showed a significant correlation (P<0.05) between long COVID-19 syndrome and age, obesity, chronic illness, vitamin D intake, number of times infected by COVID-19, number of COVID-19 symptoms and whether the infection was pre or post vaccination. The long-term symptoms most enriched in those with long COVID-19 were tinnitus (73.4%), concentration problems (68.6%) and muscle and joint ache (68.3%).A binomial logistic regression analysis was done to explore the predictors of long COVID-19 and found that age 18–45, marital status, vitamin D, number of COVID-19 symptoms and signs after vaccination are positive predictors of long COVID-19, while zinc intake is a negative predictor. Although further studies on long-term persistence of symptoms are needed, the present study provides a baseline that allows us to understand the frequency and nature of long COVID-19 among Jordanians
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2024-01-26
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