遇见数据集

<p>Minimal anonymized dataset.</p>

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NIAID Data Ecosystem2026-05-10 收录
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The disease caused by the 2019 coronavirus (COVID-19) has resulted in unprecedented morbidity and mortality worldwide, with many individuals experiencing persistent symptoms and a decline in quality of life after infection. This study aims to analyze the prevalence and associated factors of long COVID in the Brazilian population, focusing on disease severity and immunization status. This observational, cross-sectional web survey employed a quantitative approach to analyze data from 4,231 participants, focusing on the prevalence and associated factors of long COVID. Data were analyzed using inferential statistical methods to identify factors associated with the outcome. A multivariable logistic regression model was applied to determine the variables independently associated with long COVID. To determine the best model, a stepwise selection method was employed, and the model’s performance was assessed utilizing a Receiver Operating Characteristic Curve (ROC). The findings revealed a long COVID prevalence of 56.4% (2,386 cases), with men having a 36.46% (OR = 1,36 CI = 1,17−1,58) higher chance of developing long COVID compared to women. A prior diagnosis before vaccination increased by 22.30% (OR = 1,22 CI = 1,05−1,41). Additionally, the use of sedatives and alcohol was linked to increases of 24.50% (OR = 1,24 CI = 1,07−1,43) and 34.95% (OR = 1,34 CI = 1,02−1,75), respectively. Beneficiaries of social programs faced a 47.29% (OR = 1,47 CI = 1,27−1,70) higher, while individuals with comorbidities had a 33.47% (OR =1,33 CI = 1,20−1,48). Hospitalization significantly raised the likelihood of prolonged symptoms by 331.92% (OR = 4,31 CI = 2,53−7,87). Overall, various factors, including sedative and alcohol use, were factors associated with long COVID, whereas vaccination showed a positive impact, suggesting that association models can help healthcare professionals identify high-risk patients and tailor care effectively.

创建时间:
2026-01-02
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