Respiratory Research · 2020 · 45 citations · 14 references
MedicineClinical SciencesInfectious DiseasesClinical EpidemiologyEarly DetectionMolecular DiagnosticsDiagnostic CriteriaDiagnostic EvaluationC-reactive Protein TestingComparative Disease SeverityDisease Severity EstimationDisease Severity IndexLogistic RegressionLogistic Regression AnalysisRespiratory RateRespiratory Rate Evaluation
Abstract Background Several previously healthy young adults have developed Coronavirus Disease 2019 (COVID-19), and a few of them progressed to the severe stage. However, the factors are not yet determined. Method We retrospectively analyzed 123 previously healthy young adults diagnosed with COVID-19 from January to March 2020 in a tertiary hospital in Wuhan. Patients were classified as having mild or severe COVID-19 based on their respiratory rate, SpO 2 , and PaO 2 /FiO 2 levels. Patients’ symptoms, computer tomography (CT) images, preadmission drugs received, and the serum biochemical examination on admission were compared between the mild and severe groups. Significant variables were enrolled into logistic regression model to predict the factors affecting disease severity. A receiver operating characteristic (ROC) curve was applied to validate the predictive value of predictors. Result Age; temperature; anorexia; and white blood cell count, neutrophil percentage, platelet count, lymphocyte count, C-reactive protein, aspartate transaminase, creatine kinase, albumin, and fibrinogen values were significantly different between patients with mild and severe COVID-19 ( P < 0.05). Logistic regression analysis confirmed that lymphopenia ( P = 0.010) indicated severe prognosis in previously healthy young adults with COVID-19, with the area under the curve (AUC) was 0.791(95% Confidence Interval (CI) 0.704–0.877)( P < 0.001). Conclusion For previously healthy young adults with COVID-19, lymphopenia on admission can predict severe prognosis.
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Clinical characteristics of 140 patients infected with SARS‐CoV‐2 in Wuhan, China
Jinjin Zhang, Xiang Dong, Yiyuan Cao et al. · Allergy · 2020 · 4.3K citations · Full text
Veterinary Medicine, Infectious Diseases, Internal Medicine +13