Abstract
Aim: Clinical findings indicated that a fraction of coronavirus disease 2019 (COVID-19) patients did not show fever. However, the difference between the clinical characteristics of fevered and non-fevered patients is still unclear. The aim of the present study was to describe the clinical characteristics of these patients and analyze the predictors for severe events of adult fevered COVID-19 patients.Methods: Clinical and laboratory data of fevered and non-fevered COVID-19 patients in Changsha, China, were collected and analyzed. Logistic regression analysis and Receiver Operating Characteristic Curve (ROC Curve) analysis were adopted to analyze risk factors and evaluate the effectiveness of the predictors for severe events in adult fevered COVID-19 patients.Results: Of the 230 adult COVD-19 patients in this study, 175 patients (76.1%) had fever and 55 patients (23.9%) did not have fever. Compared with non-fevered patients, the fevered patients showed a lower lymphocyte proportion (P = 0.000) and lymphocyte count (P = 0.000) as well as higher levels of C-reactive protein (CRP) (P = 0.000) and erythrocyte sedimentation rate (P = 0.000). The proportion of severe cases was significantly elevated in adult fevered patients (P = 0.000). Compared to non-severe fevered patients, severe fevered patients showed a lower lymphocyte count (P = 0.000), a lower lymphocyte proportion (P = 0.000), and higher levels of CRP (P = 0.000). As determined by the multivariate analysis, CRP (OR 1.026, P = 0.018) and lymphocyte proportion (OR 0.924, P = 0.009) were significantly associated with the risk of developing severe events in fevered adult COVID-19 patients. Furthermore, ROC Curve analysis revealed that the area under the curve (AUC) for CRP combined with lymphocyte proportion to diagnose severe events in fevered adult COVID-19 patients was 0.874 (95% CI 0.820–0.927).Conclusions: Adult fevered COVID-19 patients were more likely to progress into severe cases, while CRP and lymphocyte proportion were effective predictors for developing severe events in these patients.
Highlights
The emergence of coronavirus disease 2019 (COVID-19), which was caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was first reported in China in late 2019 [1,2,3,4,5] and has quickly led to outbreaks in other countries, such as Italy, Iran, and South Korea [6,7,8]
All 230 adult patients diagnosed as COVID-19 by March 15, 2020, were included in this study; of these, 175 patients (76.1%) had fever and 55 patients (23.9%) did not have fever
There was no significant difference in age (P = 0.353) and gender (P = 0.440) between fevered and non-fevered COVID-19 patients as well as common underlying diseases, such as hypertension (P = 0.796), diabetes (P = 1.000), and cardiovascular disease (P = 1.000)
Summary
The emergence of coronavirus disease 2019 (COVID-19), which was caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was first reported in China in late 2019 [1,2,3,4,5] and has quickly led to outbreaks in other countries, such as Italy, Iran, and South Korea [6,7,8]. How to block transmission of SARS-CoV-2, early screening of severe cases, and find effective treatments are urgent issues for scientists worldwide. As the most common symptom and sign of infection, fever is generally initiated by a pyrogen, which causes a rise in temperature setting point and increases body heat production [10, 11]. The latest report found that fever was the most common symptom of COVID-19 patients, but more than 10% of patients with COVID-19 did not develop fever [4, 13]. Differences in clinical characteristics and prognosis between fevered and non-fevered COVID-19 patients remain unclear. We presented the clinical characteristics of these patients and analyzed predictors for developing severe events through Logistic regression analysis
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