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Analysis of inflammatory parameters and disease severity for 88 hospitalized COVID-19 patients in Wuhan, China
Xia Xu1, Mu-Qing Yu2, Qian Shen3
1Department of Geriatric Medicine, Qilu Hospital of Shandong University.
Insights
Clinical features and inflammatory cytokines can predict coronavirus disease 2019 (COVID-19) severity. This study identified key indicators to help clinicians promptly recognize severe cases for timely treatment.
Area of Science:
- Infectious Diseases
- Clinical Medicine
- Epidemiology
Background:
- The rapid global spread of coronavirus disease 2019 (COVID-19) necessitates understanding its clinical spectrum and predictors of severity.
- Identifying specific patient characteristics and biomarkers is crucial for effective management during the pandemic's outbreak phase.
Purpose of the Study:
- To elucidate the clinical characteristics of hospitalized COVID-19 patients.
- To investigate the correlation between clinical features, laboratory findings, and disease severity.
- To identify potential indicators for early recognition of severe and critical COVID-19 cases.
Main Methods:
- Retrospective analysis of demographic, clinical, and laboratory data from 88 hospitalized COVID-19 patients.
- Patients were categorized into moderate, severe, and critically ill groups.
- Statistical analysis was performed to identify significant associations with disease severity.
Main Results:
- The study included 88 patients with an average age of 57.11 years; common comorbidities included hypertension and diabetes mellitus.
- Fever, cough, and dyspnea were prevalent symptoms. Critically ill patients exhibited higher rates of lymphocytopenia and elevated levels of inflammatory markers such as IL-6, TNF-α, and LDH.
- Age, comorbidities, lymphocyte count, eosinophil count, ferritin, CRP, LDH, PT, and inflammatory cytokines were significantly associated with COVID-19 severity.
Conclusions:
- Specific clinical characteristics and inflammatory cytokine profiles can serve as indicators of COVID-19 severity during the outbreak.
- These findings can aid clinicians in timely identification of severe and critical cases.
- Early recognition facilitates focused and expectant treatment strategies for improved patient outcomes.
Abstract:
Background and aim: The outbreak of coronavirus disease 2019 (COVID-19) is quickly turning into a pandemic. We aimed to further clarify the clinical characteristics and the relationship between these features and disease severity. Methods: In this retrospective single-center study, demographic, clinical and laboratory data were collected and analyzed among moderate, severe and critically ill group patients. Results: 88 hospitalization patients confirmed COVID-19 were enrolled in this study. The average age of the patients was 57.11 years (SD, ±15.39). Of these 88 patients, the median body mass index (BMI) was 24.03 (IQR, 21.64-26.61; range 15.05-32.39), the median duration from disease onset to hospital admission were 11 days (IQR, 6.50-14.50). 46.59% patients had one or more comorbidities, with hypertension being the most common (26.14%), followed by diabetes mellitus (12.50%) and coronary atherosclerotic heart disease (CAD) (7.95%). Common symptoms at onset of disease were fever (71.59%), cough (59.09%), dyspnea (38.64%) and fatigue (29.55%). 88 patients were divided into moderate (47 [53.41%]), severe (32 [36.36%]) and critically ill (9 [10.23%]) groups. Compared with severe and moderate patients, lymphocytopenia occurred in 85.71% critically ill patients, and serum IL-2R, IL-6, IL-8, TNF-α, LDH, and cTnI were also increased in 71.42%, 83.33%, 57.14%, 71.43%, 100% and 42.86% in critically ill patients. Through our analysis, the age, comorbidities, lymphocyte count, eosinophil count, ferritin, CRP, LDH, PT and inflammatory cytokines were statistically significant along with the disease severity. Conclusion: We found some clinical characteristic and inflammatory cytokines could reveal the severity of COVID-19 during the outbreak phage. Our research could assist the clinicians recognize severe and critically ill patients timely and focus on the expectant treatment for each patient.
