Xiehe Yixue Zazhi (Sep 2023)
Clinical Characteristics and Inflammatory Markers of Omicron BA.5.2 Variant Infection in Hospitalized Patients and Their Predictive Role in Disease Prognosis
Abstract
Objective To analyze the clinical characteristics and inflammatory indicators of hospitalized patients infected with Omicron BA.5.2 variant, and screen for possible prognostic diagnostic markers. Methods We retrospectively collected clinical data from hospitalized patients with Omicron BA.5.2 variant infection admitted to the People's Hospital of Xinjiang Uygur Autonomous Region from August 1 to November 30, 2022. The patients were divided into mild, common, severe, and critically ill patient groups based on the severity of the disease. The differences in clinical data between the four groups were compared, and binary logistic regression was used to analyze inflammation indicators related to the severity of the disease. Multiple logistic regression method and receiver operator characteristic (ROC) curve were used to analyze the correlation between various indicators and patient prognosis, as well as the evaluation value for disease severity and prognosis. Results A total of 3006 patients who met the inclusion and exclusion criteria were included, including 1522 males (50.63%) and 1484 females (49.37%), with an average age of (58.72±18.01)(14-96) years. According to the severity of the disease, they were classified into mild (40.98%, 1232/3006), ordinary (52.56%, 1580/3006), severe (4.26%, 128/3006), and critically severe (2.20%, 66/3006) groups.There were a significant differences(all P 7.0, while CRP, IL-6, procalcitonin (PCT), D-dimer, troponin T(TnT), troponin Ⅰ(TnⅠ), NLR, SII, platelet to lymphocyte ratio (PLR), the monocyte to lymphocyte ratio (MLR) had a high prognostic diagnostic value for death or survival with the corresponding AUC > 0.70. Conclusions There were significant differences in clinical characteristics among hospitalized patients infected with Omicron BA.5.2 variant strains with different disease severity. Combining CRP, IL-6, D-dimer, PCT, D-dimer, TnT, TnⅠ, NLR, SII, PLR, and MLR prediction models may enable early identification of high-risk populations among hospitalized patients infected with Omicron BA.5.2 variant strains, and provide timely diagnosis and treatment.
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