Volume 14 Issue 5
Sep.  2023
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LIU Huan, HUANG Xiaoling, DAI Mengying, GUO Jiejie, GAO feng. Clinical Characteristics and Inflammatory Markers of Omicron BA.5.2 Variant Infection in Hospitalized Patients and Their Predictive Role in Disease Prognosis[J]. Medical Journal of Peking Union Medical College Hospital, 2023, 14(5): 1038-1045. doi: 10.12290/xhyxzz.2023-0055
Citation: LIU Huan, HUANG Xiaoling, DAI Mengying, GUO Jiejie, GAO feng. Clinical Characteristics and Inflammatory Markers of Omicron BA.5.2 Variant Infection in Hospitalized Patients and Their Predictive Role in Disease Prognosis[J]. Medical Journal of Peking Union Medical College Hospital, 2023, 14(5): 1038-1045. doi: 10.12290/xhyxzz.2023-0055

Clinical Characteristics and Inflammatory Markers of Omicron BA.5.2 Variant Infection in Hospitalized Patients and Their Predictive Role in Disease Prognosis

doi: 10.12290/xhyxzz.2023-0055
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  • Corresponding author: GAO Feng, E-mail: xjgf@sina.com
  • Received Date: 2023-02-03
  • Accepted Date: 2023-04-03
  • Publish Date: 2023-09-30
  •   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 < 0.01) in the merging of underlying diseases including cardiac disease, diabetes, hypertension, kidney disease, lung disease, malignant tumor, brain disease, viral hepatitis and autoimmune disease among each group. During the hospitalization period, a total of 74 cases (2.43%) died, including 46 cases of severe illness (63.01%), 19 cases of severe illness (26.03%), 7 cases of ordinary illness (9.60%), and 2 cases of mild illness (2.74%). The proportion of death patients aged≥70 years old was 75.68%(56/74), and all deaths were among those with underlying diseases. C-reactive protein(CRP) and albumin levels were independent risk factors for disease severity, and CRP was significantly positively correlated with disease severity(P=0.002), while albumin levels were significantly negatively correlated with disease severity (P < 0.001). CRP, systemic inflammatory response index (SIRI), and systemic immune inflammation index (SII) were independent risk factors for disease prognosis, and CRP(P=0.027) and SIRI(P=0.025) were significantly positively correlated with disease prognosis, while SII was significantly negatively correlated with disease prognosis (P=0.021). CRP, interleukin-6 (IL-6), D-dimer, and neutrophil to lymphocyte ratio (NLR) had high diagnostic value for disease severity classification with the corresponding area under the aurve(AUC) > 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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