刘欢, 黄晓玲, 代梦莹, 郭杰洁, 高峰. Omicron BA.5.2变异株感染住院患者临床特征及炎症指标对疾病预后的预测作用[J]. 协和医学杂志, 2023, 14(5): 1038-1045. DOI: 10.12290/xhyxzz.2023-0055
引用本文: 刘欢, 黄晓玲, 代梦莹, 郭杰洁, 高峰. Omicron BA.5.2变异株感染住院患者临床特征及炎症指标对疾病预后的预测作用[J]. 协和医学杂志, 2023, 14(5): 1038-1045. DOI: 10.12290/xhyxzz.2023-0055
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

Omicron BA.5.2变异株感染住院患者临床特征及炎症指标对疾病预后的预测作用

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

  • 摘要:
      目的  分析Omicron BA.5.2变异株感染住院患者临床特征及炎症指标,筛选可能的预后诊断标志物。
      方法  回顾性收集2022年8月1日—11月30日新疆维吾尔自治区人民医院收治的Omicron BA.5.2变异株感染住院患者临床资料,根据疾病严重程度将患者分为轻型、普通型、重型和危重型,比较4组临床资料差异,采用二元Logistic回归法分析与疾病严重程度相关的炎症指标,采用多因素Logistic回归法分析各指标与疾病预后的相关性,采用受试者工作特征(receiver operator characteristic, ROC)曲线分析各指标对疾病严重程度和预后的诊断价值。
      结果  共纳入符合纳入和排除标准的3006例患者,其中男性1522例(50.63%)、女性1484例(49.37%);平均年龄为(58.72±18.01)(14~96)岁;根据疾病严重程度分为轻型(40.98%,1232/3006)、普通型(52.56%,1580/3006)、重型(4.26%,128/3006)、危重型(2.20%,66/3006);各组在合并基础疾病(心脏病、糖尿病、高血压、肾脏病、肺部疾病、恶性肿瘤、脑部疾病、病毒性肝炎和自身免疫性疾病)方面均具有显著性差异(P均<0.01);住院期间共死亡74例(2.43%),其中危重型46例(63.01%)、重型19例(26.03%)、普通型7例(9.60%)、轻型2例(2.74%),年龄≥70岁的死亡患者占比为75.68%(56/74),所有死亡患者均为合并基础疾病人群;C-反应蛋白(C-reactive protein,CRP)、白蛋白是疾病严重程度的独立危险因素,且CRP与疾病严重程度呈显著正相关(P=0.002),白蛋白水平与疾病严重程度呈显著负相关(P<0.001);CRP、全身炎症反应指数(systemic inflammatory response index,SIRI)、全身免疫炎症指数(systemic immune-inflammation index,SII)为疾病预后的独立危险因素,且CRP(P=0.027)、SIRI(P=0.025)与疾病预后呈显著正相关,SII与疾病预后呈显著负相关(P=0.021);CRP、白细胞介素-6(interleukin-6,IL-6)、D-二聚体、中性粒细胞与淋巴细胞比值(neutrophil to lymphocyte ratio,NLR)对应的曲线下面积(area under the curve,AUC)均>0.70,对疾病严重程度分型的诊断价值较高;CRP、IL-6、降钙素原(procalcitonin, PCT)、D-二聚体、肌钙蛋白T(troponin T,TnT)、肌钙蛋白Ⅰ(troponin Ⅰ, TnⅠ)、NLR、SII、血小板与淋巴细胞比值(platelet to lymphocyte ratio,PLR)、单核细胞与淋巴细胞比值(monocyte to lymphocyte ratio,MLR)对应的AUC均>0.70,对死亡或存活的预后诊断价值较高。
      结论  不同疾病严重程度的Omicron BA.5.2变异株感染住院患者临床特征比较具有显著差异,结合CRP、IL-6、PCT、D-二聚体、TnT、TnⅠ、NLR、SII、PLR、MLR的预测模型可早期识别Omicron BA.5.2变异株感染住院患者中的高危人群,及时进行早期诊断和治疗。

     

    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 < 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.

     

/

返回文章
返回