2026 年第 9 期 第 21 卷

血清相关因子水平与慢性阻塞性肺疾病急性加重期患者预后的关系

Relationship between serum related factor levels and prognosis of patients with acute exacerbation of chronic obstructive pulmonary disease

作者：郭立娟1曹聪2鲍洁1马方旭1张罗元1

英文作者：Guo Lijuan1 Cao Cong2 Bao Jie1 Ma Fangxu1 Zhang Luoyuan1

单位：1河北省胸科医院（河北省肺癌防治研究中心）呼吸与危重症医学科，石家庄050000；2河北省胸科医院（河北省肺癌防治研究中心）全科医学科，石家庄050000

英文单位：1Department of Respiratory and Critical Care Medicine Hebei Chest Hospital(Hebei Lung Cancer Prevention and Treatment Research Center) Shijiazhuang 050000 China; 2Department of General Practice Hebei Chest Hospital(Hebei Lung Cancer Prevention and Treatment Research Center) Shijiazhuang 050000 China

关键词：慢性阻塞性肺疾病；半乳糖凝集素2；热休克蛋白90；细胞黏附分子1

英文关键词：Chronicobstructivepulmonarydisease;Galectin-2;Heatshockprotein90;CelladhesionmoleculeL1

• 摘要：

• 目的 探讨血清半乳糖凝集素2（galectin-2）、热休克蛋白90（HSP90）、细胞黏附分子1（CHL1）水平与慢性阻塞性肺疾病（COPD）急性加重期（AECOPD）患者预后的关系。方法 选取2024年4月至2025年4月河北省胸科医院收治的AECOPD患者120例（AECOPD组）、COPD稳定期患者120例（COPD稳定组）及健康体检者120例（对照组）作为研究对象。对AECOPD患者进行为期1个月的随访，将AECOPD组患者依据预后情况分为预后良好组和预后不良组。检测血清中galectin-2、HSP90、CHL1水平做组间比较。采用多因素Logistic回归分析方法筛选影响AECOPD患者预后状况的独立危险因素，绘制受试者工作特征曲线评价相关因子对AECOPD患者发生不良预后的预测能力。采用Bootstrap重抽样法进行内部验证，进一步通过Hosmer-Lemeshow拟合优度检验对模型校准效果进行统计验证。结果 AECOPD组和COPD稳定组患者血清galectin-2、HSP90、CHL1水平均显著高于对照组；AECOPD组患者三者水平均显著高于COPD稳定组（均P＜0.05）。随访显示预后良好组（75例）和预后不良组（45例）。预后不良组患者血清galectin-2、HSP90、CHL1水平均显著高于预后良好组［（25.6±2.9）μg/L比（22.2±2.6）μg/L、（37±4）μg/L比（32±4）μg/L、（18.7±2.0）μg/L比（16.5±1.7）μg/L］（均P＜0.001）。多因素Logistic回归分析结果表明，galectin-2、HSP90、CHL1均为影响AECOPD患者预后不良的因素（均P＜0.05）。与血清galectin-2（Z=3.440）、HSP90（Z=4.349）、CHL1（Z=2.329）水平单独检测相比，三者联合检测对AECOPD患者预后不良预测的曲线下面积显著升高（均P＜0.05）。内部验证和拟合优度检验结果显示联合检测预测模型拟合良好（χ2=1.989，P=0.981）。结论 AECOPD患者血清中galectin-2、HSP90、CHL1水平均显著升高，三者联合检测能够提高对AECOPD患者预后不良的预测价值。

• Objective To explore the relationship between serum levels of galectin-2, heat shock protein 90 (HSP90), cell adhesion molecule L1 (CHL1) and the prognosis of patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD). Methods A total of 120 patients with AECOPD (AECOPD group), 120 patients with stable COPD (stable COPD group) and 120 healthy physical examinees (control group) admitted to Hebei Chest Hospital from April 2024 to April 2025 were selected as research subjects. Patients with AECOPD were followed up for 1 month and divided into good prognosis subgroup and poor prognosis subgroup according to clinical outcomes. Serum levels of galectin-2, HSP90 and CHL1 were detected and compared among groups. Multivariate Logistic regression analysis was used to screen independent risk factors affecting the prognosis of AECOPD patients. Receiver operating characteristic curves were plotted to evaluate the predictive efficacy of the three indicators for poor prognosis in AECOPD patients. Bootstrap resampling was adopted for internal verification, and Hosmer-Lemeshow goodness-of-fit test was further performed to statistically verify the calibration effect of the model. Results Serum levels of galectin-2, HSP90 and CHL1 in the AECOPD group and stable COPD group were significantly higher than those in the control group, and the three indicators were remarkably elevated in the AECOPD group compared with the stable COPD group (all P＜0.05). Follow-up results showed 75 patients in the good prognosis subgroup and 45 patients in the poor prognosis subgroup. Serum galectin-2, HSP90 and CHL1 levels in the poor prognosis subgroup were significantly higher than those in the good prognosis subgroup ［(25.6±2.9)μg/L vs (22.2±2.6)μg/L, (37±4)μg/L vs (32±4)μg/L, (18.7±2.0)μg/L vs (16.5±1.7)μg/L］(all P＜0.001). Multivariate Logistic regression indicated that galectin-2, HSP90 and CHL1 were independent risk factors for poor prognosis in AECOPD patients (all P＜0.05). Compared with single detection of serum galectin-2 (Z=3.440), HSP90 (Z=4.349) and CHL1 (Z=2.329), combined detection of the three biomarkers achieved a significantly larger area under the curve for predicting poor prognosis in AECOPD patients (all P＜0.05). Internal verification and goodness-of-fit test demonstrated favorable fitting of the combined prediction model (χ2=1.989, P=0.981). Conclusions Serum galectin-2, HSP90 and CHL1 levels are significantly increased in AECOPD patients, and combined detection of the three biomarkers can improve the predictive value for poor prognosis in patients with AECOPD.