多指标联合评估对慢性阻塞性肺疾病病情严重程度的预测价值

Predictive Value of Multi-Index Combined Assessment for the Severity of Chronic Obstructive Pulmonary Disease

摘要: 目的：探讨多指标联合评估模型对慢性阻塞性肺疾病(COPD)病情严重程度分级的预测价值。方法：采用横断面研究设计，纳入80例COPD患者(按GOLD标准分级)和80例健康对照者。评估指标包括肺功能(FEV1%预计值、FVC、FEV1/FVC)、炎症指标(hs-CRP、中性粒细胞/淋巴细胞比值)、凝血功能(D-二聚体、纤维蛋白原)及代谢指标(同型半胱氨酸)。采用方差分析、LASSO回归和机器学习算法筛选关键预测变量并构建综合评估模型。结果：研究发现，随着COPD病情加重，全身炎症标志物(hs-CRP: GOLD I vs. IV, 30.82 vs. 41.56 mg/L, P < 0.05)和凝血功能异常(D-二聚体：0.97 vs. 0.71 μg/mL)呈阶梯式上升。由FEV1%、hs-CRP和D-二聚体组成的联合预测模型表现出最优的鉴别能力(AUC = 0.923, 95%CI: 0.891~0.955)，显著优于单项肺功能指标(FEV1% AUC = 0.83)。关键发现包括：D-二聚体与FEV1/FVC比值呈强负相关(r = −0.78, P < 0.001)；hs-CRP联合D-二聚体对重度患者的识别灵敏度达92%；同型半胱氨酸水平在中–重度病例间存在显著差异(13.6 vs. 7.6 μmol/L, P < 0.001)。结论：多指标联合评估模型整合了肺功能、炎症和凝血功能参数，相较于传统的单一指标评估方法，能更精准地预测COPD病情严重程度，具有更高的临床应用价值。

Abstract: Objective: To explore the predictive value of a multi-index combined assessment model for disease severity classification in chronic obstructive pulmonary disease (COPD). Methods: A cross-sectional study was conducted on 80 COPD patients (stratified by GOLD criteria) and 80 healthy controls. Comprehensive assessments included pulmonary function (FEV1% predicted value, FVC, FEV1/FVC ratio), inflammatory markers (hs-CRP, neutrophil-to-lymphocyte ratio), coagulation parameters (D-dimer, fibrinogen), and metabolic indicators (homocysteine). ANOVA, LASSO regression, and machine learning modeling were performed to identify key predictive variables and construct an integrated evaluation model. Results: The study demonstrated significant stepwise increases in systemic inflammation markers (hs-CRP: GOLD I vs. IV, 30.82 vs. 55.56 vs. 41.56 mg/L, P < 0.05) and coagulation dysfunction (D-dimer: 0.97 vs. 0.71 μg/mL) with disease progression. The combined predictive model comprising FEV1%, hs-CRP, and D-dimer demonstrated optimal discriminatory ability (AUC = 0.923, 95%CI: 0.891~0.955) compared to single pulmonary function indicator assessments (FEV1% AUC = 0.83). Key findings included: D-dimer was strongly negatively correlated with the FEV1/FVC ratio (r = −0.78, P < 0.001); The combination of hs-CRP and D-dimer achieved a sensitivity of 92% for identifying severe cases; Homocysteine levels showed significant differences between moderate and severe cases (13.6 vs. 7.6 μmol/L, P < 0.001). Conclusion: The multi-index combined assessment model synergistically integrates pulmonary function, inflammatory, and coagulation function parameters, and it can more accurately predict the severity of COPD and has higher clinical application value compared to conventional single-index assessment methods.