Abstract：Objective: To analyze the influencing factors of adverse outcomes in patients with chronic obstructive pulmonary disease (COPD), and to explore the predictive value of serum lymphocyte-to-lymphocyte ratio (NLR), prealbumin (PA), and procalcitonin (PCT) levels on adverse outcomes. Methods: Totally 102 patients with COPD admitted to the hospital from April 2020 to April 2023 were divided into a good prognosis group (n=87) and a poor prognosis group (n=15) according to the clinical outcomes. Univariate and multivariate logistic regression analyses were used to analyze the factors influencing adverse outcomes of patients, and the receiver characteristic operating curve (ROC) was used to analyze the predictive efficacy of PA and PCT levels for adverse outcomes. Results: The age, number of acute exacerbation hospitalizations in the past 1 year, concurrent respiratory failure, disturbance of consciousness, NLR, mMRC grading, PA, PCT, LVEF, FEV1 and FEV1/FVC exhibited statistical differences between groups (P<0.05). Logistic regression analysis indicated that age, number of acute exacerbation hospitalizations in the past 1 year, concurrent respiratory failure, disturbance of consciousness, mMRC grading, NLR, PCT and low LVEF, FEV1 and FEV1/FVC were high risk factors for adverse outcomes in patients with COPD, and the elevation of PA is a protective factor (OR=1.839, CI: 0.992-3.409; OR=2.090, CI: 1.107-3.943; OR=2.484, CI: 1.224-5.041; OR=2.125, CI: 1.100-4.106; OR=4.195, CI: 2.048-8.597; OR=2.493, CI: 1.355-4.587; OR=2.227, CI: 1.418-3.498; OR=0.958, CI: 0.919-0.998; OR=0.950, CI: 0.914-0.988; OR=0.946, CI: 0.905-0.990; OR=0.943, CI: 0.901-0.986, P<0.05). ROC curve analysis revealed that the area under the curve (AUC), sensitivity, and specificity of the combination of PCT, PA, and NLR in predicting adverse outcomes were 0.939, 93.33% and 93.10%, which were significantly better than those of each indicator alone (P<0.05). Conclusion: The adverse outcomes of patients with COPD are affected by age, mMRC grading, PA, PCT, NLR, and pulmonary function indicators. The combined detection of PA, PCT, and NLR can enhance the predictive value of adverse outcomes.
何洁, 刘婧, 赵锐, 王颖. 慢性阻塞性肺疾病患者不良结局影响因素及血清NLR PA PCT水平对其预测价值[J]. 河北医学, 2025, 31(12): 2049-2055.
HE Jie, LIU Jing, ZHAO Rui, et al. Influencing Factors of Adverse Outcomes in Patients with Chronic Obstructive Pulmonary Disease and Predictive Value of Serum NLR PA and PCT Levels. HeBei Med, 2025, 31(12): 2049-2055.
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2025, Vol. 31 
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