血小板/淋巴细胞比值(PLR)升高型AECOPD患者临床特征及危险因素分析

The Clinical Features and Risk Factors for Increased Platelet-to-Lymphocyte Ratio (PLR) in Patients with AECOPD

摘要: 目的：探讨血小板/淋巴细胞比值(PLR)升高型慢性阻塞性肺疾病急性加重期(AECOPD)患者的临床特点，并分析与其相关的独立危险因素。方法：本研究为单中心横断面研究。采用非随机抽样法，选取遂宁市中心医院呼吸与危重症医学科2022年10月至2024年9月期间收住入院的AECOPD患者，通过排除标准筛出后，最终纳入325例AECOPD患者。根据PLR中位数(158.59)，分为低PLR型AECOPD患者组(n = 163)，高PLR型AECOPD组(n = 162)。收集资料包括人口学特征、基础疾病及合并症、实验室指标、胸部CT和肺功能等相关资料。首先进行单因素分析，将单因素分析中有统计学差异(P < 0.05)的变量纳入二元Logistic回归模型，从而进一步讨论PLR升高型AECOPD患者的独立危险因素和临床特征。最后，采用列线图(Nomogram)、效验曲线、受试者工作特征(ROC)曲线和决策曲线分析法(DCA)曲线对Logistic回归模型进行验证和可视化展示。结果：单因素分析结果表明低PLR组与高PLR组在以下方面存在显著统计学差异(P < 0.05)：合并社区获得性肺炎(CAP)、血中性粒细胞(NS)、血嗜酸性粒细胞(EOS)、红细胞(RBC)、血红蛋白(Hb)、超敏C反应蛋白(CRP)、降钙素原(PCT)、血沉(ESR)、血肌酐(Cr)、血白蛋白(Hb)、血小板(PLT)和淋巴细胞(LYM)。将以上12个变量纳入二元Logistic回归方程中，结果表明血NS (OR = 1.067)、血EOS (OR = 0.372)和ESR (OR = 1.013)与AECOPD患者的PLR升高独立相关(P均 < 0.1)。进一步分析发现效应曲线平均绝对误差(MAE)为0.011，AUC值为0.648，提示该模型具有良好的预测一致性及中等的预测准确性。DCA曲线显示当nomogram的风险阈值在0.3~0.7时，该模型的预测净获益>0，表明该模型有一定的临床预测价值。结论：本研究结果提示血NS和ESR升高及血EOS减少是PLR升高型AECOPD独立相关的临床特征。该结果提示PLR升高型AECOPD患者的系统性炎症水平可能更加严重，病情可能更为危重，预后欠佳。因此，对于PLR升高型AECOPD患者，应积极的早期干预，预防患者病情的进一步进展。本研究构建的预测模型具有中等预测能力，可为临床初步评估提供参考。

Abstract: Objective: To investigate the clinical characteristics of patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) exhibiting an elevated platelet-to-lymphocyte ratio (PLR) and analyze the independent risk factors associated with this condition. Methods: This cross-sectional study was conducted at a single center, including 325 AECOPD patients from the Department of Respiratory and Critical Care Medicine in Suining Central Hospital, between October 2022 and September 2024. Using the median PLR value of 158.59 as the cutoff, patients were categorized into low-PLR (n = 163) and high-PLR (n = 162) groups. Comprehensive clinical data were collected within 24 hours of admission, encompassing demographics, laboratory tests, chest CT results, pulmonary function parameters. Initial univariate analysis identified significant variables (P < 0.05), which were subsequently incorporated into a binary logistic regression model to determine independent predictors of PLR elevation. Model performance was assessed through nomogram construction, calibration curves, ROC analysis, and decision curve analysis. Results: The univariate analysis identified twelve significant different variables (all P < 0.05) between two groups, which included community-acquired pneumonia (CAP), blood neutrophils (NS) and eosinophils (EOS), red blood cells, inflammatory markers (CRP, PCT, ESR), renal function (Cr), albumin levels, platelet (PLT), and lymphocytes (LYM). Subsequently, binary logistic regression analysis found that blood NS (OR = 1.067), EOS (OR = 0.372), and ESR (OR = 1.013) were independently associated with PLR elevation (P all < 0.1). Internal validation metrics confirmed model reliability, with mean absolute error of 0.011 in calibration curves and area under the ROC curve of 0.648, indicating moderate predictive accuracy. Clinical applicability was evidenced by decision curve analysis showing positive net benefit across the 0.3~0.7 risk threshold range, suggesting certain clinical predictive value. Conclusions: Overall, our results showed that increased ESR and NS, and decreased EOS were independently associated with elevated PLR in the patients with AECOPD, suggesting that the level of systemic inflammation in these patients is higher, the disease is more severe, and the prognosis is poorer. The constructed prediction model has moderate predictive ability, which can provide a reference for preliminary clinical evaluation. Due to the study design and limited sample size, a multicenter cohort study with a larger sample is needed to further explore the clinical prognosis and drug response of these patients.