摘要
目的探索泛免疫炎症值(Pan-Immune-Inflammation Value,PIV)与慢性阻塞性肺疾病(简称慢阻肺)之间的关联,评估PIV在预测慢阻肺发病风险中的潜在价值。方法研究基于2013年至2023年国家健康与营养调查(NHANES)数据库,共纳入20304名参与者。PIV通过中性粒细胞、血小板、单核细胞和淋巴细胞计数计算得出,并以Log 10形式进行变换处理。研究采用加权χ^(2)检验或加权t检验比较组间差异,并构建多变量逻辑回归模型(Logistic Regression),调整年龄、性别、BMI、教育水平、贫困收入比率、饮酒、吸烟、高血压、糖尿病、哮喘和冠心病等因素。此外,利用限制性三次样条(RCS)分析剂量-反应关系,绘制受试者工作特征曲线(ROC)评估预测效能。结果在未调整任何协变量的情况下,Log 10 PIV每升高一个单位,患慢阻肺的比值比(OR)为3.67(95%CI 2.86~4.72,P<0.001)。即使在全面调整多个混杂因素后,这种关联仍然显著[模型4:OR(95%CI)=1.93(1.48~2.52),P<0.001]。Log 10 PIV四分位数(Q4)人群占比在慢阻肺组明显高于非慢阻肺组(P<0.001),且随着Log 10 PIV的升高,高血压、糖尿病、冠心病、哮喘和慢阻肺发病率逐渐增加。非线性剂量反应关系显示J型趋势,但在线性模型中,慢阻肺风险随Log 10 PIV水平升高而增加。在逐步纳入年龄、性别、BMI及其他混杂因素,ROC曲线下面积(AUC)从模型1的0.631逐步提升至模型4的0.854,这表明,基于Log 10 PIV构建的多因素预测模型通过整合多个变量,显著提升了整体风险识别和预测慢阻肺的能力。结论随PIV升高慢阻肺发病风险增加,提示PIV作为慢阻肺风险预测工具的潜力,有助于早期识别高危个体并可能改善患者的临床结局。
Objective To explore the association between the Pan-Immune-Inflammation Value(PIV)and Chronic Obstructive Pulmonary Disease(COPD),and to evaluate the potential value of PIV in predicting the risk of COPD.Methods The study was based on the National Health and Nutrition Survey(NHANES)database from 2013 to 2023,and a total of 20,304 participants were included.PIV was calculated based on neutrophil,platelet,monocyte,and lymphocyte counts and is transformed in the form of Log 10.The study used a weighted χ^(2) test or a weighted t test to compare the differences between groups and constructed a multivariate Logistic Regression model,adjusting for factors such as age,gender,BMI,education level,poverty income ratio,alcohol consumption,smoking,hypertension,diabetes,asthma,and coronary heart disease.In addition,the dose-response relationship was analyzed using restricted cubic splines(RCS),and the receiver operating characteristic curve(ROC)was plotted to evaluate the predictive efficacy.Results The results showed that without adjusting for any covariates,each one-unit increase in Log 10 PIV was associated with an odds ratio(OR)of 3.67(95%CI 2.86-4.72,P<0.001)for COPD.Even after adjusting for multiple confounding factors,this association remained significant[Model 4:OR(95%CI)=1.93(1.48-2.52),P<0.001].The proportion of individuals in the highest quartile(Q4)of Log 10 PIV was significantly higher in the COPD group than in the non-COPD group(P<0.001),and as Log 10 PIV increased,the incidence of hypertension,diabetes,coronary heart disease,asthma,and COPD also increased.The non-linear dose-response relationship showed a J-shaped trend,but in the linear model,the risk of COPD increased with higher levels of Log 10 PIV.The area under the ROC curve(AUC)increased from 0.631 in Model 1 to 0.854 in Model 4 as age,gender,BMI,and other confounding factors were gradually included.This indicated that after controlling for interfering variables,the multivariate predictive model based on Log 10 PIV performs better in overall risk identification and prediction of COPD.Conclusion With the increase of PIV,the risk of COPD increases,suggesting the potential of PIV as a risk prediction tool for COPD,which is helpful for the early identification of high-risk individuals and may improve the clinical outcomes of patients.
作者
朱亚军
包拯
徐志
马丽超
ZHU Yajun;BAO Zheng;XU Zhi;MA Lichao(Department of Respiratory and Critical Care Medicine,Zhangjiagang Fifth People′s Hospital,Zhangjiagang,Jiangsu 215600,China;Department of Science and Education,Zhangjiagang Fifth People′s Hospital,Zhangjiagang,Jiangsu 215600,China;Department of Respiratory and Critical Care Medicine,Wuxi Branch of Ruijin Hospital,Affiliated with Shanghai Jiao Tong University School of Medicine,Wuxi,Jiangsu 214000,China)
出处
《临床肺科杂志》
2025年第9期1404-1412,共9页
Journal of Clinical Pulmonary Medicine
基金
张家港市青年科技项目(ZJGQNKJ202219)。
关键词
泛免疫炎症值
慢性阻塞性肺疾病
风险预测
炎症标志物
Pan-Immune-Inflammation Value(PIV)
Chronic obstructive pulmonary disease
Risk prediction
Inflammatory markers
