He Longxi, Gan Weigang, Xiao Sa, Shi Yu, Fu Mengjie, Wu Li, Zhang Jian
Department of Pharmacy, West China Hospital, Sichuan University, Chengdu, 610041, China.
Department of Otolaryngology, Head and Neck Surgery, West China Hospital, West China Medical School, Sichuan University, Chengdu, 610041, China.
Sci Rep. 2025 Apr 23;15(1):14113. doi: 10.1038/s41598-025-97895-3.
The systemic immune-inflammation index (SII) is a newly identified marker of inflammation., and the relationship between chronic bronchitis (CB) and inflammation is closely associated. However, the influence of SII on CB remains unclear at present.This cross-sectional study was conducted using data from individuals with complete SII and CB records from the 2001-2018 National Health and Nutrition Examination Survey (NHANES). Binary weighted logistic regression was employed to investigate the relationship between SII and CB risk. Additionally, restricted cubic spline regression models and segmented regression models were used to examine nonlinear relationships and threshold effects. Receiver operating characteristic (ROC) curves were adopted to evaluate the predictive value of SII for CB. Stratified analysis was adopted to assess the association between SII and CB in different populations. After adjusting for all covariables, there was a significant positive relevance observed between log-transformed SII (log (SII)) with CB (OR = 1.52, 95% CI: 1.27-1.82, P < 0.001). A nonlinear dose-response relationship with the threshold of 8.14 was observed between log (SII) and CB risk. When log (SII) exceeded 8.14, each unit increase in log (SII) was associated with a 1.31-fold increase in the risk of CB (OR = 1.31, 95% CI: 1.22-1.40, P < 0.001). Furthermore, ROC curves revealed strong predictive capability of SII for CB (AUC = 0.729). Elevated SII levels are associated with an increased prevalence of CB. Furthermore, a non-linear association exists between SII and the increased risk of CB.
全身免疫炎症指数（SII）是一种新发现的炎症标志物，与慢性支气管炎（CB）和炎症之间的关系密切相关。然而，目前SII对CB的影响尚不清楚。本横断面研究使用了2001 - 2018年美国国家健康与营养检查调查（NHANES）中具有完整SII和CB记录的个体数据。采用二元加权逻辑回归研究SII与CB风险之间的关系。此外，使用受限立方样条回归模型和分段回归模型来检验非线性关系和阈值效应。采用受试者工作特征（ROC）曲线评估SII对CB的预测价值。采用分层分析评估不同人群中SII与CB之间的关联。在调整所有协变量后，观察到对数转换后的SII（log（SII））与CB之间存在显著正相关（OR = 1.52，95% CI：1.27 - 1.82，P < 0.001）。在log（SII）与CB风险之间观察到非线性剂量反应关系，阈值为8.14。当log（SII）超过8.14时，log（SII）每增加一个单位，CB风险增加1.31倍（OR = 1.31，95% CI：1.22 - 1.40，P < 0.001）。此外，ROC曲线显示SII对CB具有较强的预测能力（AUC = 0.729）。SII水平升高与CB患病率增加相关。此外，SII与CB风险增加之间存在非线性关联。
