Univariate logistic regression analysis.

IntroductionHeparin-binding protein is an inflammatory factor with predictive value for sepsis and participates in the inflammatory response through antibacterial effects, chemotaxis, and increased vascular permeability. The role of heparin-binding protein in sepsis has been progressively demonstrated, but few studies have been conducted in the context of polytrauma combined with bacterial infections. This study aims to investigate the predictive value of heparin-binding protein for bacterial infections in patients with severe polytrauma.Materials and methodsThis is a prospective single-center study. Patients with polytrauma in the emergency intensive care unit were selected for the study, and plasma heparin-binding protein concentrations and other laboratory parameters were measured within 48 hours of admission to the hospital. A two-sample comparison and univariate logistic regression analysis investigated the relationship between heparin-binding protein and bacterial infection in polytrauma patients. A multifactor logistic regression model was constructed, and the ROC curve was plotted.ResultsNinety-seven patients with polytrauma were included in the study, 43 with bacterial infection and 54 without infection. Heparin-binding protein was higher in the infected group than in the control group [(32.00±3.20) ng/mL vs. (18.52±1.33) ng/mL, P = 0.001]. Univariate logistic regression analysis shows that heparin-binding protein is related to bacterial infection (OR = 1.10, Z = 3.91, 95%CI:1.05~1.15, P = 0.001). Multivariate logistic regression equations showed that patients were 1.12 times more likely to have bacterial infections for each value of heparin-binding protein increase, holding neutrophils and Procalcitonin (PCT) constant. ROC analysis shows that heparin-binding protein combined with neutrophils and PCT has better predictive value for bacterial infection [AUC = 0.935, 95%CI:0.870~0.977].ConclusionsHeparin-binding protein may predict bacterial infection in patients with severe polytrauma. Combining heparin-binding protein, PCT, and neutrophils may improve bacterial infection prediction.

引言
肝素结合蛋白（Heparin-binding protein）是一种对脓毒症（sepsis）具有预测价值的炎症因子，可通过抗菌作用、趋化作用及升高血管通透性参与炎症反应。目前肝素结合蛋白在脓毒症中的作用已逐步得到证实，但针对多发伤（polytrauma）合并细菌感染场景的相关研究仍较少。本研究旨在探讨肝素结合蛋白对重症多发伤患者细菌感染的预测价值。

材料与方法
本研究为前瞻性单中心研究。纳入急诊重症监护室（Emergency Intensive Care Unit）内的多发伤患者，于入院48小时内检测其血浆肝素结合蛋白浓度及其他实验室指标。采用两样本比较及单因素logistic回归分析，探讨多发伤患者中肝素结合蛋白与细菌感染的关联；构建多因素logistic回归模型，并绘制受试者工作特征曲线（Receiver Operating Characteristic curve，ROC）。

结果
本研究共纳入97例多发伤患者，其中43例合并细菌感染，54例未发生感染。感染组患者的肝素结合蛋白水平显著高于对照组[(32.00±3.20)ng/mL vs. (18.52±1.33)ng/mL，P=0.001]。单因素logistic回归分析显示，肝素结合蛋白与多发伤患者的细菌感染显著相关（比值比OR=1.10，Z=3.91，95%置信区间CI：1.05~1.15，P=0.001）。多因素logistic回归方程显示，在中性粒细胞（neutrophils）与降钙素原（Procalcitonin, PCT）水平固定的前提下，肝素结合蛋白每升高1个单位，患者发生细菌感染的风险增加1.12倍。受试者工作特征曲线分析显示，肝素结合蛋白联合中性粒细胞与PCT对细菌感染具有更优的预测效能[曲线下面积AUC=0.935，95%置信区间CI：0.870~0.977]。

结论
肝素结合蛋白可用于预测重症多发伤患者的细菌感染风险；联合检测肝素结合蛋白、PCT与中性粒细胞，可进一步提升细菌感染的预测效能。