Wang Zhi, Feng Cheng, Chang Guojing, Liu Hao, Zhang Wenchao
Department of Plastic & Cosmetic Surgery, Peking, Union Medical College Hospital, No.41 Damucang Hutong, Xicheng District, Beijing, 100032, China.
BMC Infect Dis. 2025 Mar 17;25(1):372. doi: 10.1186/s12879-025-10761-5.
This study explores the potential of combining digital polymerase chain reaction (PCR) with cutaneous infection biomarkers for the early diagnosis and monitoring of wound infections caused by multiple bacteria.
We selected a cohort of 276 patients with wounds who were admitted to our hospital from July 2022 to July 2023. These patients were categorized into 46 infection cases and 230 non-infection cases based on clinical evaluation. Clinical data, including routine blood tests [Red Blood Cell count (RBC), Hemoglobin (Hb), White Blood Cell count (WBC), Platelets (PLT)], D-dimer (D-D), and blood biochemistry parameters (liver function, lipid profile, blood glucose, renal function), were collected from both groups. Bacterial cultures were obtained from the infection group, and digital PCR targeting multiple bacteria (Pseudomonas aeruginosa, Staphylococcus aureus, Acinetobacter baumannii, Escherichia coli, Klebsiella pneumoniae) was performed. Logistic regression analysis was conducted to identify risk factors for wound infection, and receiver operating characteristic (ROC) curves were generated to assess the diagnostic performance of digital PCR in conjunction with cutaneous infection biomarkers.
No significant differences were observed between the infection and non-infection groups regarding age, gender, body mass index (BMI), or wound characteristics (P > 0.05). However, the infection group exhibited significantly higher levels of RBC, Hb, WBC, PLT, and D-D (P < 0.05). Key factors influencing wound infections included WBC, PLT, glycosylated hemoglobin, and the specific bacteria identified. ROC curve analysis revealed area under the curve (AUC) values for individual markers, with a combined AUC of 0.899, demonstrating excellent diagnostic performance.
Digital PCR, when combined with cutaneous infection biomarkers, proves to be an effective diagnostic tool for wound infections. This approach shows great promise in clinical applications, with the potential to significantly improve patient outcomes.
本研究探讨数字聚合酶链反应（PCR）与皮肤感染生物标志物相结合用于早期诊断和监测多种细菌引起的伤口感染的潜力。
我们选取了2022年7月至2023年7月期间我院收治的276例伤口患者。根据临床评估，将这些患者分为46例感染病例和230例非感染病例。收集两组患者的临床资料，包括血常规[红细胞计数（RBC）、血红蛋白（Hb）、白细胞计数（WBC）、血小板（PLT）]、D - 二聚体（D - D）以及血液生化参数（肝功能、血脂、血糖、肾功能）。从感染组获取细菌培养物，并进行针对多种细菌（铜绿假单胞菌、金黄色葡萄球菌、鲍曼不动杆菌、大肠埃希菌、肺炎克雷伯菌）的数字PCR检测。进行逻辑回归分析以确定伤口感染的危险因素，并绘制受试者工作特征（ROC）曲线以评估数字PCR结合皮肤感染生物标志物的诊断性能。
感染组与非感染组在年龄、性别、体重指数（BMI）或伤口特征方面无显著差异（P > 0.05）。然而，感染组的RBC、Hb、WBC、PLT和D - D水平显著更高（P < 0.05）。影响伤口感染的关键因素包括WBC、PLT、糖化血红蛋白以及鉴定出的特定细菌。ROC曲线分析显示各个标志物的曲线下面积（AUC）值，联合AUC为0.899，显示出优异的诊断性能。
数字PCR与皮肤感染生物标志物相结合被证明是伤口感染的有效诊断工具。这种方法在临床应用中显示出巨大潜力，有可能显著改善患者预后。
