Yu Jie, Jiang Jichang, Fan Caili, Huo Jinlong, Luo Tingting, Zhao Lijin
Department of General Surgery, Digestive Disease Hospital, Affiliated Hospital of Zunyi Medical University, Zunyi Guizhou, China.
Department of Nursing, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, China.
Front Med (Lausanne). 2025 Apr 10;12:1563235. doi: 10.3389/fmed.2025.1563235. eCollection 2025.
Bacterial infection is a common complication of liver transplantation and is associated with high mortality rates. However, multifactor-based early-prediction tools are currently lacking. Therefore, this study investigated the risk factors of early bacterial infections after liver transplantation and used them to establish a nomogram.
We retrospectively collected the clinical data of 232 patients who underwent liver transplantation. We excluded 15 patients aged less than 18 years, 7 patients with infection before transplantation, and 3 patients with incomplete laboratory test results based on the sample exclusion criteria, and finally included 207 liver transplant patients. The patients were divided into the bacterial infection group (75 cases) and non-infected group (132 cases) according to whether bacterial infection had occurred within 30 days after surgery. The associated risk factors were determined using stepwise regression, and a nomogram was established based on the results of the multifactorial analysis. The predictive performance of the model was compared by assessing the area under the receiver operating characteristic curve (AUC-ROC), decision curve analysis (DCA), and the calibration curve, which was validated using cross-validation and repeated sampling.
Preoperative systemic immune inflammation index (SII) (OR = 1.003, = 0.001), duration of surgery (OR = 1.008, = 0.005), duration of postoperative ventilator use (OR = 1.013, = 0.025), neutrophil to lymphocyte ratio (NLR) (OR = 1.017, = 0.024), ICU stay time (OR = 1.125, = 0.015) were independent risk factors for early bacterial infection after liver transplantation. The nomogram was constructed based on the above factors, achieving an AUC of 0.863 (95%CI: 0.808, 0.918), which showed that the mean absolute error between the predicted risk and the actual risk of the model was 0.044. The decision curve analysis showed that it was located above both extreme curves in a range of more than the 14% threshold, which indicated that there was a good clinical benefit in this range. Internal validation using 10-fold cross validation and bootstrap replicate sampling yielded areas under the corrected ROC curves of 0.842 and 0.854, respectively. These results indicate that the developed model exhibits good predictive performance and a moderate error in training and validation.
The nomogram constructed in this study showed good differentiation, calibration, and clinical applicability. It can effectively identify the high-risk group for bacterial infection in the early postoperative period after liver transplantation, while simultaneously helping the transplant team dynamically monitor the key indicators and optimize perioperative management.
细菌感染是肝移植常见的并发症，且与高死亡率相关。然而，目前缺乏基于多因素的早期预测工具。因此，本研究调查了肝移植术后早期细菌感染的危险因素，并利用这些因素建立了列线图。
回顾性收集232例行肝移植患者的临床资料。根据样本排除标准，排除15例年龄小于18岁的患者、7例移植前有感染的患者以及3例实验室检查结果不完整的患者，最终纳入207例肝移植患者。根据术后30天内是否发生细菌感染，将患者分为细菌感染组（75例）和非感染组（132例）。采用逐步回归确定相关危险因素，并根据多因素分析结果建立列线图。通过评估受试者工作特征曲线下面积（AUC-ROC）、决策曲线分析（DCA）和校准曲线来比较模型的预测性能，并使用交叉验证和重复抽样进行验证。
术前全身免疫炎症指数（SII）（OR = 1.003，P = 0.001）、手术时长（OR = 1.008，P = 0.005）、术后呼吸机使用时长（OR = 1.013，P = 0.025）、中性粒细胞与淋巴细胞比值（NLR）（OR = 1.017，P = 0.024）、ICU住院时间（OR = 1.125，P = 0.015）是肝移植术后早期细菌感染的独立危险因素。基于上述因素构建列线图，AUC为0.863（95%CI：0.808，0.918），表明模型预测风险与实际风险之间的平均绝对误差为0.044。决策曲线分析表明，在超过14%阈值的范围内，它位于两条极端曲线之上，这表明在此范围内有良好的临床获益。使用10倍交叉验证和自助重复抽样进行内部验证，校正后ROC曲线下面积分别为0.842和0.854。这些结果表明，所建立的模型在训练和验证中表现出良好的预测性能和适度的误差。
本研究构建的列线图具有良好的区分度、校准度和临床适用性。它可以有效识别肝移植术后早期细菌感染的高危人群，同时帮助移植团队动态监测关键指标并优化围手术期管理。
