术前联合检测NLR和PTAR对肝移植术后早期腹腔感染的预测价值

Predictive value of preoperative combined detection of NLR and PTAR for early abdominal infection after liver transplantation

  • 摘要:
    目的  探讨术前联合检测中性粒细胞/淋巴细胞比值(NLR)及凝血酶原时间国际标准化比值/白蛋白比值(PTAR)对肝移植术后早期腹腔感染的预测价值。
    方法  回顾性分析首都医科大学附属北京友谊医院肝移植中心在2020年1月至2024年4月287例行肝移植手术受者的临床资料,根据术后30 d内是否发生腹腔感染分为感染组(60例)和未感染组(227例),分析感染受者病原菌分布特点及感染时间分布情况。采用Spearman法分析NLR、PTAR与Child-Pugh、术前终末期肝病模型(MELD)评分的相关性,采用单因素和多因素logistic回归分析腹腔感染的危险因素。绘制NLR、PTAR单项及二者联合预测模型的受试者工作特征(ROC)曲线并评估对肝移植术后腹腔感染的预测效能。根据联合模型的截断值将受者分为低危组和高危组,采用Kaplan-Meier法比较两组受者术后30 d内腹腔累积感染率。
    结果  287例肝移植受者术后发生腹腔细菌或真菌感染共60例,感染受者共分离出86株菌株,其中革兰阴性菌感染占58%,革兰阳性菌感染占36%,真菌感染占5%。术前NLR、PTAR与Child-Pugh、MELD评分之间均呈正相关(均为1>r>0,P<0.05)。logistic回归分析结果显示,术前NLR、术前PTAR、术后ICU停留时间、术后并发胆汁漏均为影响受者术后30 d内发生腹腔感染的危险因素。NLR、PTAR、Child-Pugh评分、MELD评分的曲线下面积(AUC)分别是0.771、0.735、0.650、0.741,而联合NLR和PTAR的预测模型的AUC为0.824(95%可信区间:0.763~0.885,P<0.001),截断值为0.168。Kaplan-Meier结果显示,低危组受者术后30 d内腹腔累积感染率低于高危组,差异有统计学意义(P<0.001)。
    结论  术前NLR、PTAR均为肝移植术后30 d内发生腹腔感染的独立危险因素,NLR联合PTAR的预测模型可有效识别肝移植术后早期腹腔感染的高危受者,为早期干预提供依据。

     

    Abstract:
    Objective  To investigate the predictive value of preoperative combined detection of neutrophil-to-lymphocyte ratio (NLR) and prothrombin time-international normalized ratio to albumin ratio (PTAR) for early abdominal infection after liver transplantation.
    Methods  Clinical data of 287 recipients who underwent liver transplantation at the Liver Transplant Center of Beijing Friendship Hospital, Affiliated to Capital Medical University, from January 2020 to April 2024 were retrospectively analyzed. The patients were divided into infection group (n=60) and non-infection group (n=227) based on whether abdominal infection occurred within 30 days after surgery. The distribution characteristics of pathogens and infection time in infected patients were analyzed. Spearman correlation analysis was used to assess the correlation between NLR, PTAR, Child-Pugh score and preoperative model for end-stage liver disease (MELD) score. Univariate and multivariate logistic regression analyses were performed to identify risk factors for abdominal infection. Receiver operating characteristic (ROC) curves were plotted for NLR, PTAR, and the combined prediction model to evaluate their predictive efficacy for abdominal infection after liver transplantation. Based on the cutoff value of the combined model, recipients were divided into low-risk and high-risk groups, and Kaplan-Meier analysis was used to compare the cumulative incidence of abdominal infection within 30 days after surgery between the two groups.
    Results  Among the 287 recipients who underwent liver transplantation, 60 developed bacterial or fungal abdominal infections postoperatively. A total of 86 strains were isolated from infected patients, with Gram-negative bacteria accounting for 58%, Gram-positive bacteria for 36%, and fungi for 5%. Preoperative NLR and PTAR were positively correlated with Child-Pugh and MELD scores (all 1 > r > 0, P < 0.05). Logistic regression analysis showed that preoperative NLR, preoperative PTAR, postoperative ICU stay duration and postoperative biliary leakage were risk factors for abdominal infection within 30 days after surgery. The area under the curve (AUC) for NLR, PTAR, Child-Pugh score and MELD score were 0.771, 0.735, 0.650 and 0.741, respectively. The AUC for the combined NLR and PTAR prediction model was 0.824 (95% confidence interval: 0.763-0.885, P < 0.001), with a cutoff value of 0.168. Kaplan-Meier analysis showed that the cumulative incidence of abdominal infection within 30 days after surgery was lower in the low-risk group than in the high-risk group, with statistically significant difference (P < 0.001).
    Conclusions  Preoperative NLR and PTAR are independent risk factors for abdominal infection within 30 days after liver transplantation. The combined prediction model of NLR and PTAR may effectively identify high-risk recipients for early abdominal infection after liver transplantation, providing basis for early intervention.

     

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