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已发表论文
基于中性粒细胞与淋巴细胞比值（NLR）和凝血酶原时间-国际标准化比值（PT-INR）与白蛋白比值（PTAR）的列线图模型对原位肝移植术后早期细菌性腹腔内感染的预测价值
Authors Peng HB , Liu Y , Hou F, Zhao S , Zhang YZ , He ZY, Cui TT, Liu JY, Xiong HF , Sun LY
Received 7 October 2025
Accepted for publication 10 December 2025
Published 9 January 2026 Volume 2026:19 571498
DOI https://doi.org/10.2147/JIR.S571498
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Fatih Türker
Hua-Bin Peng,1 Ying Liu,1 Fei Hou,1 Shuang Zhao,1 Yi-Zhi Zhang,1 Zhi-Ying He,1 Ting-Ting Cui,1 Jing-Yi Liu,1 Hao-Feng Xiong,1 Li-Ying Sun1– 5
1Department of Critical Liver Diseases, National Clinical Research Center for Digestive Diseases, Beijing Friendship Hospital, Capital Medical University, Beijing, People’s Republic of China; 2Liver Transplantation Center, National Clinical Research Center for Digestive Diseases, Beijing Friendship Hospital, Capital Medical University, Beijing, People’s Republic of China; 3Beijing Key Laboratory of Organ Cultivation and Organ Protection in Transplantation, Beijing Friendship Hospital, Capital Medical University, Beijing, People’s Republic of China; 4State Key Laboratory of Digestive Health, Beijing, People’s Republic of China; 5Laboratory for Clinical Medicine, Capital Medical University, Beijing, People’s Republic of China
Correspondence: Li-Ying Sun, Department of Critical Liver Diseases, Beijing Friendship Hospital, Capital Medical University, Number 101, Luyuan East Road, Tongzhou District, Beijing, 101100, People’s Republic of China, Email sunxlx@outlook.com Hao-Feng Xiong, Department of Critical Liver Diseases, Beijing Friendship Hospital, Capital Medical University, Number 101, Luyuan East Road, Tongzhou District, Beijing, 101100, People’s Republic of China, Email Xionghaofengmd@qq.com
Purpose: To identify risk factors for bacterial intra-abdominal infections (IAIs) after orthotopic liver transplantation (OLT) and establish a nomogram prediction model based on preoperative neutrophil-to-lymphocyte ratio (NLR) and preoperative prothrombin time-international normalized ratio (PT-INR)-to-albumin ratio (PTAR).
Patients and Methods: We retrospectively analyzed 261 patients who received OLT between January 2020 and April 2024 in Beijing Friendship Hospital. Independent risk factors for bacterial IAIs within 30 days postoperatively were identified by logical regression analysis. The area under the receiver operating characteristic (ROC) curve (AUC) was calculated to evaluate the predictive performance of NLR and PTAR as well as the nomogram model based on them. Hepatic function was evaluated using the Child–Turcotte–Pugh (CTP) score and the Model for End-Stage Liver Disease (MELD) score.
Results: Fifty patients (19.2%, 50/261) developed postoperative bacterial IAIs. The majority of the 66 isolated strains were gram-negative (63.6%). Most infections (74.0%, 37/50) occurred within two weeks postoperatively. Multivariate logistic regression analysis identified preoperative NLR, preoperative PTAR, acute physiology and chronic health evaluation II (APACHE II) score, and biliary leakage as independent risk factors. A nomogram-based prediction model was constructed utilizing the identified independent risk factors. Internal validation was conducted through the bootstrap method. The Hosmer–Lemeshow test indicated no significant deviation from the goodness-of-fit (χ2 = 7.349, P = 0.499 > 0.05). The calibration curve indicated excellent concordance between predicted and observed outcomes. The nomogram exhibited strong discriminative capability, evidenced by a C-index of 0.900 (95% CI: 0.828– 0.972) and an AUC of 0.912 (95% CI: 0.864– 0.960) for predicting abdominal infection, with an optimal diagnostic threshold of 0.221 (95% CI: 0.125– 0.265). Decision curve analysis revealed a positive net benefit across a wide range of threshold probabilities (0.03– 1.0), indicating the model’s substantial clinical utility.
Conclusion: Both the preoperative NLR and the preoperative PTAR are independent risk factors for IAIs within 30 days after OLT. The nomogram model based on NLR and PTAR can effectively predict the occurrence of IAIs after OLT.
Keywords: orthotopic liver transplantation, intra-abdominal infection, neutrophil-to-lymphocyte ratio, international normalized ratio-to-albumin ratio, nomogram model
1Department of Critical Liver Diseases, National Clinical Research Center for Digestive Diseases, Beijing Friendship Hospital, Capital Medical University, Beijing, People’s Republic of China; 2Liver Transplantation Center, National Clinical Research Center for Digestive Diseases, Beijing Friendship Hospital, Capital Medical University, Beijing, People’s Republic of China; 3Beijing Key Laboratory of Organ Cultivation and Organ Protection in Transplantation, Beijing Friendship Hospital, Capital Medical University, Beijing, People’s Republic of China; 4State Key Laboratory of Digestive Health, Beijing, People’s Republic of China; 5Laboratory for Clinical Medicine, Capital Medical University, Beijing, People’s Republic of China
Correspondence: Li-Ying Sun, Department of Critical Liver Diseases, Beijing Friendship Hospital, Capital Medical University, Number 101, Luyuan East Road, Tongzhou District, Beijing, 101100, People’s Republic of China, Email sunxlx@outlook.com Hao-Feng Xiong, Department of Critical Liver Diseases, Beijing Friendship Hospital, Capital Medical University, Number 101, Luyuan East Road, Tongzhou District, Beijing, 101100, People’s Republic of China, Email Xionghaofengmd@qq.com
Purpose: To identify risk factors for bacterial intra-abdominal infections (IAIs) after orthotopic liver transplantation (OLT) and establish a nomogram prediction model based on preoperative neutrophil-to-lymphocyte ratio (NLR) and preoperative prothrombin time-international normalized ratio (PT-INR)-to-albumin ratio (PTAR).
Patients and Methods: We retrospectively analyzed 261 patients who received OLT between January 2020 and April 2024 in Beijing Friendship Hospital. Independent risk factors for bacterial IAIs within 30 days postoperatively were identified by logical regression analysis. The area under the receiver operating characteristic (ROC) curve (AUC) was calculated to evaluate the predictive performance of NLR and PTAR as well as the nomogram model based on them. Hepatic function was evaluated using the Child–Turcotte–Pugh (CTP) score and the Model for End-Stage Liver Disease (MELD) score.
Results: Fifty patients (19.2%, 50/261) developed postoperative bacterial IAIs. The majority of the 66 isolated strains were gram-negative (63.6%). Most infections (74.0%, 37/50) occurred within two weeks postoperatively. Multivariate logistic regression analysis identified preoperative NLR, preoperative PTAR, acute physiology and chronic health evaluation II (APACHE II) score, and biliary leakage as independent risk factors. A nomogram-based prediction model was constructed utilizing the identified independent risk factors. Internal validation was conducted through the bootstrap method. The Hosmer–Lemeshow test indicated no significant deviation from the goodness-of-fit (χ2 = 7.349, P = 0.499 > 0.05). The calibration curve indicated excellent concordance between predicted and observed outcomes. The nomogram exhibited strong discriminative capability, evidenced by a C-index of 0.900 (95% CI: 0.828– 0.972) and an AUC of 0.912 (95% CI: 0.864– 0.960) for predicting abdominal infection, with an optimal diagnostic threshold of 0.221 (95% CI: 0.125– 0.265). Decision curve analysis revealed a positive net benefit across a wide range of threshold probabilities (0.03– 1.0), indicating the model’s substantial clinical utility.
Conclusion: Both the preoperative NLR and the preoperative PTAR are independent risk factors for IAIs within 30 days after OLT. The nomogram model based on NLR and PTAR can effectively predict the occurrence of IAIs after OLT.
Keywords: orthotopic liver transplantation, intra-abdominal infection, neutrophil-to-lymphocyte ratio, international normalized ratio-to-albumin ratio, nomogram model