Objective:To study the clinical value of the Naples prognostic score (NPS) in predicting the prognosis of patients with intrahepatic cholangiocarcinoma (ICC) after radical resection and establish a nomogram prediction model.Methods:Clinical data of 77 patients with ICC undergoing radical hepatectomy for the first time in the First Affiliated Hospital of Zhengzhou University from January 2018 to December 2022 were retrospectively collected, including 46 males and 31 females, aged (58.9±11.0) years old. The area under the receiver operating characteristic curve for NPS to predict the death after radical hepatectomy in ICC patients was 0.673, and the optimal cut-off value for NPS based on the Youden's index was 2.5. According to the optimal cut-off value of NPS, patients were divided into two groups: the low NPS group (patients with NPS≤2.5, n=37) and high NPS group (patients with NPS>2.5, n=40). The clinicopathological data including resection extent, blood transfusion, tumor differentiation, lymphovascular invasion, lymph node metastasis and postoperative complications were compared between the groups. Follow-ups were conducted via outpatient or telephone reviews. Kaplan-Meier method was used for survival analysis, and log-rank test was used for survival comparison. Cox proportional hazards regression was used to analyze the risk factors affecting postoperative survival. A prediction nomogram was established and evaluated. Results:Compared to the low NPS group, the proportion of patients with tumor length ≥5 cm, lymphovascular invasion, lymph node metastasis, tumor carbohydrate antigen 19-9 ≥37 U/ml and the level of neutrophil to lymphocyte ratio were increased in the high NPS group, while the proportion of patients with serum albumin ≥40 g/L was decreased (all P<0.05). The cumulative survival rate of patients in the high NPS group was lower than that of the low NPS group ( P=0.001). Multivariate Cox analysis showed that ICC patients with lymphovascular invasion, lymph node metastasis, and NPS>2.5 had a higher risk of short survival after surgery (all P<0.05). The nomogram model based on NPS has a good predictive capacity. Conclusion:High preoperative NPS score indicates poor postoperative prognosis, and NPS score is an independent risk factor affecting the prognosis of ICC patients.

Objective:To explore the risk factors of short-term prognosis of severe Budd-Chiari syndrome (BCS) patients,established and verified the nomogram prediction model for these BCS patients and evaluated its clinical application value.Methods:This study is a retrospective cohort study. The clinical data of 171 patients with severe BCS diagnosed were retrospectively analyzed in the Department of Hepatopancreatobiliary Surgery First Affiliated Hospital of Zhengzhou University from January 2018 to December 2023. There were 105 males and 66 females, aged (52.1±12.8) years (range: 18 to 79 years). The patients were divided into two groups based on whether they died within 28 days: the death group ( n=38) and the survival group ( n=133). The risk factors for short-term death of patients were analyzed,and independent risk factors were screened by univariate and multivariate analysis. Furthermore,these factors were used to establish the nomogram prediction model. The area under the curve(AUC),the Bootstrap Resampling,the Hosmer-Lemeshow test and the Decision Curve Analysis(DCA) were used to verify the model′s differentiation,internal verification,calibration degree and clinical effectiveness,respectively. Results:Univariate and multivariate Logistics regression analysis showed that the history of hepatic encephalopathy,white blood cell,glomerular filtration rate and prothrombin time were independent risk factors ( P<0.05). The above factors were used to successfully establish the prediction model with 0.908 of AUC and 0.895 of the internal verification of AUC,indicating that the predictive model was valuable. The 0.663 P-values in the Hosmer-Lemeshow test indicated the high calibration degree of the model. The clinical effectiveness of the model was proved by the 18% clinical benefit population using the DCA curve with the 17% probability threshold. Conclusions:The independent risk factors are the history of hepatic encephalopathy,white blood cell,glomerular filtration rate and prothrombin time. An adequate basis was acquired by establishing a nomogram prediction model of the short-term prognosis of severe BCS,which was helpful for early clinical screening and identification of high-risk patients with severe BCS who could die in the short term and timely providing timely intervention measures for improving the prognosis.

Objective:To explore the risk factors of short-term prognosis of severe Budd-Chiari syndrome (BCS) patients,established and verified the nomogram prediction model for these BCS patients and evaluated its clinical application value.Methods:This study is a retrospective cohort study. The clinical data of 171 patients with severe BCS diagnosed were retrospectively analyzed in the Department of Hepatopancreatobiliary Surgery First Affiliated Hospital of Zhengzhou University from January 2018 to December 2023. There were 105 males and 66 females, aged (52.1±12.8) years (range: 18 to 79 years). The patients were divided into two groups based on whether they died within 28 days: the death group ( n=38) and the survival group ( n=133). The risk factors for short-term death of patients were analyzed,and independent risk factors were screened by univariate and multivariate analysis. Furthermore,these factors were used to establish the nomogram prediction model. The area under the curve(AUC),the Bootstrap Resampling,the Hosmer-Lemeshow test and the Decision Curve Analysis(DCA) were used to verify the model′s differentiation,internal verification,calibration degree and clinical effectiveness,respectively. Results:Univariate and multivariate Logistics regression analysis showed that the history of hepatic encephalopathy,white blood cell,glomerular filtration rate and prothrombin time were independent risk factors ( P<0.05). The above factors were used to successfully establish the prediction model with 0.908 of AUC and 0.895 of the internal verification of AUC,indicating that the predictive model was valuable. The 0.663 P-values in the Hosmer-Lemeshow test indicated the high calibration degree of the model. The clinical effectiveness of the model was proved by the 18% clinical benefit population using the DCA curve with the 17% probability threshold. Conclusions:The independent risk factors are the history of hepatic encephalopathy,white blood cell,glomerular filtration rate and prothrombin time. An adequate basis was acquired by establishing a nomogram prediction model of the short-term prognosis of severe BCS,which was helpful for early clinical screening and identification of high-risk patients with severe BCS who could die in the short term and timely providing timely intervention measures for improving the prognosis.