ObjectiveTo investigate the influencing factors for hepatic hydrothorax （HH） before intervention for primary hepatic carcinoma （PHC）， and to construct and assess the nomogram risk prediction model. MethodsA retrospective analysis was performed for the clinical data of 353 hospitalized patients who attended the Third People’s Hospital of Kunming for the first time from October 2012 to October 2021 and there diagnosed with PHC， and according to the presence or absence of HH， they were divided into HH group with 153 patients and non-HH group with 200 patients. General data and the data of initial clinical testing after admission were collected from all PHC patients. The independent-samples t test was used for comparison of normally distributed continuous data between two groups， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups； the chi-square test or the Fisher’s exact test was used for comparison of categorical data between groups. After the multicollinearity test was performed for the variables with statistical significance determined by the univariate analysis， the multivariate Logistic regression analysis was used to identify independent influencing factors. The “rms” software package was used to construct a nomogram risk prediction model， and the Hosmer-Lemeshow test and the receiver operating characteristic （ROC） curve were used to assess the risk prediction model； the “Calibration Curves” software package was used to plot the calibration curve， and the “rmda” software package was used to plot the clinical decision curve and the clinical impact curve. ResultsAmong the 353 patients with PHC， there were 153 patients with HH， with a prevalence rate of 43.34%. Child-Pugh class B （odds ratio ［OR］=2.652， 95% confidence interval ［CI］： 1.050 — 6.698， P=0.039）， Child-Pugh class C （OR=7.963， 95%CI： 1.046‍ ‍—‍ ‍60.632， P=0.045）， total protein （OR=0.947， 95%CI： 0.914‍ ‍—‍ ‍0.981， P=0.003）， high-sensitivity C-reactive protein （OR=1.007， 95%CI： 1.001‍ ‍—‍ ‍1.014， P=0.025）， and interleukin-2 （OR=0.801， 95%CI： 0.653‍ ‍—‍ ‍0.981， P=0.032） were independent influencing factors for HH before PHC intervention， and a nomogram risk prediction model was established based on these factors. The Hosmer-Lemeshow test showed that the model had a good degree of fitting （χ²=5.006， P=0.757）， with an area under the ROC curve of 0.752 （95%CI： 0.701‍ ‍—‍ ‍0.803）， a sensitivity of 78.40%， and a specificity of 63.50%. The calibration curve showed that the model had good consistency in predicting HH before PHC intervention， and the clinical decision curve and the clinical impact curve showed that the model had good clinical practicability within a certain threshold range. ConclusionChild-Pugh class， total protein， interleukin-2， and high-sensitivity C-reactive protein are independent influencing factors for developing HH before PHC intervention， and the nomogram model established based on these factors can effectively predict the risk of developing HH.

Objective To analyze the influencing factors of chronic liver failure in patients with primary hepatic carcinoma(PHC)before intervention,and to establish and evaluate a nomogram risk prediction model.Methods A retrospective analysis was conducted by collecting general data and clinical test data within 24 hours of admission for PHC patients.Univariate analysis and Lasso regression were used for variable selection,followed by multivariate logistic regression analysis to identify independent influencing factors for CLF before PHC intervention,leading to the establishment of a nomogram risk prediction model.The model was evaluated using the Hosmer-Lemeshow test,receiver operating characteristic(ROC)curve,calibration curve,clinical decision curve,and clinical impact curve.Result A total of 353 cases of PHC patients were collected,including 153 cases in the liver failure group and 200 cases in the non-liver failure group,with a prevalence rate of 43.3％.Variables selected by Lasso regression included gastrointestinal bleeding,prothrombin time(PT),albumin(ALB),total bilirubin(TBIL),and gamma glutamyl transferase(GGT).Multivariate logistic regression analysis showed that gastrointestinal bleeding(OR=13.549,95％CI:2.899～63.322,P=0.001),PT(OR=1.599,95％CI:1.282～1.995,P＜0.001),TBIL(OR=1.016,95％CI:1.006～1.025,P=0.002),and GGT(OR=1.002,95％CI:1.000～1.003,P=0.028)were independent risk factors for chronic liver failure prior to PHC intervention,leading to the establishment of a nomogram risk prediction model.The Hosmer Lemeshow test showed that the model had a good fit(x2=6.152,P＞0.05);the area under ROC was 0.902(0.869-0.934),with a sensitivity of 80.4％and a specificity of 87.5％.The calibration curve indicated that the model predicts chronic liver failure prior to PHC intervention with good consistency.Clinical decision curve analysis and clinical impact curve analysis showed that the model has good clinical utility within a certain threshold range.Conclusion Gastrointestinal bleeding,PT ≥16.05s,TBIL≥37.80 mmol/L,and GGT≥ 99.00 U/L are independent risk factors for the occurrence of chronic liver failure before PHC intervention.The established nomogram risk prediction model has certain clinical application value in predicting the risk of chronic liver failure before PHC intervention.

Objective To investigate the independent risk factors for portal vein thrombosis(PVT)in patients with viral hepatitis-related decompensated cirrhosis,and to establish and validate a nomogram risk prediction model.Methods A retrospective analysis was performed for the clinical data of 1 116 patients with decompensated HBV/HCV cirrhosis who attended The Third People's Hospital of Kunming for the first time from January 2022 to December 2023,and according to the presence or absence of PVT,they were divided into PVT group and control group.The independent samples t-test or the Mann-Whitney U test was used for comparison of continuous data between groups,and the chi-square test was used for comparison of categorical data between groups.Univariate analysis and least absolute shrinkage and selection operator(LASSO)regression analysis were used to identify variables,and a binary logistic regression analysis was used to obtain independent influencing factors and establish a predictive model,which was visualized using a nomogram.The model was validated based on the receiver operating characteristic(ROC)curve,the area under the ROC curve(AUC),the Hosmer-Lemeshow test,Bootstrap sampling(1 000 iterations),the calibration curve,the decision curve analysis(DCA),and the clinical impact curve(CIC).Results There were 178 patients in the PVT group and 938 patients in the control group,and the prevalence rate of PVT was 15.9%(178/1 116).Male patients accounted for 68.5%(764/1 116),and the patients with drinking,Child-Pugh class B liver function,and ascites accounted for 51.0%(569/1 116),78.8%(879/1 116),and 67.1%(749/1 116),respectively.Compared with the control group,the PVT group had significantly higher age(Z=-2.362,P<0.05),prothrombin time(Z=-2.403,P<0.05),international normalized ratio(Z=-2.470,P<0.05),free thyroxine(Z=-5.910,P<0.05),D-dimer(Z=-5.764,P<0.05),interleukin-6(Z=-6.581,P<0.05),interleukin-10(IL-10)(Z=-3.915,P<0.05),interleukin-8(Z=-3.705,P<0.05),diameter of the portal vein(Z=-9.690,P<0.05),and spleen thickness(Z=-7.183,P<0.05),as well as significantly lower levels of white blood cell count(Z=-2.115,P<0.05),platelet count(Z=-3.026,P<0.05),fibrinogen(Z=-2.169,P<0.05),alanine aminotransferase(Z=-3.151,P<0.05),prealbumin(Z=-3.509,P<0.05),cholinesterase(Z=-3.415,P<0.05),alpha-fetoprotein(Z=-3.513,P<0.05),triglycerides(Z=-2.679,P<0.05),CD3 cell count(Z=-6.059,P<0.05),CD4 cell count(Z=-7.257,P<0.05),CD8 cell count(Z=-2.340,P<0.05),CD4+/CD8+cell ratio(Z=-4.479,P<0.05),triiodothyronine(Z=-3.338,P<0.05),free triiodothyronine(FT3)(Z=-9.560,P<0.05),and portal blood flow velocity(Z=-4.568,P<0.05).The multivariate logistic regression analysis was performed for the variables with statistical significance identified by the LASSO regression analysis,and the results showed that age(odds ratio[OR]=1.046,95%confidence interval[CI]:1.026-1.066),CD4+/CD8+cell ratio(OR=0.568,95%CI:0.410-0.787),FT3(OR=0.956,95%CI:0.944-0.968),IL-10(OR=1.021,95%CI:1.001-1.042),diameter of the portal vein(OR=1.446,95%CI:1.329-1.574),and spleen thickness(OR=1.035,95%CI:1.014-1.055)were independent influencing factors.A model was established as Logit(P)=-8.784+0.045×age-0.566×CD4+/CD8+-0.046×FT3+0.021×IL-10+0.369×diameter of the portal vein+0.034×spleen thickness,and a nomogram model was established and validated based on this model,with an AUC of 0.859(95%CI:0.833-0.887).The Hosmer-Lemeshow test showed that the model had a high goodness of fit(χ2=11.349,P=0.183).Bootstrap internal validation showed a mean absolute error of 0.006 and a C-index of 0.855.The decision curve analysis showed that the model had a high net clinical benefit within a wide range of thresholds.Conclusion Age,CD4+/CD8+ratio,FT3,IL-10,diameter of the portal vein,and spleen thickness may be independent influencing factors for PVT in patients with decompensated HBV/HCV cirrhosis.The predictive model established based on these six variables can help to predict the risk of PVT in patients with hepatitis-related decompensated cirrhosis in the early stage in clinical practice.

Objective To investigate the independent risk factors for portal vein thrombosis(PVT)in patients with viral hepatitis-related decompensated cirrhosis,and to establish and validate a nomogram risk prediction model.Methods A retrospective analysis was performed for the clinical data of 1 116 patients with decompensated HBV/HCV cirrhosis who attended The Third People's Hospital of Kunming for the first time from January 2022 to December 2023,and according to the presence or absence of PVT,they were divided into PVT group and control group.The independent samples t-test or the Mann-Whitney U test was used for comparison of continuous data between groups,and the chi-square test was used for comparison of categorical data between groups.Univariate analysis and least absolute shrinkage and selection operator(LASSO)regression analysis were used to identify variables,and a binary logistic regression analysis was used to obtain independent influencing factors and establish a predictive model,which was visualized using a nomogram.The model was validated based on the receiver operating characteristic(ROC)curve,the area under the ROC curve(AUC),the Hosmer-Lemeshow test,Bootstrap sampling(1 000 iterations),the calibration curve,the decision curve analysis(DCA),and the clinical impact curve(CIC).Results There were 178 patients in the PVT group and 938 patients in the control group,and the prevalence rate of PVT was 15.9%(178/1 116).Male patients accounted for 68.5%(764/1 116),and the patients with drinking,Child-Pugh class B liver function,and ascites accounted for 51.0%(569/1 116),78.8%(879/1 116),and 67.1%(749/1 116),respectively.Compared with the control group,the PVT group had significantly higher age(Z=-2.362,P<0.05),prothrombin time(Z=-2.403,P<0.05),international normalized ratio(Z=-2.470,P<0.05),free thyroxine(Z=-5.910,P<0.05),D-dimer(Z=-5.764,P<0.05),interleukin-6(Z=-6.581,P<0.05),interleukin-10(IL-10)(Z=-3.915,P<0.05),interleukin-8(Z=-3.705,P<0.05),diameter of the portal vein(Z=-9.690,P<0.05),and spleen thickness(Z=-7.183,P<0.05),as well as significantly lower levels of white blood cell count(Z=-2.115,P<0.05),platelet count(Z=-3.026,P<0.05),fibrinogen(Z=-2.169,P<0.05),alanine aminotransferase(Z=-3.151,P<0.05),prealbumin(Z=-3.509,P<0.05),cholinesterase(Z=-3.415,P<0.05),alpha-fetoprotein(Z=-3.513,P<0.05),triglycerides(Z=-2.679,P<0.05),CD3 cell count(Z=-6.059,P<0.05),CD4 cell count(Z=-7.257,P<0.05),CD8 cell count(Z=-2.340,P<0.05),CD4+/CD8+cell ratio(Z=-4.479,P<0.05),triiodothyronine(Z=-3.338,P<0.05),free triiodothyronine(FT3)(Z=-9.560,P<0.05),and portal blood flow velocity(Z=-4.568,P<0.05).The multivariate logistic regression analysis was performed for the variables with statistical significance identified by the LASSO regression analysis,and the results showed that age(odds ratio[OR]=1.046,95%confidence interval[CI]:1.026-1.066),CD4+/CD8+cell ratio(OR=0.568,95%CI:0.410-0.787),FT3(OR=0.956,95%CI:0.944-0.968),IL-10(OR=1.021,95%CI:1.001-1.042),diameter of the portal vein(OR=1.446,95%CI:1.329-1.574),and spleen thickness(OR=1.035,95%CI:1.014-1.055)were independent influencing factors.A model was established as Logit(P)=-8.784+0.045×age-0.566×CD4+/CD8+-0.046×FT3+0.021×IL-10+0.369×diameter of the portal vein+0.034×spleen thickness,and a nomogram model was established and validated based on this model,with an AUC of 0.859(95%CI:0.833-0.887).The Hosmer-Lemeshow test showed that the model had a high goodness of fit(χ2=11.349,P=0.183).Bootstrap internal validation showed a mean absolute error of 0.006 and a C-index of 0.855.The decision curve analysis showed that the model had a high net clinical benefit within a wide range of thresholds.Conclusion Age,CD4+/CD8+ratio,FT3,IL-10,diameter of the portal vein,and spleen thickness may be independent influencing factors for PVT in patients with decompensated HBV/HCV cirrhosis.The predictive model established based on these six variables can help to predict the risk of PVT in patients with hepatitis-related decompensated cirrhosis in the early stage in clinical practice.