ObjectiveTo investigate the risk factors for atherosclerosis （AS） in rheumatoid arthritis （RA） patients and its correlation with traditional Chinese medicine （TCM） syndromes. MethodsA cross-sectional study was conducted， enrolling 16,082 RA patients from 122 medical centers nationwide. Patient demographics， disease assessment data including disease activity （DAS-28）， tender joint count （TJC）， swollen joint count （SJC）， patient's global assessment （PGA）， evaluator's global assessment （EGA）， and visual analogue scale （VAS）， major clinical symptoms including insomnia， loss of appetite， irritability， and fatigue， and laboratory indicators including blood routine， inflammatory markers， liver and kidney function， metabolic indices， and coagulation markers were collected through questionnaire. Based on the four examinations in TCM， patients were classified into eight TCM syndromes， which were wind-damp obstruction， cold-damp obstruction， damp-heat obstruction， phlegm-stasis obstruction， blood stasis obstructing the collaterals， qi-blood deficiency， liver-kidney insufficiency， and qi-yin deficiency. Patients who experienced AS events were included in the event group （564 cases）， while those without AS events were included in the non-event group （15,518 cases）. Intergroup difference tests were used to screen potential risk factors， and binary logistic regression analysis was employed to assess the correlation between TCM syndromes and rheumatoid arthritis with atherosclerosis （RA-AS）. ResultsCompared to the non-event group， patients in the event group had longer disease duration， higher body weight， and older age （P＜0.05）， and showed significantly higher DAS28， TJC， SJC， PGA， EGA， VAS， ESR， low-density lipoprotein cholesterol （LDL-C）， triglycerides （TG）， total cholesterol （TC）， and D-dimer levels， and lower high-density lipoprotein cholesterol （HDL-C）， with more severe symptoms of insomnia， irritability， and fatigue （P＜0.05）. Damp-heat obstruction syndrome was the most prevalent in both groups， with a higher proportion in the event group （393/564， 69.68%） than in the non-event group （4578/15,518， 29.50%） showing significant difference （P＜0.05）. Logistic regression analysis showed that patients with damp-heat obstruction syndrome had a 5.326-fold higher risk of developing RA-AS compared to those without this syndrome （OR=5.326， 95%CI 4.517 to 7.089， P＜0.001）. ConclusionThe occurrence of RA-AS is associated with TCM syndromes， disease activity， inflammatory markers and lipid metabolic indices， and damp-heat obstruction syndrome is an independent risk factor for RA-AS.

ObjectiveTo investigate the predictive factors for HBsAg clearance in chronic hepatitis B （CHB） patients with a low level of hepatitis B surface antigen （HBsAg） treated with pegylated interferon α-2b （PEG-IFN-α-2b）， to establish a combined predictive model and a nomogram based on multiple factors， and to provide a reference for formulating individualized treatment regimens and predicting treatment outcome in clinical practice. MethodsA retrospective analysis was performed for 167 CHB patients with HBsAg <1 500 IU/mL who attended The Third People’s Hospital of Kunming from January 2022 to January 2024 and were treated with PEG-IFN-α-2b. According to whether clinical cure was achieved， the patients were divided into HBsAg clearance group and HBsAg non-clearance group. Related data were collected， including general information and serological/biochemical/virological indicators at different time points during treatment. The independent samples t-test was used for comparison of normally distributed continuous data， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data； the chi-square test was used for comparison of categorical data. The multivariate logistic regression analysis was used to identify independent influencing factors. The receiver operating characteristic （ROC） curve was used to assess the value of indicators used alone or in combination in predicting clinical cure， and calibration curves were plotted to assess the risk prediction model. ResultsThe univariate analysis showed that there were significant differences between the two groups in age （t=-6.839， P<0.05）， history of nucleos（t）ide analogue treatment for over 1 year （χ²=59.339， P<0.05）， genotype （χ²=4.610， P<0.05）， nonalcoholic fatty liver disease （χ²=5.319， P<0.05）， hepatitis B virus DNA status before treatment （χ²=60.861， P <0.05）， compensated liver cirrhosis （χ²=10.960， P<0.05）， HBeAg status before treatment （χ²=19.060， P<0.05）， a history of interferon treatment （χ²=8.162， P<0.05）， presence of interferon antibodies after treatment （χ²=12.858， P<0.05）， HBsAg level before treatment （Z=-7.412， P<0.05）， alanine aminotransaminase （ALT） level at baseline （Z=-6.117， P<0.05）， ALT level at 12 weeks of treatment （Z=-7.171， P<0.05）， platelet count （PLT） at 24 weeks of treatment （Z=-3.622， P<0.05）， and thyroid stimulating hormone （TSH） level at 24 weeks of treatment （Z=-2.830， P<0.05）. The multivariate logistic regression analysis showed that age （odds ratio ［OR］=1.230， P=0.007）， history of nucleos（t）ide analogue treatment for over 1 year （OR=0.008， P=0.011）， HBeAg status before treatment （OR=0.003， P=0.012）， HBsAg level before treatment （OR=1.005， P=0.014）， ALT level at baseline （OR=0.949， P=0.014）， ALT level at 12 weeks of treatment （OR=0.969， P=0.016）， PLT at 24 weeks of treatment （OR=0.969， P=0.022）， and TSH level at 24 weeks of treatment （OR=3.608， P=0.045） were independent influencing factors for HBsAg clearance at 48 weeks of treatment in CHB patients with HBsAg <1 500 IU/mL. The Hosmer-Lemeshow goodness-of-fit test yielded χ²=1.398， P=0.994， indicating that the model had good fitting. The Bootstrap method was used to perform internal validation of the nomogram model， and there was a good degree of fitting between the calibration curve and the ideal curve， with a mean absolute error of 0.029. The ROC curve analysis showed that the combination of predictive factors had an area under the ROC curve of 0.982 （95% confidence interval： 0.961 — 0.999）， with a sensitivity of 94.10% and a specificity of 93.10%， suggesting that the nomogram model had a good discriminatory ability. For the CHB patients with HBsAg <1 500 IU/mL and different features， further analysis of HBsAg clearance rate at 48 weeks of treatment showed an HBsAg clearance rate of 69.60% for those with HBsAg ≤67.65 IU/mL before treatment， 58.30% for those with a baseline ALT level of ≥62.50 U/L， 68.30% for those with an ALT level of ≥92.50 U/L at 12 weeks of treatment， 42.40% for those with PLT ≥104×10⁹/L at 24 weeks of treatment， and 48.30% for those with a TSH level of ≤1.38 μIU/mL at 24 weeks of treatment， with significant differences between the two groups （all P<0.001）. ConclusionAge， history of nucleos（t）ide analogue treatment for over 1 year， HBeAg status before treatment， HBsAg level before treatment， baseline ALT level， ALT level at 12 weeks of treatment， PLT level at 24 weeks， and TSH level at 24 weeks of treatment are independent predictive factors. The combined prediction nomogram model constructed in this study has a relatively high value in predicting clinical cure at 48 weeks of PEG-IFN-α-2b treatment in CHB patients with HBsAg<1 500 IU/mL， thereby providing a reference for selecting suitable treatment population and predicting clinical cure.

AIM:To investigate the effects of nebulized sodium tanshinone ⅡA sulfonate(STS)in a mouse model of pulmonary hypertension associated with chronic obstructive pulmonary disease(COPD-PH).METHODS:A to-tal of 32 healthy SPF-grade male C57BL/6 mice were randomly divided into 4 groups:control(CTL,n=8)group,COPD-PH(CS+LPS,n=8)group,STS-treated COPD-PH(CS+LPS+STS,n=8)group,and STS(n=8)group.The COPD-PH model was established through whole-body exposure to cigarette smoke(CS)combined with lipopolysaccharide(LPS)in-halation.Mice were subjected to cigarette smoke exposure in a chamber(9 cigarettes/h,2 h/session,2 sessions/d,6 d/week)for 60 d,except on days of LPS inhalation.On days 1 and 14,COPD-PH model mice received LPS(7.5 μg/mouse in 50 μL saline)via intranasal inhalation,while the CTL and STS groups received an equivalent volume of saline.STS was administered via nebulized inhalation(5 mg/kg,30 min per session,twice daily)immediately before CS exposure.At the end of the modeling period,lung function and right heart pressure were assessed.Bronchoalveolar lavage fluid(BALF)was collected for inflammatory cell counting.Levels of interleukin-6(IL-6)in BALF supernatants and plasma were measured using ELISA.Pathological changes in the airway and lung tissues were evaluated.RESULTS:(1)Com-pared to CTL mice,those exposed to CS and LPS exhibited lesions characteristic of COPD-PH,including emphysema,lung inflammation,decreased lung function,and increased right ventricular systolic pressure(RVSP)and right ventricu-lar hypertrophy index(RVHI)(P<0.05);(2)COPD-PH mice showed significantly elevated IL-6 levels in both BALF and plasma(P<0.05);(3)STS treatment alleviated emphysema and lung inflammation,improved lung function,prevent-ed increases in RVSP and the RV/(LV+S)ratio,and reduced IL-6 levels in both BALF and plasma(P<0.05).CON-CLUSION:The results indicate that nebulized inhalation of STS significantly slows the progression of COPD-PH,likely due to its ability to inhibit lung inflammation and reduce IL-6 expression in the lungs.

Objective To investigate the predictive factors for the occurrence of HBsAg clearance in patients with HBeAg-negative chronic hepatitis B(CHB)receiving peginterferon alfa-2b(PEG-IFN-α-2b)treatment,analyze the effects of various indicators on the HBsAg clearance rate under different characteristics,and construct and evaluate a combined predictive model.Methods We included 125 patients with HBeAg-negative CHB at Kunming Third People's Hospital from May 2021 to May 2023.After treatment with PEG-IFN-α-2b combined with nucleoside analogues for a course of 48 weeks,they were divided into HBsAg clearance group and HBsAg non-clearance group.Their general information and serological,biochemical,and virological indicators at different time points during treatment were recorded.Continuous data in normal distribution were compared using the t test.Continuous data in non-normal distribution were compared using the Mann-Whitney U test,and comparisons across different time points were performed using the multiple paired-sample Friedman test.Categorical data were compared using the χ2 test.A Logistic regression analysis was used to select variables to establish a combined multi-parameter predictive model.Receiver operating characteristic(ROC)curves were generated to evaluate the diagnostic value of individual indicators and the combined predictive model for HBsAg clearance.Results Before treatment,there were significant differences in baseline HBsAg level(Z=-3.997,P<0.05)and treatment history(χ2=8.221,P<0.05)between the two groups.During treatment,gradually decreasing trends were observed in white blood cell count(χ2=104.944),neutrophil count(χ2=132.036),platelet count(χ2=162.881),and thyroid-stimulating hormone level(TSH,χ2=83.304,all P<0.05),while alanine aminotransferase(ALT,χ2=157.618)and alpha fetoprotein(χ2=159.472)showed gradually increasing trends(both P<0.05).At 48 weeks of treatment,treatment history(odds ratio[OR]=0.232,95%confidence interval[CI]:0.071-0.753),baseline HBsAg level(OR=13.423,95%CI:3.276-54.997),the extent of decrease in HBsAg from baseline after 12 weeks of treatment(OR=0.143,95%CI:0.040-0.515),the maximum ALT level during treatment(OR=0.986,95%CI:0.980-0.993),and the minimum TSH level during treatment(OR=3.281,95%CI:1.413-7.619)were independent factors affecting HBsAg clearance(all P<0.05).A combined predictive model for HBsAg clearance was built:Y=-1.603-1.462×treatment history+2.597×baseline HBsAg value-1.944×the extent of HBsAg reduction from baseline after 12 weeks of treatment-0.014×the maximum ALT value during treatment+1.188×the minimum TSH value during treatment.The diagnostic value of the individual indicators for HBsAg clearance from high to low was as following:the maximum ALT value during treatment(AUC=0.824),baseline HBsAg value(AUC=0.727),the minimum TSH value during treatment(AUC=0.707),the extent of HBsAg reduction from baseline after 12 weeks of treatment(AUC=0.641),and treatment history(AUC=0.636).The combined model showed better predictive performance than the individual indicators,with the AUC being 0.921(all P<0.05).Conclusion The combined model,constructed with baseline HBsAg value,the extent of HBsAg reduction from baseline after 12 weeks of treatment,the maximum ALT value during treatment,and the minimum TSH value during treatment,has high predictive value for the occurrence of HBsAg clearance in patients with HBeAg-negative CHB after 48 weeks of treatment with PEG-IFN-α-2b,which can provide a reference for identifying suitable patients for treatment and predicting clinical outcome.

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 predictive factors for the occurrence of HBsAg clearance in patients with HBeAg-negative chronic hepatitis B(CHB)receiving peginterferon alfa-2b(PEG-IFN-α-2b)treatment,analyze the effects of various indicators on the HBsAg clearance rate under different characteristics,and construct and evaluate a combined predictive model.Methods We included 125 patients with HBeAg-negative CHB at Kunming Third People's Hospital from May 2021 to May 2023.After treatment with PEG-IFN-α-2b combined with nucleoside analogues for a course of 48 weeks,they were divided into HBsAg clearance group and HBsAg non-clearance group.Their general information and serological,biochemical,and virological indicators at different time points during treatment were recorded.Continuous data in normal distribution were compared using the t test.Continuous data in non-normal distribution were compared using the Mann-Whitney U test,and comparisons across different time points were performed using the multiple paired-sample Friedman test.Categorical data were compared using the χ2 test.A Logistic regression analysis was used to select variables to establish a combined multi-parameter predictive model.Receiver operating characteristic(ROC)curves were generated to evaluate the diagnostic value of individual indicators and the combined predictive model for HBsAg clearance.Results Before treatment,there were significant differences in baseline HBsAg level(Z=-3.997,P<0.05)and treatment history(χ2=8.221,P<0.05)between the two groups.During treatment,gradually decreasing trends were observed in white blood cell count(χ2=104.944),neutrophil count(χ2=132.036),platelet count(χ2=162.881),and thyroid-stimulating hormone level(TSH,χ2=83.304,all P<0.05),while alanine aminotransferase(ALT,χ2=157.618)and alpha fetoprotein(χ2=159.472)showed gradually increasing trends(both P<0.05).At 48 weeks of treatment,treatment history(odds ratio[OR]=0.232,95%confidence interval[CI]:0.071-0.753),baseline HBsAg level(OR=13.423,95%CI:3.276-54.997),the extent of decrease in HBsAg from baseline after 12 weeks of treatment(OR=0.143,95%CI:0.040-0.515),the maximum ALT level during treatment(OR=0.986,95%CI:0.980-0.993),and the minimum TSH level during treatment(OR=3.281,95%CI:1.413-7.619)were independent factors affecting HBsAg clearance(all P<0.05).A combined predictive model for HBsAg clearance was built:Y=-1.603-1.462×treatment history+2.597×baseline HBsAg value-1.944×the extent of HBsAg reduction from baseline after 12 weeks of treatment-0.014×the maximum ALT value during treatment+1.188×the minimum TSH value during treatment.The diagnostic value of the individual indicators for HBsAg clearance from high to low was as following:the maximum ALT value during treatment(AUC=0.824),baseline HBsAg value(AUC=0.727),the minimum TSH value during treatment(AUC=0.707),the extent of HBsAg reduction from baseline after 12 weeks of treatment(AUC=0.641),and treatment history(AUC=0.636).The combined model showed better predictive performance than the individual indicators,with the AUC being 0.921(all P<0.05).Conclusion The combined model,constructed with baseline HBsAg value,the extent of HBsAg reduction from baseline after 12 weeks of treatment,the maximum ALT value during treatment,and the minimum TSH value during treatment,has high predictive value for the occurrence of HBsAg clearance in patients with HBeAg-negative CHB after 48 weeks of treatment with PEG-IFN-α-2b,which can provide a reference for identifying suitable patients for treatment and predicting clinical outcome.

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.

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.

ObjectiveTo investigate the value of noninvasive imaging detection （FibroScan）， two serological models of gamma-glutamyl transpeptidase-to-platelet ratio （GPR） score and S index， and two inflammatory factors of interleukin-6 （IL-6） and tumor necrosis factor-α （TNF-α） in predicting liver fibrosis in patients with HBeAg-positive chronic hepatitis B （CHB）， as well as the consistency of liver biopsy in pathological staging， and to provide early warning for early intervention of CHB. MethodsA retrospective analysis was performed for 131 HBeAg-positive CHB patients who underwent liver biopsy in The Third People’s Hospital of Kunming from January 2019 to December 2023. The results of liver biopsy were collected from all patients， and related examinations were performed before liver biopsy， including total bilirubin， alanine aminotransferase， platelet count， gamma-glutamyl transpeptidase， albumin， IL-6， TNF-α， liver stiffness measurement （LSM）， and abdominal ultrasound. An analysis of variance was used for comparison of normally distributed continuous data between groups， and the Kruskal-Wallis H test was used for comparison of non-normally distributed continuous data between groups； the chi-square test was used for comparison of categorical data between groups. A Kappa analysis was used to investigate the consistency between LSM noninvasive histological staging and pathological staging based on liver biopsy， and the Spearman analysis was used to investigate the correlation between each variable and FibroScan in the diagnosis of liver fibrosis stage. The Logistic regression analysis was used to construct joint predictive factors. The receiver operating characteristic （ROC） curve was used to evaluate the value of each indicator alone and the joint predictive model in the diagnosis of liver fibrosis， and the Delong test was used for comparison of the area under the ROC curve （AUC）. ResultsIn the consistency check， inflammation degree based on liver biopsy had a Kappa value of 0.807 （P<0.001）， and liver fibrosis degree based on liver biopsy had a Kappa value of 0.827 （P<0.001）， suggesting that FibroScan noninvasive histological staging and liver biopsy showed good consistency in assessing inflammation degree and liver fibrosis stage. Age was positively correlated with LSM， GPR score， S index， IL-6， and TNF-α （all P<0.05）， and GPR score， S index， IL-6， and TNF-α were positively correlated with LSM （all P<0.05）. GPR score， S index， IL-6， and TNF-α were all independent risk factors for diagnosing significant liver fibrosis （≥S2） and progressive liver fibrosis （≥S3） （all P<0.05）. As for each indicator alone， GPR score had the highest value in the diagnosis of significant liver fibrosis （≥S2）， followed by S index， IL-6， and TNF-α， while S index had the highest value in the diagnosis of progressive liver fibrosis （≥S3）， followed by GPR score， TNF-α， and IL-6. The joint model had a higher predictive value than each indicator alone （all P<0.05）. ConclusionThere is a good consistency between FibroScan noninvasive histological staging and pathological staging based on liver biopsy. GPR score， S index， IL-6， and TNF-α are independent risk factors for evaluating different degree of liver fibrosis in CHB， and the combined prediction model established by them can better diagnose liver fibrosis.

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.