ObjectiveTo construct and validate a predictive model for hepatic encephalopathy （HE） in patients with end-stage liver disease （ESLD） by combining key indicators such as cytokines and Model for End-Stage Liver Disease （MELD） score， and to provide evidence-based support for the early identification of high-risk populations and the optimization of intervention strategies in clinical practice. MethodsA retrospective analysis was performed for 2 167 patients with ESLD who were admitted to The Third People’s Hospital of Kunming from January 2022 to December 2024， the patients were divided into a training set with 1 517 patients and a validation set with 650 patients at a ratio of 7∶3 using the stratified random sampling method. A univariate analysis and a least absolute shrinkage and selection operator （LASSO） regression analysis were performed for the training set to identify potential influencing variables， and then a binary Logistic regression model was constructed to investigate the independent influencing factors for HE in ESLD patients. A nomogram prediction model was established based on this regression model， and the Hosmer-Lemeshow goodness-of-fit test was performed. The receiver operating characteristic （ROC） curve， calibration curves， decision curve analysis， and clinical impact curve were used to comprehensively evaluate the degree of fit， accuracy， consistency， and clinical practicability of the predictive model derived from the training set. The Mann-Whitney U test was used for comparison of non-normally distributed quantitative data between two groups. The chi-square test or Fisher exact test was used for comparison of categorical data between two groups. ResultsThe univariate analysis showed that there were significant differences between the study group and the control group in age， sex， blood ammonia， lymphocytes， hemoglobin， platelet count， prothrombin time， fibrinogen， international normalized ratio， total bilirubin， aspartate aminotransferase， total protein， albumin， prealbumin， alkaline phosphatase， cholinesterase， total bile acid， triglyceride， total cholesterol， high-density lipoprotein， low-density lipoprotein， blood glucose， CD3⁺ T cells， CD4⁺ T cells， CD8⁺ T cells， high-sensitivity C-reactive protein， carcinoembryonic antigen， triiodothyronine， thyroxine， free triiodothyronine， free thyroxine， interleukin-1β， interleukin-5， interleukin-6， interleukin-8， interleukin-12p70， interleukin-17， interferon-γ， and MELD score （all P<0.05）. The LASSO regression analysis identified nine variables of age， blood ammonia， albumin， prealbumin， cholinesterase， total cholesterol， thyroxine， interleukin-17， and MELD score， and the binary Logistic regression analysis showed that blood ammonia， interleukin-17， and MELD score were independent risk factors for HE in ESLD patients， while age and thyroxine were independent protective factors （all P<0.05）. A nomogram model was constructed based on these five variables. The Hosmer-Lemeshow goodness-of-fit test in the training set showed a good degree of fit （P=0.207）， with a McFadden’s pseudo-R² of 0.184， suggesting that the model had acceptable explanatory power； the Hosmer-Lemeshow goodness-of-fit test in the internal validation set further confirmed the calibration stability of the model （P=0.067）， suggesting that the model had a good degree of fit in independent data. The model had an area under the ROC curve of 0.784 in the validation set， with a sensitivity of 0.710 and a specificity of 0.752. The mean absolute error of the calibration curve was 0.067， and decision curve analysis and clinical impact curve showed that the nomogram model had positive net benefit and good clinical practicability. ConclusionThe nomogram model constructed based on age， blood ammonia， thyroxine， interleukin-17， and MELD score for predicting HE in patients with ESLD has a good degree of fit， high accuracy and consistency， and excellent clinical practicability.

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.

ObjectiveTo investigate the independent risk factors for concurrent myocardial injury before intervention in patients with primary hepatic carcinoma （PHC）， to construct and validate a nomogram prediction model for the early identification of such patients， and to provide a basis for early clinical prevention and management. MethodsA retrospective analysis was performed for the clinical data of 1 822 patients with PHC in two medical institutions from January 2019 to June 2025， among whom the 1 518 patients from The Third People’s Hospital of Kunming were used as the training set to construct the nomogram prediction model， and the 304 patients from The Second People’s Hospital of Baoshan were used as the validation set. According to the result of high-sensitivity cardiac troponin T measurement before intervention， the patients with PHC were divided into myocardial injury group and non-myocardial injury group. The univariate analysis， the LASSO regression analysis， and the multivariate Logistic regression analysis were used to identify the risk factors of concurrent myocardial injury in PHC patients before intervention， and then a nomogram prediction model was constructed based on these findings. The independent data of the 304 patients in the validation set were used for external validation， and the area under the receiver operating characteristic curve （AUC）， the Hosmer-Lemeshow test， the calibration curve， decision curve analysis， and clinical impact curve were used to assess model performance. ResultsIn the training set， there were 346 patients in the myocardial injury group and 1 172 patients in the non-myocardial injury group， and the prevalence rate of concurrent myocardial injury was 22.79%. The mean age was 56.44±9.45 years， and the male patients accounted for 81.49%. The patients with drinking， smoking， chronic hepatitis B， chronic hepatitis C， hypertension， diabetes， Child-Pugh class A liver disease， BCLC stage B liver disease， or abnormal electrocardiographic findings accounted for 49.34%， 57.44%， 61.73%， 32.48%， 22.66%， 17.19%， 50.53%， 33.86%， and 62.12%， respectively. The univariate analysis， the LASSO regression analysis， and the multivariate Logistic regression analysis showed that age （odds ratio ［OR］=1.051， 95% confidence interval ［CI］： 1.036 — 1.067， P<0.001）， history of diabetes （OR=1.862， 95%CI： 1.346 — 2.574， P<0.001）， electrocardiographic findings （OR=1.446， 95%CI： 1.077 — 1.940， P=0.014）， hemoglobin （HGB） （OR=0.993， 95%CI： 0.988 — 0.998， P=0.003）， albumin （Alb） （OR=0.951， 95%CI： 0.930 — 0.972， P<0.001）， and creatinine （Cr） （OR=1.021， 95%CI： 1.016 — 1.026， P<0.001） were independent influencing factors for myocardial injury in PHC patients. A regression equation was established as Logit（Y）=-3.406+0.050×age+0.621×history of diabetes+0.369×electrocardiogram－0.007×HGB－0.051×Alb+0.021×Cr， and a nomogram prediction model was constructed based on these factors. The Bootstrap internal validation of the model yielded an AUC of 0.743 （95%CI： 0.707 — 0.778）， and the model had an AUC of 0.766 （95%CI： 0.738 — 0.794） in the training set and 0.730 （95%CI： 0.688 — 0.793） in the validation set. The Hosmer-Lemeshow goodness-of-fit test yielded a P value of 0.716 for the training set and 0.408 for the validation set， suggesting that the model had a good degree of fitting. Calibration curves， decision curve analysis， and clinical impact curves in both the training set and the validation set showed that the model had a good clinical application value. ConclusionAge， history of diabetes， electrocardiographic findings， HGB， Alb， and Cr are independent influencing factors for myocardial injury in patients with PHC， and the nomogram prediction model constructed based on these factors has good discriminatory ability， accuracy， and clinical practicability.

ObjectiveTo investigate the value of albumin-bilirubin （ALBI）， easy albumin-bilirubin （EZ-ALBI）， and platelet-albumin-bilirubin （PALBI） scores in predicting 2-year survival in patients with HCV-associated hepatocellular carcinoma （HCV-HCC）. MethodsA retrospective analysis was performed for the clinical data of 174 patients with HCV-HCC who were admitted to The Third People’s Hospital of Kunming from January 2020 to January 2022， and the patients were followed up till 2 years after admission. According to the follow-up results， the patients were divided into survival group with 95 patients and death group with 79 patients. The independent-samples t test or the Mann-Whitney U test was used for comparison of continuous data between two groups， and the chi-square test was used for comparison of categorical data between two groups. Univariate and multivariate Cox proportional-hazards regression model analyses were used to investigate the influencing factors for the survival of HCV-HCC patients. The Kaplan-Meier method was used to plot survival curves and analyze the 2-year survival rate of HCV-HCC patients with different EZ-ALBI grades， and the log-rank test was used for comparison between groups. ResultsThere were significant differences between the survival group and the death group in platelet count， aspartate aminotransferase （AST）， total bilirubin， albumin （Alb）， alpha-fetoprotein （AFP）， prealbumin， prothrombin time， international normalized ratio， PALBI score， ALBI score， EZ-ALBI score， Model for End-Stage Liver Disease （MELD） score， HCV genotype， peritoneal effusion， and vascular invasion （all P<0.05）. The univariate Cox regression analysis showed that AST， Alb， AFP， ALBI score， EZ-ALBI score， PALBI score， MELD score， Barcelona Clinic Liver Cancer Staging， and peritoneal effusion were influencing factors for the survival of patients （all P<0.05）， and the multivariate Cox regression analysis showed that EZ-ALBI score （hazard ratio ［HR］=1.850， 95% confidence interval ［CI］： 1.054 — 3.247， P=0.032） and peritoneal effusion （HR=1.993， 95%CI： 1.030 — 3.858， P=0.041） were independent risk factors for the survival of HCV-HCC patients. The survival curve analysis showed that the patients with EZ-ALBI grade 1/2/3 had a 2-year survival rate of 90.9%， 60.2%， and 32.2%， respectively， and there was a significant difference in cumulative survival rate between the patients with different EZ-ALBI grades （χ²=26.294， P<0.001）. ConclusionEZ-ALBI score and the presence or absence of peritoneal effusion can be used as predictors of the survival of HCV-HCC patients.

OBJECTIVES: To explore the effects of cannabidiol on endoplasmic reticulum stress and neuronal apoptosis in rats with multiple concussions (MCC). METHODS: SD rats were randomized into sham group, MCC group, 1% tween20 (TW) treatment group, and low-dose (10 mg/kg) and high-dose (40 mg/kg) cannabidiol treatment groups. In all but the sham group, MCC models were established using a metal pendulum percussion device, after which the rats received daily intraperitoneal injections of the corresponding agents for 2 weeks. The expressions of PERK, eIF2α, ATF4, CHOP, TRIB3, p-Akt and pro-caspase-3 in the brain tissue of the rats were detected with qRT-PCR, Western blotting and immunofluorescence staining. The core targets of cannabidiol in treatment of traumatic brain injury (TBI) were identified by network pharmacology analysis, and molecular docking was carried out to simulate the interaction of cannabidiol with the factors related to endoplasmic reticulum stress and apoptosis. RESULTS: Compared with the sham-operated rats, the rat models of MCC showed significantly increased mRNA expressions of PERK, eIF2α and CHOP and protein expressions of PERK, eIF2α, ATF4, CHOP, TRIB3, p-AKT and pro-caspase-3 in the cerebral cortex. CBD treatment, especially at the high dose, obviously increased the expression of p-Akt and lowered the expression levels of the other factors tested in the rat models. Network pharmacology analysis indicated interactions of the core targets of CBD with the factors related to endoplasmic reticulum stress and TBI, and molecular docking study showed a high binding energy of CBD with multiple factors pertaining to endoplasmic reticulum stress and apoptosis. CONCLUSIONS MCC induce endoplasmic reticulum stress and apoptosis in rat brain tissues, for which CBD, especially at a high dose, provides neuroprotective effects by inhibiting endoplasmic reticulum stress and cell apoptosis.
Animals ; Endoplasmic Reticulum Stress/drug effects* ; Apoptosis/drug effects* ; Rats, Sprague-Dawley ; Activating Transcription Factor 4/metabolism* ; Transcription Factor CHOP/metabolism* ; Rats ; Eukaryotic Initiation Factor-2/metabolism* ; Signal Transduction/drug effects* ; eIF-2 Kinase/metabolism* ; Cannabidiol/pharmacology* ; Neurons/metabolism* ; Brain Concussion/metabolism* ; Male ; Molecular Docking Simulation

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 compare the efficacy of Tenofovir Alafenamide(TMF)and Tenofovir Disoproxil Fumarate(TDF)in terms of liver function restoration,virus clearance,immune regulation,anti liver fibrosis,lipid metabolism,bone and renal safety,and adverse reactions.Methods A retrospective analysis was conducted on 110 patients with chronic hepatitis B(CHB)admitted to Kunming Third People's Hospital from January 2022 to December 2022.Patients were divided into the TMF treatment group(n=55)and the TDF treatment group(n=55)based on their treatment regimen.We compared the levels of transaminase levels,antiviral efficacy,T cell subsets,renal function electrolytes,lipid metabolism,four liver fibrosis-related indicators,and changes in liver stiffness grading before and after treatment in two groups of patients.The incidence of adverse reactions post-treatment was also compared.Results After 48 weeks of treatment,the levels of TBIL,ALT,AST,GGT,and GLOB in both groups of patients were significantly lower than pre-treatment levels(P<0.05).The decrease in AST levels in the TMF group was lower than that in the TDF group(P<0.05).After 48 weeks of treatment,the HBV-DNA seroconversion rate in the TMF group(90.90%)was higher than that in the TDF group(83.64%).The serological HBsAg clearance rate in the TMF group(7.3%)was lower than that in the TDF group(9.1%),while the HBeAg clearance rate in the TMF group(38.2%)was significantly higher than that in the TDF group(18.2%),with statistical significance(P<0.05).After 48 weeks of treatment,levels of CD3+,CD4+,and CD8+in both groups were significantly elevated compared to pre-treatment levels(P<0.05);notably,the TMF group had higher post-treatment levels of CD3+,CD4+,and CD8+than the TDF group.After 48 weeks,the average values of HA,IV-C,and LN among the TMF group for liver fibrosis indicators were significantly lower than those in the TDF group(P<0.05).The proportions of F0 and F2 in both groups significantly increased post-treatment,while the proportions of F3 and F4 significantly decreased(P to be supplemented);furthermore,the proportions of F0 and F2 in the TMF group were significantly higher than those in the TDF group,and the proportions of F3 and F4 in the TMF group were significantly lower than those in the TDF group(P<0.05).After 48 weeks,HDL-C levels in the TMF group increased compared to pre-treatment(P<0.05).There were no significant differences in TG,TC,HDL-C,or LDL-C levels in the TDF group compared to pre-treatment(P>0.05).After 48 weeks of treatment,there was no difference in the levels of BUN、Cr、P+,and Ca+in the TMF group compared to pre-treatment(P>0.05);however,BUN and Cr levels in the TDF group were significantly higher than pre-treatment levels,while P+and Ca+levels were significantly lower(P<0.05).The incidence of elevated uric acid and bone pain was significantly higher in the TMF group compared to the TDF group(P<0.05);the incidence of diarrhea and abdominal pain was slightly higher in the TMF group compared to the TDF group(P>0.05).Conclusion Compared to TDF,TMF demonstrates a higher rate of liver function recovery,a greater virological response,enhanced anti fibrotic efficacy,and improved drug safety,making it worthy of clinical application in the future.

Objective To investigate the value of albumin-bilirubin(ALBI),easy albumin-bilirubin(EZ-ALBI),and platelet-albumin-bilirubin(PALBI)scores in predicting 2-year survival in patients with HCV-associated hepatocellular carcinoma(HCV-HCC).Methods A retrospective analysis was performed for the clinical data of 174 patients with HCV-HCC who were admitted to The Third People's Hospital of Kunming from January 2020 to January 2022,and the patients were followed up till 2 years after admission.According to the follow-up results,the patients were divided into survival group with 95 patients and death group with 79 patients.The independent-samples t test or the Mann-Whitney U test was used for comparison of continuous data between two groups,and the chi-square test was used for comparison of categorical data between two groups.Univariate and multivariate Cox proportional-hazards regression model analyses were used to investigate the influencing factors for the survival of HCV-HCC patients.The Kaplan-Meier method was used to plot survival curves and analyze the 2-year survival rate of HCV-HCC patients with different EZ-ALBI grades,and the log-rank test was used for comparison between groups.Results There were significant differences between the survival group and the death group in platelet count,aspartate aminotransferase(AST),total bilirubin,albumin(Alb),alpha-fetoprotein(AFP),prealbumin,prothrombin time,international normalized ratio,PALBI score,ALBI score,EZ-ALBI score,Model for End-Stage Liver Disease(MELD)score,HCV genotype,peritoneal effusion,and vascular invasion(all P<0.05).The univariate Cox regression analysis showed that AST,Alb,AFP,ALBI score,EZ-ALBI score,PALBI score,MELD score,Barcelona Clinic Liver Cancer Staging,and peritoneal effusion were influencing factors for the survival of patients(all P<0.05),and the multivariate Cox regression analysis showed that EZ-ALBI score(hazard ratio[HR]=1.850,95%confidence interval[CI]:1.054-3.247,P=0.032)and peritoneal effusion(HR=1.993,95%CI:1.030-3.858,P=0.041)were independent risk factors for the survival of HCV-HCC patients.The survival curve analysis showed that the patients with EZ-ALBI grade 1/2/3 had a 2-year survival rate of 90.9%,60.2%,and 32.2%,respectively,and there was a significant difference in cumulative survival rate between the patients with different EZ-ALBI grades(χ2=26.294,P<0.001).Conclusion EZ-ALBI score and the presence or absence of peritoneal effusion can be used as predictors of the survival of HCV-HCC patients.

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.