1.Influencing factors for recompensation and its impact on the prognosis in patients with decompensated liver cirrhosis
Danqing XU ; Haiwen LI ; Huan MU ; Yingyuan ZHANG ; Caifen SA ; Li LIU ; Yongrui YANG
Journal of Clinical Hepatology 2026;42(1):90-100
ObjectiveTo investigate the influencing factors for recompensation in patients with decompensated liver cirrhosis, as well as the impact of recompensation on the prognosis of such patients, and to provide a basis for early identification of high-risk patients in clinical practice. MethodsA retrospective analysis was performed for the clinical data of patients who attended The Third People’s Hospital of Kunming from January 2016 to December 2022 and were diagnosed with decompensated liver cirrhosis due to hepatitis B, hepatitis C, alcoholic hepatitis, and autoimmune hepatitis, and they were divided into recompensation group and persistent decompensation group. To control for confounding factors, whether recompensation occurred was used as the rouping variable,and BMI, alcohol consumption history, HIV infection history, TG, CHOL, LDL, and HDL were used as covariates. The propensity score was calculated, and 1:1 nearest neighbor matching was performed with a caliper value of 0.1. After propensity score matching, the recompensation group and the persistent decompensation group with relatively balanced covariates were obtained. Univariate and multivariate Cox proportional-hazards regression model analyses were used to investigate the influencing factors for recompensation; the “rms” package was used to establish a nomogram; the receiver operating characteristic (ROC) curve was plotted to calculate the area under the ROC curve (AUC); the Hosmer-Lemeshow test was used to assess the goodness of fit of the model; the “Calibration Curves” package was used to plot calibration curves for model assessment. The Kaplan-Meier method was used to plot survival curves, and the Log-rank test was used for comparison of survival curves. ResultsAmong the 863 patients with decompensated liver cirrhosis, 305 experienced recompensation, resulting in an incidence rate of 35.3%. After PSM, 610 cases were successfully matched, with 305 cases in each group. The univariate and multivariate Cox regression analyses showed that etiology (hepatitis C: hazard ratio[HR]=0.288, P=0.002); male(HR=0.701, P=0.016), age(HR=0.988, P=0.047), hemoglobin (HGB)(HR=1.006, P=0.017), and CD4 T cell(HR=1.001,P=0.047), TIPS procedure (HR=1.808,P=0.042) were independent influencing factors for recompensation in patients with decompensated liver cirrhosis. During follow-up, 116 patients died of liver disease-related causes, with 27 patients (8.85%) in the recompensation group and 89 (15.95%) in the persistent decompensation group; 109 patients developed HCC, with 23 patients (7.54%) in the recompensation group and 86 (15.41%) in the persistent decompensation group. The Kaplan-Meier survival curves showed significant separation between the patients with different states of compensation in terms of liver disease-related mortality rate and the incidence rate of HCC, and the Log-rank test showed that there were significant differences between the two groups in liver disease-related mortality rate (χ2=9.023, P=0.003) and the incidence rate of HCC (χ2=10.526, P=0.001). ConclusionEtiology,sex,age,TIPS,HGB,and CD4 T cell are independent influencing factors for recompensation in patients with decompensated liver cirrhosis. There is a significant difference in the incidence rate of recompensation between decompensated liver cirrhosis patients with different etiologies, and female patients and patients with a younger age,a history of TIPS, a higher HGB level, and a higher CD4 lymphocyte count are more likely to experience recompensation. Recompensation is the key to improving the long-term prognosis of patients and can significantly reduce long-term liver disease-related mortality rate and the incidence rate of HCC.
2.Risk factors for concurrent hepatic hydrothorax before intervention in primary liver cancer and construction of a nomogram prediction model
Yuanzhen WANG ; Renhai TIAN ; Yingyuan ZHANG ; Danqing XU ; Lixian CHANG ; Chunyun LIU ; Li LIU
Journal of Clinical Hepatology 2025;41(1):75-83
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.
3.Influencing factors for recompensation in patients with decompensated hepatitis C cirrhosis
Danqing XU ; Huan MU ; Yingyuan ZHANG ; Lixian CHANG ; Yuanzhen WANG ; Weikun LI ; Zhijian DONG ; Lihua ZHANG ; Yijing CHENG ; Li LIU
Journal of Clinical Hepatology 2025;41(2):269-276
ObjectiveTo investigate the influencing factors for recompensation in patients with decompensated hepatitis C cirrhosis, and to establish a predictive model. MethodsA total of 217 patients who were diagnosed with decompensated hepatitis C cirrhosis and were admitted to The Third People’s Hospital of Kunming l from January, 2019 to December, 2022 were enrolled, among whom 63 patients who were readmitted within at least 1 year and had no portal hypertension-related complications were enrolled as recompensation group, and 154 patients without recompensation were enrolled as control group. Related clinical data were collected, and univariate and multivariate analyses were performed for the factors that may affect the occurrence of recompensation. The independent-samples t test was used for comparison of normally distributed measurement data between two groups, and the Mann-Whitney U test was used for comparison of non-normally distributed measurement data between two groups; the chi-square test or the Fisher’s exact test was used for comparison of categorical data between two groups. A binary Logistic regression analysis was used to investigate the influencing factors for recompensation in patients with decompensated hepatitis C cirrhosis, and the receiver operating characteristic (ROC) curve was used to assess the predictive performance of the model. ResultsAmong the 217 patients with decompensated hepatitis C cirrhosis, 63 (29.03%) had recompensation. There were significant differences between the recompensation group and the control group in HIV history (χ2=4.566, P=0.034), history of partial splenic embolism (χ2=6.687, P=0.014), Child-Pugh classification (χ2=11.978, P=0.003), grade of ascites (χ2=14.229, P<0.001), albumin (t=4.063, P<0.001), prealbumin (Z=-3.077, P=0.002), high-density lipoprotein (t=2.854, P=0.011), high-sensitivity C-reactive protein (Z=-2.447, P=0.014), prothrombin time (Z=-2.441, P=0.015), carcinoembryonic antigen (Z=-2.113, P=0.035), alpha-fetoprotein (AFP) (Z=-2.063, P=0.039), CA125 (Z=-2.270, P=0.023), TT3 (Z=-3.304, P<0.001), TT4 (Z=-2.221, P=0.026), CD45+ (Z=-2.278, P=0.023), interleukin-5 (Z=-2.845, P=0.004), tumor necrosis factor-α (Z=-2.176, P=0.030), and portal vein width (Z=-5.283, P=0.005). The multivariate analysis showed that history of partial splenic embolism (odds ratio [OR]=3.064, P=0.049), HIV history (OR=0.195, P=0.027), a small amount of ascites (OR=3.390, P=0.017), AFP (OR=1.003, P=0.004), and portal vein width (OR=0.600, P<0.001) were independent influencing factors for the occurrence of recompensation in patients with decompensated hepatitis C cirrhosis. The ROC curve analysis showed that HIV history, grade of ascites, history of partial splenic embolism, AFP, portal vein width, and the combined predictive model of these indices had an area under the ROC curve of 0.556, 0.641, 0.560, 0.589, 0.745, and 0.817, respectively. ConclusionFor patients with decompensated hepatitis C cirrhosis, those with a history of partial splenic embolism, a small amount of ascites, and an increase in AFP level are more likely to experience recompensation, while those with a history of HIV and an increase in portal vein width are less likely to experience recompensation.
4.Engineered Extracellular Vesicles Loaded with MiR-100-5p Antagonist Selectively Target the Lesioned Region to Promote Recovery from Brain Damage.
Yahong CHENG ; Chengcheng GAI ; Yijing ZHAO ; Tingting LI ; Yan SONG ; Qian LUO ; Danqing XIN ; Zige JIANG ; Wenqiang CHEN ; Dexiang LIU ; Zhen WANG
Neuroscience Bulletin 2025;41(6):1021-1040
Hypoxic-ischemic (HI) brain damage poses a high risk of death or lifelong disability, yet effective treatments remain elusive. Here, we demonstrated that miR-100-5p levels in the lesioned cortex increased after HI insult in neonatal mice. Knockdown of miR-100-5p expression in the brain attenuated brain injury and promoted functional recovery, through inhibiting the cleaved-caspase-3 level, microglia activation, and the release of proinflammation cytokines following HI injury. Engineered extracellular vesicles (EVs) containing neuron-targeting rabies virus glycoprotein (RVG) and miR-100-5p antagonists (RVG-EVs-Antagomir) selectively targeted brain lesions and reduced miR-100-5p levels after intranasal delivery. Both pre- and post-HI administration showed therapeutic benefits. Mechanistically, we identified protein phosphatase 3 catalytic subunit alpha (Ppp3ca) as a novel candidate target gene of miR-100-5p, inhibiting c-Fos expression and neuronal apoptosis following HI insult. In conclusion, our non-invasive method using engineered EVs to deliver miR-100-5p antagomirs to the brain significantly improves functional recovery after HI injury by targeting Ppp3ca to suppress neuronal apoptosis.
Animals
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MicroRNAs/metabolism*
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Extracellular Vesicles/metabolism*
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Mice
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Recovery of Function/physiology*
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Hypoxia-Ischemia, Brain/therapy*
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Mice, Inbred C57BL
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Antagomirs/administration & dosage*
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Male
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Animals, Newborn
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Apoptosis/drug effects*
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Brain Injuries/metabolism*
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Glycoproteins
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Peptide Fragments
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Viral Proteins
5.Value of FibroScan, gamma-glutamyl transpeptidase-to-platelet ratio, S index, interleukin-6, and tumor necrosis factor-α in the diagnosis of HBeAg-positive chronic hepatitis B liver fibrosis
Yingyuan ZHANG ; Danqing XU ; Huan MU ; Chunyan MOU ; Lixian CHANG ; Yuanzhen WANG ; Hongyan WEI ; Li LIU ; Weikun LI ; Chunyun LIU
Journal of Clinical Hepatology 2025;41(4):670-676
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.
6.Value of albumin-bilirubin, easy albumin-bilirubin, and platelet-albumin-bilirubin scores in predicting the prognosis of patients with HCV-associated hepatocellular carcinoma
Huan MU ; Yingyuan ZHANG ; Danqing XU ; Yuanqiang HE ; Chunyan MOU ; Chunyun LIU ; Li LIU
Journal of Clinical Hepatology 2025;41(5):921-926
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.
7.Buqi-Tongluo Decoction inhibits osteoclastogenesis and alleviates bone loss in ovariectomized rats by attenuating NFATc1, MAPK, NF-κB signaling.
Yongxian LI ; Jinbo YUAN ; Wei DENG ; Haishan LI ; Yuewei LIN ; Jiamin YANG ; Kai CHEN ; Heng QIU ; Ziyi WANG ; Vincent KUEK ; Dongping WANG ; Zhen ZHANG ; Bin MAI ; Yang SHAO ; Pan KANG ; Qiuli QIN ; Jinglan LI ; Huizhi GUO ; Yanhuai MA ; Danqing GUO ; Guoye MO ; Yijing FANG ; Renxiang TAN ; Chenguang ZHAN ; Teng LIU ; Guoning GU ; Kai YUAN ; Yongchao TANG ; De LIANG ; Liangliang XU ; Jiake XU ; Shuncong ZHANG
Chinese Journal of Natural Medicines (English Ed.) 2025;23(1):90-101
Osteoporosis is a prevalent skeletal condition characterized by reduced bone mass and strength, leading to increased fragility. Buqi-Tongluo (BQTL) decoction, a traditional Chinese medicine (TCM) prescription, has yet to be fully evaluated for its potential in treating bone diseases such as osteoporosis. To investigate the mechanism by which BQTL decoction inhibits osteoclast differentiation in vitro and validate these findings through in vivo experiments. We employed MTS assays to assess the potential proliferative or toxic effects of BQTL on bone marrow macrophages (BMMs) at various concentrations. TRAcP experiments were conducted to examine BQTL's impact on osteoclast differentiation. RT-PCR and Western blot analyses were utilized to evaluate the relative expression levels of osteoclast-specific genes and proteins under BQTL stimulation. Finally, in vivo experiments were performed using an osteoporosis model to further validate the in vitro findings. This study revealed that BQTL suppressed receptor activator of NF-κB ligand (RANKL)-induced osteoclastogenesis and osteoclast resorption activity in vitro in a dose-dependent manner without observable cytotoxicity. The inhibitory effects of BQTL on osteoclast formation and function were attributed to the downregulation of NFATc1 and c-fos activity, primarily through attenuation of the MAPK, NF-κB, and Calcineurin signaling pathways. BQTL's inhibitory capacity was further examined in vivo using an ovariectomized (OVX) rat model, demonstrating a strong protective effect against bone loss. BQTL may serve as an effective therapeutic TCM for the treatment of postmenopausal osteoporosis and the alleviation of bone loss induced by estrogen deficiency and related conditions.
Animals
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NFATC Transcription Factors/genetics*
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Drugs, Chinese Herbal/pharmacology*
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Ovariectomy
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Osteoclasts/metabolism*
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Female
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Osteogenesis/drug effects*
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Rats, Sprague-Dawley
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Rats
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NF-kappa B/genetics*
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Osteoporosis/genetics*
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Signal Transduction/drug effects*
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Bone Resorption/genetics*
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Cell Differentiation/drug effects*
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Humans
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RANK Ligand/metabolism*
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Mitogen-Activated Protein Kinases/genetics*
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Transcription Factors
8.Association between albumin and recompensation in patients with hepatitis B/C virus-related decompensated liver cirrhosis
Danqing XU ; Yingyuan ZHANG ; Jingru SHANG ; Caifen SA ; Wenyan LI ; Li LIU ; Zhijian DONG
Journal of Clinical Hepatology 2025;41(11):2323-2328
ObjectiveTo investigate the association between albumin (Alb) and recompensation by comparing recompensation rate between hepatitis B/C virus-related decompensated liver cirrhosis patients with different Alb levels, and to provide guidance for the identification and management of high-risk patients in clinical practice. MethodsRelated clinical data were collected from 734 patients with hepatitis B/C virus-related decompensated liver cirrhosis who attended The Third People’s Hospital of Kunming from January 1, 2016 to December 31, 2022, and they were divided into three groups based on the level of Alb. The linear regression analysis and chi-square test were used for trend tests. The Kaplan-Meier curve was plotted for the cumulative incidence rate of recompensation in the three groups, and the log-rank test was used for comparison between groups. A Cox proportional-hazards regression model analysis was used to investigate the association between Alb and recompensation in patients with hepatitis B/C virus-related decompensated liver cirrhosis. ResultsAmong the 734 patients with hepatitis B/C virus-related decompensated liver cirrhosis, 270 achieved recompensation, with a recompensation rate of 36.8%. All patients had a median Alb level of 29.90 (25.90 — 34.80) g/L on admission, and according to the level of Alb, they were divided into <25.9 g/L group with 177 patients, 25.9 — 34.8 g/L group with 377 patients, and >34.8 g/L group with 180 patients; 36 patients (20.3%) in the <25.9 g/L group, 138 (36.6%) in the 25.9 — 34.8 g/L group, and 96 (53.3%) in the >34.8 g/L group achieved recompensation, and the recompensation rate increased with the increase in Alb level (χ2=41.730, P<0.001). After adjustment for all confounding factors, compared with the <25.9 g/L group, there was a significant increase in the incidence rate of recompensation in the 25.9 — 34.8 g/L group (hazard ratio [HR]=1.842, 95% confidence interval [CI]: 1.274 — 2.663) and the >34.8 g/L group (HR=2.336, 95% CI: 1.575 — 3.463). The Kaplan-Meier survival analysis showed that there was a significant difference in the cumulative incidence rate of recompensation between the three groups (χ2=41.632, P<0.001). ConclusionAlb level is an influencing factor for recompensation in patients with hepatitis B/C virus-related decompensated liver cirrhosis, and the recompensation rate increases with the increase in Alb level.
9.Analysis of influencing factors and construction of predictive model for HBsAg clearance in patients with HBeAg-negative chronic hepatitis B treated with PEG-IFN-α-2b
Yingyuan ZHANG ; Danqing XU ; Huan MU ; Yuanqiang HE ; Yuanzhen WANG ; Chunyun LIU ; Weikun LI ; Chunyan MOU ; Li LIU
Journal of Clinical Hepatology 2025;41(8):1525-1532
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.
10.The study on the optimization of portal vein image quality in liver cirrhosis by combining deep learning image reconstruction with"three low techniques"spectrum CT with low keV
Ming LI ; Yongjun JIA ; Li SHEN ; Junfeng FAN ; Nan YU ; Yong YU ; Danqing ZHANG
Journal of Practical Radiology 2025;41(10):1729-1733
Objective To explore the value of deep learning image reconstruction(DLIR)combined with"three low(low radiation dose,low contrast dose,and low contrast injection rate)techniques"of spectrum CT with low keV in optimizing the image quality of portal vein for liver cirrhosis.Methods Sixty patients with liver cirrhosis who underwent computed tomography portal venography(CTPV)were selected and randomly divided into standard protocol group(group A,n=30)and"three-low"protocol group(group B,n=30).The group A with 120 kVp,contrast dose of 1.4 mL/kg,injection rate of 4.0-5.0 mL/s,and reconstructed 50%adaptive statistical iterative reconstruction-Veo(ASIR-V)image.The group B with 80 kVp/140 kVp double instantaneous switching gemstone spectral imaging(GSI)scan,contrast dose of 1.0 mL/kg,injection rate of 3.0-3.5 mL/s,and reconstructed 40 keV DLIR-M and DLIR-H images.The quality of portal vein images,effective dose(ED),contrast dose and injection rate were compared between the two groups.Results The ED of(4.10±1.56)mSv in group B was lower than that of(7.88±1.08)mSv in group A(P<0.001),and the contrast dose of(67.26±8.74)mL in group B was lower than that of(99.12±8.84)mL in group A(P<0.001).The injection rate of 3.0-3.5 mL/s in group B was reduced by 25%-30%compared with group A.Group B had the greatest contrast-to-noise ratio(CNR)and signal-to-noise ratio(SNR)of portal vein in the 40 keV DLIR-H.The subjective image quality scores were in good agreement between the two physicians(Kappa value>0.75).The subjective DLIR score in group B was higher than that in group A.Conclusion DLIR combined with"three low techniques"spectrum CT with low keV can improve the image quality of portal vein in liver cirrhosis patients.

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