Observation on the Therapeutic Effect of Yiqi Huoxue Huazhuo Therapy on Hepatic Fibrosis in Wilson's Disease / 广州中医药大学学报

Objective To assess the clinical effect of the Yiqi Huoxue Huazhuo therapy(the therapy for replenishing qi,activating blood and resolving turbidity)for the treatment of hepatic fibrosis in Wilson's disease(WD,also known as hepatolenticular degeneration).Methods Using retrospective research method,52 patients with liver fibrosis in WD of qi deficiency and blood stasis type were divided into 24 cases in the control group and 28 cases in the treatment group according to the treatment method.The control group was treated with conventional decopper therapy with western medicines,and the treatment group was treated with Chinese herbal decoction based on Yiqi Huoxue Huazhuo therapy together with conventional decopper therapy.Both groups were treated for a total of 4 weeks.Before and after the treatment,the two groups were observed in the changes of traditional Chinese medicine(TCM)syndrome scores,Unified Wilson's Disease Rating Scale(UWDRS)hepatic symptom scores,serum levels of liver fibrosis indicators of pre-collagen typeⅢ(PCⅢ),hyaluronic acid(HA),collagenⅣ(CⅣ),and laminin(LN),C-X-C motif chemokine ligand 10(CXCL10)level,and the point shear-wave elastography(pSWE)values of hepatic ultrasound based on acoustic radiation force impulse imaging(ARFI).After treatment,the clinical efficacy of the two groups was evaluated.Results(1)After 4 weeks of treatment,the total effective rate of the treatment group was 85.71%(24/28),while that of the control group was 54.17%(13/24),and the intergroup comparison(tested by chi-square test)showed that the therapeutic efficacy of the treatment group was significantly superior to that of the control group(P＜0.05).(2)After treatment,the TCM syndrome scores in both groups were decreased compared with those before treatment(P＜0.01),and the decrease of TCM syndrome scores in the treatment group was significantly superior to that in the control group(P＜0.05).(3)After treatment,the UWDRS liver symptom scores in the two groups were decreased compared with those before treatment(P＜0.01),but the difference was not statistically significant when comparing between the two groups after treatment(P＞0.05).(4)After treatment,serum levels of liver fibrosis indicators of HA,LN,CⅣ and PCⅢ in the treatment group were all decreased compared with those before treatment(P＜0.01),while in the control group only serum LN and PCⅢlevels were decreased(P＜0.05).The intergroup comparison showed that the decrease of serum HA,LN,and PCⅢlevels in the treatment group was superior to that in the control group(P＜0.05 or P＜0.01),while the decrease of serum CⅣlevel tended to be superior to that in the control group,but the difference was not statistically significant(P＞0.05).(5)After treatment,the serum chemokine CXCL10 level in the treatment group was significantly decreased compared with that before treatment(P＜0.01),while the level tended to decrease in the control group,but the difference was not statistically significant(P＞0.05).The intergroup comparison showed that the reduction of serum CXCL10 level in the treatment group was significantly superior to that in the control group(P＜0.05).(6)After treatment,the pSWE values of hepatic ultrasound in the two groups were lower than those before treatment(P＜0.01),and the reduction of pSWE values in treatment group was significantly superior to that of the control group(P＜0.01).Conclusion Yiqi Huoxue Huazhuo therapy can effectively reduce the TCM syndrome scores of WD patients,improve the UWDRS hepatic symptom scores,down-regulate the liver fibrosis indicator level and serum CXCL10 expression level,reduce the pSWE values of hepatic ultrasound,and enhance the clinical efficacy.

Predictive value of intratumoral heterogeneity measured by 18F-FDG PET/CT for EGFR mutation of adenocarcinoma / 中华核医学与分子影像杂志

Objective:To investigate the value of traditional metabolic parameters, CT features and intratumoral heterogeneity parameters measured by 18F-FDG PET/CT in predicting the mutation status of the epidermal growth factor receptor (EGFR) gene in patients with adenocarcinoma. Methods:A total of 147 patients (73 males, 74 females, age (59.8±10.2) years) with pathological confirmed adenocarcinoma between January 2016 and June 2020 in the Affiliated Hospital of Jining Medical University were retrospectively included. The differences of clinical data (smoking history, tumor location and clinical stage), CT features (maximum diameter, ground-glass opacity content, lobulation, speculation, cavitation, air-bronchogram, pleural retraction and bronchial cut-off sign), 18F-FDG PET/CT traditional metabolic parameters (SUV max, SUV mean, metabolic tumor volume (MTV) and total lesion glycolysis (TLG)) and intratumoral heterogeneity parameters ( CV, heterogeneity index (HI)) were analyzed between patients with EGFR mutation and patients with EGFR wild-type. Independent-sample t test, Mann-Whitney U test and χ2 test were used to analyze the data. Multivariate logistic regression was used to analyze the predictors of EGFR mutation. ROC curve analysis was used to evaluate the predictive value of clinical and PET/CT information. Results:Among 147 patients, 87 were with EGFR mutation and 60 were with EGFR wild-type. There were significant differences in gender (male/female), smoking history (with/without), location (peripheral lesion/central lesion), pleural retraction (with/without), SUV max, SUV mean, TLG, CV and HI ( χ2 values: 4.72-23.89, z values: from -2.31 to 5.74, all P<0.05). Multivariate logistic regression analysis showed that smoking history (odds ratio ( OR)=0.167, 95% CI: 0.076-0.366; P<0.001), pleural retraction ( OR=1.404, 95% CI: 1.115-3.745; P=0.012), SUV max ( OR=0.922, 95% CI: 0.855-0.995; P=0.003), TLG ( OR=0.991, 95% CI: 0.986-0.996; P=0.001) and HI ( OR=0.796, 95% CI: 0.700-0.859; P<0.001) were predictors of EGFR mutation. ROC curve analysis showed the AUC of HI was 0.779, with the sensitivity of 76.67%(46/60) and the specificity of 79.31%(69/87). The predictive model was constructed by combining smoking history, pleural retraction, TLG, SUV max and HI, and the AUC was 0.908, with the sensitivity of 88.33%(53/60) and the specificity of 68.97%(60/87). The difference of AUCs between HI and the predictive model was statistically significant ( z=3.71, P<0.001). Conclusion:HI can predict EGFR mutations better, and the predictive value for EGFR mutations can be enhanced when combining HI with smoking history, pleural retraction, TLG and SUV max.

Stellate Ganglion Block as an Adjunctive Intervention for Chronic Subjective Tinnitus： Efficacy and Predictive Indicators / 中山大学学报(医学科学版)

ObjectiveTo explore the efficacy and predictive indicators of stellate ganglion block （SGB） as an adjunctive intervention for chronic subjective tinnitus and accumulate experience for the application of SGB in the clinical treatment of tinnitus. MethodsA retrospective review was conducted on the data of chronic subjective tinnitus patients who received SGB intervention， with unsatisfactory outcomes otherwise. Pure tone audiometry （PTA）， tinnitus loudness evaluation and Pittsburgh sleep quality index （PSQI） were used. The tinnitus handicap inventory （THI） scores were compared before and after SGB intervention. Correlation analysis and linear regression equations were employed to identify the potential indicators predicting the effectiveness of SGB intervention. Statistical analysis was performed by SPSS 24.0 software. ResultsBy April 2023， a total of 107 patients with chronic subjective tinnitus had undergone SGB intervention， including 67 male and 40 female， with a mean age of （45.32±11.40） years old and an average tinnitus history of （20.32±24.64） months ［16 （12~20）］. Only 7 patients （6.54%） quitted the intervention for personal reasons， which demonstrated good compliance with the intervention. No patients experienced adverse reactions such as infection at the injection site， hematoma， nerve injury， local anesthetic intoxication and so on， which revealed good safety. After SGB intervention， THI scores decreased to below 36 points in 77 patients and decrease by 10 points or more in 12 of the remaining patients， with a total effective rate of 89%. A paired sample t-test showed a significant difference in THI scores before and after SGB intervention （t=15.575， P<0.001）， indicating good improvement. Pearson correlation analysis suggested that pre-intervention THI scores and subjective tinnitus loudness were significantly positively correlated with the improvement level of THI scores （P<0.05）. Further stepwise linear regression analysis found that "pre-intervention THI scores" had statistical significance （P<0.001）， with a regression coefficient of 0.308， predicting a 17.4% improvement level in THI scores. ConclusionsDue to its good and safe short-term effects， SGB intervention can be used as a supplementary option for chronic subjective tinnitus when other interventions are not ideal， especially for patients with higher THI scores. However， further research is needed to clarify the long-term efficacy and underlying mechanisms， in order to establish a more solid theoretical basis for SGB intervention in the treatment of subjective tinnitus.

Non-linear association between long-term air pollution exposure and risk of metabolic dysfunction-associated steatotic liver disease

BACKGROUND@#Metabolic Dysfunction-associated Steatotic Liver Disease (MASLD) has become a global epidemic, and air pollution has been identified as a potential risk factor. This study aims to investigate the non-linear relationship between ambient air pollution and MASLD prevalence.@*METHOD@#In this cross-sectional study, participants undergoing health checkups were assessed for three-year average air pollution exposure. MASLD diagnosis required hepatic steatosis with at least 1 out of 5 cardiometabolic criteria. A stepwise approach combining data visualization and regression modeling was used to determine the most appropriate link function between each of the six air pollutants and MASLD. A covariate-adjusted six-pollutant model was constructed accordingly.@*RESULTS@#A total of 131,592 participants were included, with 40.6% met the criteria of MASLD. "Threshold link function," "interaction link function," and "restricted cubic spline (RCS) link functions" best-fitted associations between MASLD and PM2.5, PM10/CO, and O3 /SO2/NO2, respectively. In the six-pollutant model, significant positive associations were observed when pollutant concentrations were over: 34.64 µg/m3 for PM2.5, 57.93 µg/m3 for PM10, 56 µg/m3 for O3, below 643.6 µg/m3 for CO, and within 33 and 48 µg/m3 for NO2. The six-pollutant model using these best-fitted link functions demonstrated superior model fitting compared to exposure-categorized model or linear link function model assuming proportionality of odds.@*CONCLUSION@#Non-linear associations were found between air pollutants and MASLD prevalence. PM2.5, PM10, O3, CO, and NO2 exhibited positive associations with MASLD in specific concentration ranges, highlighting the need to consider non-linear relationships in assessing the impact of air pollution on MASLD.

Taiwan Association for the Study of the Liver-Taiwan Society of Cardiology Taiwan position statement for the management of metabolic dysfunction- associated fatty liver disease and cardiovascular diseases

Metabolic dysfunction-associated fatty liver disease (MAFLD) is an increasingly common liver disease worldwide. MAFLD is diagnosed based on the presence of steatosis on images, histological findings, or serum marker levels as well as the presence of at least one of the three metabolic features: overweight/obesity, type 2 diabetes mellitus, and metabolic risk factors. MAFLD is not only a liver disease but also a factor contributing to or related to cardiovascular diseases (CVD), which is the major etiology responsible for morbidity and mortality in patients with MAFLD. Hence, understanding the association between MAFLD and CVD, surveillance and risk stratification of MAFLD in patients with CVD, and assessment of the current status of MAFLD management are urgent requirements for both hepatologists and cardiologists. This Taiwan position statement reviews the literature and provides suggestions regarding the epidemiology, etiology, risk factors, risk stratification, nonpharmacological interventions, and potential drug treatments of MAFLD, focusing on its association with CVD.

Artificial intelligence predicts direct-acting antivirals failure among hepatitis C virus patients: A nationwide hepatitis C virus registry program

Background/Aims@#Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. @*Methods@#We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. @*Results@#The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. @*Conclusions@#Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.

Metformin and statins reduce hepatocellular carcinoma risk in chronic hepatitis C patients with failed antiviral therapy

Background/Aims@#Chronic hepatitis C (CHC) patients who failed antiviral therapy are at increased risk for hepatocellular carcinoma (HCC). This study assessed the potential role of metformin and statins, medications for diabetes mellitus (DM) and hyperlipidemia (HLP), in reducing HCC risk among these patients. @*Methods@#We included CHC patients from the T-COACH study who failed antiviral therapy. We tracked the onset of HCC 1.5 years post-therapy by linking to Taiwan’s cancer registry data from 2003 to 2019. We accounted for death and liver transplantation as competing risks and employed Gray’s cumulative incidence and Cox subdistribution hazards models to analyze HCC development. @*Results@#Out of 2,779 patients, 480 (17.3%) developed HCC post-therapy. DM patients not using metformin had a 51% increased risk of HCC compared to non-DM patients, while HLP patients on statins had a 50% reduced risk compared to those without HLP. The 5-year HCC incidence was significantly higher for metformin non-users (16.5%) versus non-DM patients (11.3%; adjusted sub-distribution hazard ratio [aSHR]=1.51; P=0.007) and metformin users (3.1%; aSHR=1.59; P=0.022). Statin use in HLP patients correlated with a lower HCC risk (3.8%) compared to non-HLP patients (12.5%; aSHR=0.50; P<0.001). Notably, the increased HCC risk associated with non-use of metformin was primarily seen in non-cirrhotic patients, whereas statins decreased HCC risk in both cirrhotic and non-cirrhotic patients. @*Conclusions@#Metformin and statins may have a chemopreventive effect against HCC in CHC patients who failed antiviral therapy. These results support the need for personalized preventive strategies in managing HCC risk.

Robot-assisted minimally invasive coronary artery bypass in treating multi-vessel coronary artery disease: A retrospective study in a single center / 中国胸心血管外科临床杂志

@#Objective    To evaluate the early and mid-term results of robot-assisted coronary artery bypass grafting (RACAB) in the treatment of multi-vessel coronary artery disease (MV-CAD). Methods     Patients with MV-CAD who underwent RACAB from April 2018 to December 2021 in our hospital were included. Patients who underwent hybrid coronary revascularization (HCR) which combined RACAB with percutaneous coronary intervention were allocated to a HCR-RACAB group, and patients who underwent multi-vessel RACAB were allocated to a MV-RACAB group. Perioperative and follow-up data were collected and compared between the two groups. Results     A total of 102 patients were included, including 81 males and 21 females with a mean age of 61.7±10.8 years. Two (2.0%) patients were transferred to conventional CABG due to sudden ventricular fibrillation and pleura adhesion. In the remaining 100 patients who underwent RACAB, 100 left internal mammary arteries (LIMA) and 46 right internal mammary arteries (RIMA) were harvested with a 100.0% success rate. Besides, all patients undergoing RACAB achieved LIMA/RIMA-left anterior descending branch reconstruction, with an average number of 2.5±0.6 target vessels revascularized by stent or graft. One patient had perioperative myocardial infarction with an outcome of death. The incidence of major perioperative adverse events was 1.0%. There was no perioperative stroke or re-sternotomy for hemostasis. The mean follow-up time was 28.2 months, with a follow-up rate of 99.0% and an overall major adverse cardiac and cerebrovascular event (MACCE) rate of 7.0%, including 3 all-cause deaths (3.0%), 2 strokes (2.0%) and 3 re-revascularizations (3.0%). The HCR-RACAB group had fewer red blood cell transfusion (P=0.030) and intraoperative blood loss (P=0.037) compared with the MV-RACAB group, and there was no statistical difference in the incidence of major perioperative adverse events or MACCE between the two groups during the follow-up period (P>0.05). Conclusion    RACAB can be safely applied in the treatment of MV-CAD with good early and mid-term outcomes. High-quality harvesting of LIMA/RIMA and aortic no-touch technique are crucial to achieve these results.

Heterogeneity of the tumor immune microenvironment and clinical interventions / 医学前沿

The tumor immune microenvironment (TIME) is broadly composed of various immune cells, and its heterogeneity is characterized by both immune cells and stromal cells. During the course of tumor formation and progression and anti-tumor treatment, the composition of the TIME becomes heterogeneous. Such immunological heterogeneity is not only present between populations but also exists on temporal and spatial scales. Owing to the existence of TIME, clinical outcomes can differ when a similar treatment strategy is provided to patients. Therefore, a comprehensive assessment of TIME heterogeneity is essential for developing precise and effective therapies. Facilitated by advanced technologies, it is possible to understand the complexity and diversity of the TIME and its influence on therapy responses. In this review, we discuss the potential reasons for TIME heterogeneity and the current approaches used to explore it. We also summarize clinical intervention strategies based on associated mechanisms or targets to control immunological heterogeneity.

The development of a predictive model of self-injurious behavior and the influencing factors among college students / 中华行为医学与脑科学杂志

Objective:A machine learning algorithm was used to develop a predictive model of self-injury among college students and to explore the high-risk factors for self-injury among college students.Methods:From November to December 2022, a convenience sample of 791 college students from a university in Hebei Province was selected.Whether the self-injurious behavior occurred or not was regarded as an outcome variable.The basic demographics data were collected for statistical analysis.The adolescent self-harm questionnaire, the acquired helplessness scale, the Chinese version of the interpersonal needs questionnaire, the adolescent life events scale, and the childhood traumatic experiences questionnaire were used for assessment.The predictor variables were statistically analyzed by SPSS 26.0 software, and the performance of the model was evaluated by random forest, support vector machine and logistic regression so as to predict the self-injury behavior of college students.The model performance was evaluated by the accuracy, F1 score, sensitivity, specificity, and AUC value of the model, and the optimal model was selected.Finally, the optimal model was used to analyze the high-risk factors of college students' self-injury behaviors.Results:(1) The results of one-way ANOVA showed that the detection rate of self-injury behavior among college students was 42.4%(335/791), and the detection rate of male students was significantly higher than that of female students ( χ2=14.139, P<0.05). Individuals with lower-middle monthly household income(RMB 3 000-5 999) had a significantly higher detection rate of self-injury behavior than those with other monthly household income( P<0.05). (2) The accuracy of random forest, support vector machine, and logistic regression models were 85.53%, 85.96%, and 68.86%, F1 scores were 0.853, 0.864, and 0.676, and sensitivities were 83.91%, 89.04%, and 64.91%, respectively.The AUCs of support vector machine, logistic regression models and random forest were 0.89, 0.73 and 0.92.(3) The top ten characteristic variables of high risk factors for college students' self-injury behaviors based on the random forest algorithm with better predictive efficacy were emotional abuse, frustration of belonging, helplessness, interpersonal relationship factor, despair, emotional neglect, academic stress factor, monthly family income, perception of tiredness, and health adaptation factor, in that order. Conclusions:Random forest is optimal for predicting self-injury behavior among college students compared to support vector machine and logistic regression.Factors influencing self-injury behavior among college students originate from environmental factors, individual factors and interpersonal factors.