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.

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.

OBJECTIVES: To investigate the clinical treatment outcomes and the changes of the outcomes over time in extremely preterm twins in Guangdong Province, China. METHODS: A retrospective analysis was performed for 269 pairs of extremely preterm twins with a gestational age of <28 weeks who were admitted to the department of neonatology in 26 grade A tertiary hospitals in Guangdong Province from January 2008 to December 2017. According to the admission time, they were divided into two groups: 2008-2012 and 2013-2017. Besides, each pair of twins was divided into the heavier infant and the lighter infant subgroups according to birth weight. The perinatal data of mothers and hospitalization data of neonates were collected. The survival rate of twins and the incidence rate of complications were compared between the 2008-2012 and 2013-2017 groups. RESULTS: Compared with the 2008-2012 group, the 2013-2017 group (both the heavier infant and lighter infant subgroups) had lower incidence rates of severe asphyxia and smaller head circumference at birth (P<0.05). The mortality rates of both of the twins, the heavier infant of the twins, and the lighter infant of the twins were lower in the 2013-2017 group compared with the 2008-2012 group (P<0.05). Compared with the 2008-2012 group, the 2013-2017 group (both the heavier infant and lighter infant subgroups) had lower incidence rates of pulmonary hemorrhage, patent ductus arteriosus (PDA), periventricular-intraventricular hemorrhage (P-IVH), and neonatal respiratory distress syndrome (NRDS) and a higher incidence rate of bronchopulmonary dysplasia (P<0.05). CONCLUSIONS There is a significant increase in the survival rate over time in extremely preterm twins with a gestational age of <28 weeks in the 26 grade A tertiary hospitals in Guangdong Province. The incidences of severe asphyxia, pulmonary hemorrhage, PDA, P-IVH, and NRDS decrease in both the heavier and lighter infants of the twins, but the incidence of bronchopulmonary dysplasia increases. With the improvement of diagnosis and treatment, the multidisciplinary collaboration between different fields of fetal medicine including prenatal diagnosis, obstetrics, and neonatology is needed in the future to jointly develop management strategies for twin pregnancy.
Bronchopulmonary Dysplasia/epidemiology* ; Female ; Gestational Age ; Humans ; Infant ; Infant, Extremely Premature ; Infant, Newborn ; Pregnancy ; Respiratory Distress Syndrome, Newborn/epidemiology* ; Retrospective Studies ; Treatment Outcome

Objective: To describe gastric cancer incidence in Suzhou cohort, explore the environmental risk factors of gastric cancer in Suzhou, and provide appropriate suggestions for gastric cancer prevention and control. Methods: The participants were from the Suzhou cohort of China Kadoorie Biobank. Baseline survey was conducted from 2004 to 2008, followed by long-term follow-up until December 31, 2013. After the exclusion of those who had been previously diagnosed with peptic ulcer and malignant tumor reported at baseline survey and gastric cancer within six months after enrollment, a total of 50,136 participants were included. Cox proportional risk models were used to identify risk factors of gastric cancer and their hazard ratios in Suzhou. The effect modifications of gender on the association between risk factors and gastric cancer were analyzed. Results: In the follow-up of 7.19 years (median), 374 gastric cancers cases occurred. The standardized incidence was 94.57 per 100 000 person-years. Multivariate Cox proportional risk model analysis found that age (10 years old as a age group, HR=2.20, 95%CI: 1.92-2.53, P<0.001), current smoking (HR=1.84, 95%CI: 1.10-3.07 P=0.020), consumption of preserved vegetables weekly (HR=2.28, 95%CI: 1.28-4.07, P=0.005) and daily (HR=2.05, 95%CI: 1.16-3.61, P=0.013) were risk factors for gastric cancer. Female (HR=0.44, 95%CI: 0.25-0.76, P=0.003) and refrigerator use (10 years as a limit, HR=0.85, 95%CI: 0.74-0.97, P=0.016) were protective factors for gastric cancer. Further analysis showed that there was heterogeneity between males and females in the association between refrigerator use years and the incidence of gastric cancer (P=0.009), and there was an interaction effect between gender and refrigerator use on the incidence of gastric cancer (P=0.010). Conclusions: The incidence of gastric cancer in Suzhou cohort was high. The risk factors of gastric cancer varied. There was a synergistic interaction effect between gender and refrigerator use years on the incidence of gastric cancer.
Child ; Cohort Studies ; Female ; Humans ; Incidence ; Male ; Proportional Hazards Models ; Prospective Studies ; Risk Factors ; Stomach Neoplasms/epidemiology*

OBJECTIVES: To study the early clinical efficacy of combined therapy of stage 4 neuroblastoma. METHODS: A retrospective analysis was performed on the medical data and follow-up data of 14 children with stage 4 neuroblastoma who were diagnosed in Hong Kong University-Shenzhen Hospital from January 2016 to June 2021. RESULTS: The median age of onset was 3 years and 7.5 months in these 14 children. Among these children, 9 had positive results of bone marrow biopsy, 4 had N-Myc gene amplification, 13 had an increase in neuron-specific enolase, and 7 had an increase in vanilmandelic acid in urine. Based on the results of pathological examination, differentiated type was observed in 6 children, undifferentiated type in one child, mixed type, in one child and poorly differentiated type in 6 children. Of all the children, 10 received chemotherapy with the N7 regimen (including 2 children receiving arsenic trioxide in addition) and 4 received chemotherapy with the Rapid COJEC regimen. Thirteen children underwent surgery, 14 received hematopoietic stem cell transplantation, and 10 received radiotherapy. A total of 8 children received Ch14.18/CHO immunotherapy, among whom 1 child discontinued due to anaphylactic shock during immunotherapy, and the other 7 children completed Ch14.18/CHO treatment without serious adverse events, among whom 1 child was treated with Lu177 Dotatate 3 times after recurrence and is still undergoing chemotherapy at present. The median follow-up time was 45 months for all the 14 children. Four children experienced recurrence within 2 years, and the 2-year overall survival rate was 100%; 4 children experienced recurrence within 3 years, and 7 achieved disease-free survival within 3 years. CONCLUSIONS Multidisciplinary combined therapy is recommended for children with stage 4 neuroblastoma and can help them achieve better survival and prognosis.
Antineoplastic Combined Chemotherapy Protocols/therapeutic use* ; Child ; Child, Preschool ; Combined Modality Therapy ; Humans ; Infant ; Neuroblastoma/drug therapy* ; Positron-Emission Tomography ; Radionuclide Imaging ; Retrospective Studies ; Treatment Outcome

Background/Aims: Direct‐acting antivirals (DAAs) have been approved for hepatitis C virus (HCV) treatment in patients with end-stage renal disease (ESRD) on hemodialysis. Nevertheless, the complicated comedications and their potential drug-drug interactions (DDIs) with DAAs might limit clinical practice in this special population. Methods: The number, class, and characteristics of comedications and their potential DDIs with five DAA regimens were analyzed among HCV-viremic patients from 23 hemodialysis centers in Taiwan. Results: Of 2,015 hemodialysis patients screened in 2019, 169 patients seropositive for HCV RNA were enrolled (mean age, 65.6 years; median duration of hemodialysis, 5.8 years). All patients received at least one comedication (median number, 6; mean class number, 3.4). The most common comedication classes were ESRD-associated medications (94.1%), cardiovascular drugs (69.8%) and antidiabetic drugs (43.2%). ESRD-associated medications were excluded from DDI analysis. Sofosbuvir/velpatasvir/voxilaprevir had the highest frequency of potential contraindicated DDIs (red, 5.6%), followed by glecaprevir/pibrentasvir (4.0%), sofosbuvir/ledipasvir (1.3%), sofosbuvir/velpatasvir (1.3%), and elbasvir/grazoprevir (0.3%). For potentially significant DDIs (orange, requiring close monitoring or dose adjustments), sofosbuvir/velpatasvir/voxilaprevir had the highest frequency (19.9%), followed by sofosbuvir/ledipasvir (18.2%), glecaprevir/pibrentasvir (12.6%), sofosbuvir/velpatasvir (12.6%), and elbasvir/grazoprevir (7.3%). Overall, lipid-lowering agents were the most common comedication class with red-category DDIs to all DAA regimens (n=62), followed by cardiovascular agents (n=15), and central nervous system agents (n=10). Conclusions HCV-viremic patients on hemodialysis had a very high prevalence of comedications with a broad spectrum, which had varied DDIs with currently available DAA regimens. Elbasvir/grazoprevir had the fewest potential DDIs, and sofosbuvir/velpatasvir/voxilaprevir had the most potential DDIs.

Metabolomics, which inherits the ideas of genomics and proteomics, has been widely applied in clinical medical research. In the field of kidney transplantation, changes, which occur in the concentration of small molecule metabolites in blood or urine, can be used to identify organs at risk of acute rejection, locate organ damage, and monitor graft function. This article reviews the problems in the field of kidney transplantation, the concepts, characteristics and research methods of metabolomics, as well as the progress in the application of kidney transplantation and the biomarkers that have been discovered.

BACKGROUND: Resting heart rate (RHR) is considered as a strong predictor of total mortality and hospitalization due to heart failure in hypertension patients. Bisoprolol fumarate, a second-generation beta-adrenoreceptor blockers (β-blocker) is commonly prescribed drug to manage hypertension. The present study was to retrospectively evaluate changes in the average RHR and its association with cardiovascular outcomes in bisoprolol-treated coronary artery disease (CAD) patients from the CAD treated with bisoprolol (BISO-CAD) study who had comorbid hypertension. METHODS: We performed ad-hoc analysis for hypertension sub-group of the BISO-CAD study (n = 866), which was a phase IV, multination, multi-center, single-arm, observational study carried out from October 2011 to July 2015 across China, South Korea, and Vietnam. Multivariate regression analysis was used to identify factors associated with incidence of composite cardiac clinical outcome (CCCO), the results were presented as adjusted odds ratio (OR) along with 95% confidence interval (CI) and adjusted P value. RESULTS: A total of 681 patients (mean age: 64.77 ± 10.33 years) with hypertension from BISO-CAD study were included in the analysis. Bisoprolol improved CCCOs in CAD patients with comorbid hypertension, with RHR <65 and <70 beats/min compared with RHR ≥65 and ≥75 beats/min, respectively, in the efficacy analysis (EA) set. In addition, it lowered RHR in both intent-to-treat (ITT) and EA groups after 6, 12, and 18 months of treatment. Further, RHR 70 to 74 beats/min resulted in significantly higher risk of CCCOs EA set of patients (adjusted OR: 4.34; 95% CI: 1.19-15.89; P = 0.03). Also, events of hospitalization due to acute coronary syndrome were higher when RHR 69 to 74 beats/min compared to RHR <69 beats/min in ITT patients. CONCLUSION Bisoprolol can effectively reduce RHR in Asian CAD patients with comorbid hypertension and hence, improve CCCO without affecting their blood pressure.

OBJECTIVE: To compare clinical effect of dynamic locking screws and common screws in treating humeral shaft fractures. METHODS: From January 2016 to October 2018, clinical data of 46 patients with humeral shaft fracture were retrospectively analyzed, which were divided into dynamic locking screw internal fixation group (treatment group) and ordinary screw internal fixation group (control group). In treatment group, there were 14 males and 10 females, aged from 20 to 61 years old with an average of (36.8±10.9) years old;22 patients in control group, there were 13 males and 9 females, aged from 19 to 60 years old with an average of (35.9±12.8) years old. Length of incision, operation time, amount of bleeding, fracture healing time and complications were compared between two groups, Constant-Murley score of shoulder joint and Mayo score of elbow joint at 3 and 9 months after operation were compared to evaluate clinical effect. RESULTS: Forty six patients were followed up from 9 to 43 months with an average of (18.6±7.9) months. There were no statistical differences in length of incision, operation time, amount of bleeding between two groups (>0.05);fracture healing time in treatment group was (12.2±3.2) weeks, and (15.6±4.7) weeks in control group;there was difference between two groups (<0.05). Constant-Murley score and Mayo score of elbow joint at 3 months after operation in treatment group were 84.9±5.9 and 81.8±6.7, while in control group were 74.6±9.2 and 71.5±10.7;there were differences between two groups (<0.05). There were no statistical differences in Constant-Murley score and Mayo score of elbow joint between two groups at 9 months after operation (>0.05);One patient occurred neural paralysis in treatment group;1 patient occurred delayedunion, 2 patients occurred bone nonunion and 1 patient occurred broken nail in control group;while there was no statistical difference between two groups in complication. CONCLUSION Both of dynamic locking screws and ordinary screws could effectively treat humeral shaft fractures. dynamic locking screws has an advantage in fracture healing time, and recovery of early shoulder and elbow function. However, the active time of this technology is not too long in China, further study on long-term efficacy of large samples is needed.
Adult ; Bone Plates ; Bone Screws ; China ; Female ; Fracture Fixation, Internal ; Humans ; Humeral Fractures ; Humerus ; Male ; Middle Aged ; Retrospective Studies ; Treatment Outcome ; Young Adult

Brain science accelerates the study of intelligence and behavior, contributes fundamental insights into human cognition, and offers prospective treatments for brain disease. Faced with the challenges posed by imaging technologies and deep learning computational models, big data and high-performance computing (HPC) play essential roles in studying brain function, brain diseases, and large-scale brain models or connectomes. We review the driving forces behind big data and HPC methods applied to brain science, including deep learning, powerful data analysis capabilities, and computational performance solutions, each of which can be used to improve diagnostic accuracy and research output. This work reinforces predictions that big data and HPC will continue to improve brain science by making ultrahigh-performance analysis possible, by improving data standardization and sharing, and by providing new neuromorphic insights.