1.Influence of atrial septal defect on mitral valve growth after repair of coarctation of the aorta or an interrupted aortic arch in infants
Yi-Chia WANG ; Heng-Wen CHOU ; Chi-Hsiang HUANG ; Hsing-Hao HUANG ; Yih-Sharng CHEN ; En-Ting WU ; Shyh-Jye CHEN ; Ming-Tai LIN ; Shuenn-Nan CHIU ; Shu-Chien HUANG
Clinical and Experimental Pediatrics 2026;69(4):322-329
Background:
Patients with coarctation of the aorta (CoA) and an interrupted aortic arch (IAA) may present with small mitral valves (MVs) and a reduced left ventricular (LV) volume. Biventricular repair (BVR) in these patients is dependent on adequate size of the left cardiac structures.Purpose: This study evaluated the impact of the hemodynamic characteristics of atrial septal defects (ASDs) on MV growth following surgical repair.
Methods:
We retrospectively reviewed the data of patients diagnosed with CoA or IAA between 2007 and 2024. The z score for MV size measured 6 months postoperatively (Z2) was compared with the preoperative MV size (Z1). The factors associated with MV growth were also studied.
Results:
A total of 161 patients with CoA or IAA were included. Transthoracic echocardiography was used to assess the MV and LV dimensions preoperatively and 6 months postoperatively. Of the cohort, 155 (96.3%) underwent initial BVR and 6 underwent single-ventricle palliation. MV z scores significantly increased following BVR (mean change: +0.45±1.35; P<0.001) but decreased after single-ventricle repair (-0.56±0.49, P=0.04). Multivariate analysis identified the initial MV z score and ASD pressure gradient as independent predictors of MV growth (R2=0.39).
Conclusion
Annular growth of the MV was not observed in patients who underwent single-ventricle palliation. In contrast, among patients who achieved BVR, those with a small preoperative MV annulus and low ASD pressure gradient demonstrated subsequent catch-up MV growth, suggesting that adequate left-sided preload is essential for MV development.
2.Corporate Governance and Workplace Mental Health Practices: The Mediating Role of Structured Occupational Safety and Health Engagement
Ro-Ting LIN ; Lung-Chang CHIEN ; Chieh-Wen CHANG ; Yu-Chi LIAO ; Tomohisa NAGATA
Safety and Health at Work 2026;17(1):33-39
Background:
This study examines whether stronger corporate governance is associated with workplace mental health practices and whether this relationship is mediated by a structured sequence of occupational safety and health (OSH) engagement: recognition, goal-setting, and implementation.
Methods:
We analyzed 134 listed companies in Taiwan that published sustainability reports and received corporate governance evaluations between 2014 and 2023. Governance scores―based on shareholder rights, board functioning, transparency, and sustainability―were dichotomized into high vs. low categories. Workplace mental health practices were measured using 24 binary indicators across planning, provision, and reporting. OSH engagement was conceptualized in three stages based on Global Reporting Initiative 403 guidelines, with composite indicators derived via grouped weighted quantile sum regression. Associations were analyzed using generalized linear mixed-effects and serial mediation models.
Results:
Compared to companies ranked low in corporate governance, those ranked high had a higher likelihood of adopting mental health practices. OSH goal-setting and implementation showed significant positive associations, whereas recognition did not. Serial mediation analysis showed that 83% of the total effect of corporate governance on mental health practices was direct, while 17% was mediated through structured OSH engagement, primarily via implementation. Recognition showed a nonsignificant effect but initiated significant sequential pathways via goal-setting and implementation.Goal-setting functioned as a bridge within these chains.
Conclusion
Corporate governance plays a central role in advancing workplace mental health practices.While most effects are direct, structured OSH engagement helps translate governance priorities into sustained organizational actions that embed mental health into routine practice.
3.Artificial intelligence predicts direct-acting antivirals failure among hepatitis C virus patients: A nationwide hepatitis C virus registry program
Ming-Ying LU ; Chung-Feng HUANG ; Chao-Hung HUNG ; Chi‐Ming TAI ; Lein-Ray MO ; Hsing-Tao KUO ; Kuo-Chih TSENG ; Ching-Chu LO ; Ming-Jong BAIR ; Szu-Jen WANG ; Jee-Fu HUANG ; Ming-Lun YEH ; Chun-Ting CHEN ; Ming-Chang TSAI ; Chien-Wei HUANG ; Pei-Lun LEE ; Tzeng-Hue YANG ; Yi-Hsiang HUANG ; Lee-Won CHONG ; Chien-Lin CHEN ; Chi-Chieh YANG ; Sheng‐Shun YANG ; Pin-Nan CHENG ; Tsai-Yuan HSIEH ; Jui-Ting HU ; Wen-Chih WU ; Chien-Yu CHENG ; Guei-Ying CHEN ; Guo-Xiong ZHOU ; Wei-Lun TSAI ; Chien-Neng KAO ; Chih-Lang LIN ; Chia-Chi WANG ; Ta-Ya LIN ; Chih‐Lin LIN ; Wei-Wen SU ; Tzong-Hsi LEE ; Te-Sheng CHANG ; Chun-Jen LIU ; Chia-Yen DAI ; Jia-Horng KAO ; Han-Chieh LIN ; Wan-Long CHUANG ; Cheng-Yuan PENG ; Chun-Wei- TSAI ; Chi-Yi CHEN ; Ming-Lung YU ;
Clinical and Molecular Hepatology 2024;30(1):64-79
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.
4.Impact of Interleukin-10 Gene Polymorphisms on Survival in Patients with Colorectal Cancer.
Wen Chien TING ; Lu Min CHEN ; Li Chia HUANG ; Mann Jen HOUR ; Yu Hsuan LAN ; Hong Zin LEE ; Bang Jau YOU ; Ta Yuan CHANG ; Bo Ying BAO
Journal of Korean Medical Science 2013;28(9):1302-1306
Chronic inflammation is thought to be the leading cause of colorectal cancer, and interleukin-10 (IL10) has been identified as a potent immunomodulatory cytokine that regulates inflammatory responses in the gastrointestinal tract. Although several single nucleotide polymorphisms (SNPs) in IL10 have been associated with the risk of colorectal cancer, their prognostic significance has not been determined. Two hundred and eighty-two colorectal cancer patients were genotyped for two candidate cancer-associated SNPs in IL10. The associations of these SNPs with distant metastasis-free survival and overall survival were evaluated by Kaplan-Meier analysis and Cox regression model. The minor homozygote GG genotype of IL10 rs3021094 was significantly associated with a 3.30-fold higher risk of death compared with the TT+TG genotypes (P=0.011). The patients with IL10 rs3021094 GG genotype also had a poorer overall survival in Kaplan-Meier analysis (log-rank P=0.007) and in multivariate Cox regression model (P=0.044) adjusting for age, gender, carcinoembryonic antigen levels, tumor differentiation, stage, lymphovascular invasion, and perineural invasion. In conclusion, our results suggest that IL10 rs3021094 might be a valuable prognostic biomarker for colorectal cancer patients.
Aged
;
Alleles
;
Carcinoembryonic Antigen/blood
;
Cell Differentiation
;
Colorectal Neoplasms/*genetics/mortality/pathology
;
Female
;
Genotype
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Homozygote
;
Humans
;
Interleukin-10/*genetics
;
Kaplan-Meier Estimate
;
Lymphatic Metastasis
;
Male
;
Middle Aged
;
Neoplasm Staging
;
*Polymorphism, Single Nucleotide
;
Regression Analysis
;
Tumor Markers, Biological/genetics

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