1.Relationship between the FRAX® score and falls in community-dwelling middle-aged and elderly people.
Ling Chun OU ; Yin Fan CHANG ; Chin Sung CHANG ; Ting Hsing CHAO ; Ruey Mo LIN ; Zih Jie SUN ; Chih Hsing WU
Osteoporosis and Sarcopenia 2016;2(4):221-227
OBJECTIVES: Falls is a risk factor for fracture. The FRAX® predicts fractures. Whether the FRAX® is associated with fall in both gender is inconclusive. The aim of our study is to evaluate the association between FRAX scores and falls. METHODS: The cross-sectional study set from 2009 to 2010 included 1200 community-dwelling people who were systematically sampled in central Taiwan. The 1200 participants (men: 524; women: 676; ≥40 years old) completed questionnaires about socioeconomic status; lifestyle; medical and fall history were completed. FRAX scores with and without bone mineral density (BMD) were calculated by using the Taiwan calculator. RESULTS: A total of 19.8% participants fell down. Binary regression models showed that diabetes mellitus history (OR: 1.61; 95% CI: 1.03–2.52), the FRAX without BMD in a continuous major score (OR: 1.06; 95% CI: 1.03–1.09), continuous hip score (OR: 1.11; 95% CI: 1.05–1.16), categorical major score ≥ 10% (OR: 1.81; 95% CI: 1.25–2.61), and categorical hip score ≥ 3% (OR: 1.80; 95% CI: 1.30–2.50) were independent risk factors for falls. FRAX with BMD in a continuous major score (OR: 1.04; 95% CI: 1.02–1.06), continuous hip score (OR: 1.06; 95% CI: 1.02–1.09), categorical major score ≥ 10% (OR: 1.52; 95% CI: 1.09–2.12), and categorical hip score ≥ 3% (OR: 1.53; 95% CI: 1.13–2.09) were also independent risk factors. CONCLUSIONS: We concluded that FRAX® scores with and without BMD were unanimously correlated with falls in community-dwelling middle-aged and elderly males and females.
Accidental Falls*
;
Aged*
;
Bone Density
;
Cross-Sectional Studies
;
Diabetes Mellitus
;
Female
;
Hip
;
Humans
;
Life Style
;
Male
;
Risk Factors
;
Social Class
;
Taiwan
2.Epigenetic regulation in allergic diseases and related studies
Chang Hung KUO ; Chong Chao HSIEH ; Min Sheng LEE ; Kai Ting CHANG ; Hsuan Fu KUO ; Chih Hsing HUNG
Asia Pacific Allergy 2014;4(1):14-18
Asthma, a chronic inflammatory disorder of the airway, has features of both heritability as well as environmental influences which can be introduced in utero exposures and modified through aging, and the features may attribute to epigenetic regulation. Epigenetic regulation explains the association between early prenatal maternal smoking and later asthma-related outcomes. Epigenetic marks (DNA methylation, modifications of histone tails or noncoding RNAs) work with other components of the cellular regulatory machinery to control the levels of expressed genes, and several allergy- and asthma-related genes have been found to be susceptible to epigenetic regulation, including genes important to T-effector pathways (IFN-γ, interleukin [IL] 4, IL-13, IL-17) and T-regulatory pathways (FoxP3). Therefore, the mechanism by which epigenetic regulation contributes to allergic diseases is a critical issue. In the past most published experimental work, with few exceptions, has only comprised small observational studies and models in cell systems and animals. However, very recently exciting and elegant experimental studies and novel translational research works were published with new and advanced technologies investigating epigenetic mark on a genomic scale and comprehensive approaches to data analysis. Interestingly, a potential link between exposure to environmental pollutants and the occurrence of allergic diseases is revealed recently, particular in developed and industrialized countries, and endocrine disrupting chemicals (EDCs) as environmental hormone may play a key role. This review addresses the important question of how EDCs (nonylphenol, 4 octylphenol, and phthalates) influences on asthma-related gene expression via epigenetic regulation in immune cells, and how anti-asthmatic agents prohibit expression of inflammatory genes via epigenetic modification. The discovery and validation of epigenetic biomarkers linking exposure to allergic diseases might lead to better epigenotyping of risk, prognosis, treatment prediction, and development of novel therapies.
Acetylation
;
Aging
;
Animals
;
Anti-Asthmatic Agents
;
Asthma
;
Biomarkers
;
Developed Countries
;
Endocrine Disruptors
;
Environmental Pollutants
;
Epigenomics
;
Gene Expression
;
Histones
;
Hypersensitivity
;
Interleukin-13
;
Interleukins
;
Methylation
;
Prognosis
;
Smoke
;
Smoking
;
Statistics as Topic
;
Tail
;
Translational Medical Research
3.Prevalence of Enterobius vermicularis Infection among Preschool Children in Kindergartens of Taipei City, Taiwan in 2008.
Tso Kang CHANG ; Chien Wei LIAO ; Ying Chieh HUANG ; Chun Chao CHANG ; Chia Mei CHOU ; Hsin Chieh TSAY ; Alice HUANG ; Shu Fen GUU ; Ting Chang KAO ; Chia Kwung FAN
The Korean Journal of Parasitology 2009;47(2):185-187
The prevalence of Enterobius vermicularis infection among preschool children was reported to be low based on a 5-year screening program in Taipei City, Taiwan. The Taipei City government intended to terminate the E. vermicularis screening program among preschool children. Thus, we were entrusted with confirming whether pinworm infections among preschool children in Taipei City had truly declined. From each of 12 administrative districts 2-3 kindergartens were randomly selected for investigation. In total, 4,349 children were examined, of which 2,537 were boys and 1,812 were girls. The cellophane tape adhered to a glass slide was used, and all examinations were done by certified medical technologists. Results indicated that the overall prevalence rate of pinworm infections was 0.62% (27/4,349). Although the infection rate was higher among boys (0.67%, 17/2,537) than in girls (0.55%, 10/1,812), no significant difference was found (chi2 = 0.399, P = 0.62). According to the administrative district, the infection rate ranged from no positive cases of E. vermicularis infection in the Xinyi, Zhongzhen, and Wanhua Districts (0%; 0/299, 0/165, and 0/358, respectively), to 0.26% (1/131) in Songshan District, with the highest rate of 1.88% (7/373) in Wenshan District. Because the overall infection rate (0.62%, 27/4,349) in the present study was unchanged compared to that (0.40%, 197/49,541) previously reported in 2005, we propose that regular pinworm screening and treatment programs should be continued in some parts of Taipei City.
Animals
;
Child Day Care Centers
;
Child, Preschool
;
Enterobiasis/*epidemiology
;
Enterobius/*isolation & purification
;
Female
;
Humans
;
Male
;
Microscopy/methods
;
Prevalence
;
Taiwan/epidemiology
4.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
Pin-Nan CHENG ; Wen-Jone CHEN ; Charles Jia-Yin HOU ; Chih-Lin LIN ; Ming-Ling CHANG ; Chia-Chi WANG ; Wei-Ting CHANG ; Chao-Yung WANG ; Chun-Yen LIN ; Chung-Lieh HUNG ; Cheng-Yuan PENG ; Ming-Lung YU ; Ting-Hsing CHAO ; Jee-Fu HUANG ; Yi-Hsiang HUANG ; Chi-Yi CHEN ; Chern-En CHIANG ; Han-Chieh LIN ; Yi-Heng LI ; Tsung-Hsien LIN ; Jia-Horng KAO ; Tzung-Dau WANG ; Ping-Yen LIU ; Yen-Wen WU ; Chun-Jen LIU
Clinical and Molecular Hepatology 2024;30(1):16-36
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.
5.Management of ulcerative colitis in Taiwan: consensus guideline of the Taiwan Society of Inflammatory Bowel Disease updated in 2023
Hsu-Heng YEN ; Jia-Feng WU ; Horng-Yuan WANG ; Ting-An CHANG ; Chung-Hsin CHANG ; Chen-Wang CHANG ; Te-Hsin CHAO ; Jen-Wei CHOU ; Yenn-Hwei CHOU ; Chiao-Hsiung CHUANG ; Wen-Hung HSU ; Tzu-Chi HSU ; Tien-Yu HUANG ; Tsung-I HUNG ; Puo-Hsien LE ; Chun-Che LIN ; Chun-Chi LIN ; Ching-Pin LIN ; Jen-Kou LIN ; Wei-Chen LIN ; Yen-Hsuan NI ; Ming-Jium SHIEH ; I-Lun SHIH ; Chia-Tung SHUN ; Tzung-Jiun TSAI ; Cheng-Yi WANG ; Meng-Tzu WENG ; Jau-Min WONG ; Deng-Chyang WU ; Shu-Chen WEI
Intestinal Research 2024;22(3):213-249
Ulcerative colitis (UC) is a chronic inflammation of the gastrointestinal tract and is characterized by alternating periods of inflammation and remission. Although UC incidence is lower in Taiwan than in Western countries, its impact remains considerable, demanding updated guidelines for addressing local healthcare challenges and patient needs. The revised guidelines employ international standards and recent research, emphasizing practical implementation within the Taiwanese healthcare system. Since the inception of the guidelines in 2017, the Taiwan Society of Inflammatory Bowel Disease has acknowledged the need for ongoing revisions to incorporate emerging therapeutic options and evolving disease management practices. This updated guideline aims to align UC management with local contexts, ensuring comprehensive and context-specific recommendations, thereby raising the standard of care for UC patients in Taiwan. By adapting and optimizing international protocols for local relevance, these efforts seek to enhance health outcomes for patients with UC.
6.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.