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 PM_2.5, 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 PM_2.5, 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. PM_2.5, 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.
Humans ; Nitrogen Dioxide ; Cross-Sectional Studies ; Air Pollution/analysis* ; Air Pollutants/analysis* ; Particulate Matter/analysis* ; Liver Diseases ; Environmental Exposure/analysis*

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.

Background/Aims: The performance of machine learning (ML) in predicting the outcomes of patients with hepatocellular carcinoma (HCC) remains uncertain. We aimed to develop risk scores using conventional methods and ML to categorize early-stage HCC patients into distinct prognostic groups. Methods: The study retrospectively enrolled 1,411 consecutive treatment-naïve patients with the Barcelona Clinic Liver Cancer (BCLC) stage 0 to A HCC from 2012 to 2021. The patients were randomly divided into a training cohort (n=988) and validation cohort (n=423). Two risk scores (CATS-IF and CATS-INF) were developed to predict overall survival (OS) in the training cohort using the conventional methods (Cox proportional hazards model) and ML-based methods (LASSO Cox regression), respectively. They were then validated and compared in the validation cohort. Results: In the training cohort, factors for the CATS-IF score were selected by the conventional method, including age, curative treatment, single large HCC, serum creatinine and alpha-fetoprotein levels, fibrosis-4 score, lymphocyte-tomonocyte ratio, and albumin-bilirubin grade. The CATS-INF score, determined by ML-based methods, included the above factors and two additional ones (aspartate aminotransferase and prognostic nutritional index). In the validation cohort, both CATS-IF score and CATS-INF score outperformed other modern prognostic scores in predicting OS, with the CATSINF score having the lowest Akaike information criterion value. A calibration plot exhibited good correlation between predicted and observed outcomes for both scores. Conclusions Both the conventional Cox-based CATS-IF score and ML-based CATS-INF score effectively stratified patients with early-stage HCC into distinct prognostic groups, with the CATS-INF score showing slightly superior performance.

OBJECTIVES: Information regarding the underlying causes of death (UCODs) and standardized mortality ratio (SMR) of dementia is instrumental in formulating medical strategies to prolong life in persons with dementia (PWD). We examined the leading UCODs among PWD and estimated the overall and cause-specific SMRs in relation to dementia in Taiwan. METHODS: Data were retrieved from 2 national datasets: the Taiwan Death Registry and the medical claim datasets of the National Health Insurance program. The observed person-years for each study participant were counted from the date of cohort enrollment to either the date of death or the final day of 2016. Sex-specific and age-specific SMRs were then calculated. RESULTS: The leading UCOD was circulatory disease, accounting for 26.0% of total deaths (n=3,505), followed by respiratory disease at 21.3% (n=2,875). PWD were at significantly increased risk of all-cause mortality (SMR, 2.01), with SMR decreasing with advancing age. A cause-specific analysis revealed that the highest SMRs were associated with nervous system diseases (SMR, 7.58) and mental, behavioral, and neurodevelopmental disorders (SMR, 4.80). Age appeared to modify SMR, suggesting that younger age at cohort enrollment was linked to higher SMRs for nearly all causes of mortality. CONCLUSIONS Circulatory and respiratory diseases were the leading UCODs among PWD. The particularly elevated mortality due to nervous system diseases and mental disorders suggests that allocating more resources to neurological and psychiatric services is warranted. The elevated SMRs of various UCODs among younger PWD underscore the need for clinicians to pay particular attention to the medical care provided to these patients.

Nutrition information on food labels guides consumers to purchase healthier food choices. Besides nutrition information, other factors influence a purchase. This study aims to determine the association between the knowledge, attitude, and practice (KAP) among tertiary students on nutrition and food labels. In this cross-sectional study, a total of 190 students from three tertiary institutions within Klang Valley completed an online survey. Self-administered questionnaires on sociodemographic profiles and KAP questions, available in Malay and English, were distributed. Association between KAP was determined using Spearman's Rho test, while multiple linear regression was used to assess predictors of KAP scores. Mean body mass index (BMI) of the respondents were 20.8 kg/m2. The total mean score for knowledge on food labels was 8.93, followed by attitude and practice with 3.86 and 3.11, respectively. There was a significant correlation between attitude and practice (p<0.005). Nutrient and total calorie information on food labels influenced purchases, with 56.3% of respondents reported looking at the total calorie content, followed by 55.7% and 49.5% checking on sugar and fats, respectively. In addition, other factors such as expiry date (60.9%) and price (59.9%) also influenced purchases. Overall, respondents have a positive attitude on food selection, but male respondents have better knowledge levels than females. However, female respondents interpret food labelling effectively compared to male respondents. Despite having good knowledge and attitude towards nutrition, respondents were still making poor choices. A more extensive range of healthier food options and targeted healthy eating campaigns may empower students to choose more nutritious foods.

Background/Aims: Real-world studies assessing the effectiveness and safety of sofosbuvir/velpatasvir (SOF/VEL) plus ribavirin (RBV) for Child-Pugh B/C hepatitis C virus (HCV)-related cirrhosis are limited. Methods: We included 107 patients with Child-Pugh B/C HCV-related cirrhosis receiving SOF/VEL plus RBV for 12 weeks in Taiwan. The sustained virologic response rates at off-treatment week 12 (SVR12) for the evaluable population (EP), modified EP, and per-protocol population (PP) were assessed. Thesafety profiles were reported. Results: The SVR12 rates in the EP, modified EP and PP were 89.7% (95% confidence interval [CI], 82.5–94.2%), 94.1% (95% CI, 87.8–97.3%), and 100% (95% CI, 96.2–100%). Number of patients who failed to achieve SVR12 were attributed to virologic failures. The SVR12 rates were comparable regardless of patient characteristics. One patient discontinued treatment because of adverse events (AEs). Twenty-four patients had serious AEs and six died, but none were related to SOF/VEL or RBV. Among the 96 patients achieving SVR12, 84.4% and 64.6% had improved Child-Pugh and model for endstage liver disease (MELD) scores. Multivariate analysis revealed that a baseline MELD score ≥15 was associated with an improved MELD score of ≥3 (odds ratio, 4.13; 95% CI, 1.16–14.71; P=0.02). Patients with chronic kidney disease (CKD) stage 1 had more significant estimated glomerular filtration rate declines than patients with CKD stage 2 (-0.42 mL/min/1.73 m2/month; P=0.01) or stage 3 (-0.56 mL/min/1.73 m2/month; P<0.001). Conclusions SOF/VEL plus RBV for 12 weeks is efficacious and well-tolerated for Child-Pugh B/C HCV-related cirrhosis.

Background/Aims: Real-world studies assessing the effectiveness and safety of sofosbuvir/velpatasvir (SOF/VEL) plus ribavirin (RBV) for Child-Pugh B/C hepatitis C virus (HCV)-related cirrhosis are limited. Methods: We included 107 patients with Child-Pugh B/C HCV-related cirrhosis receiving SOF/VEL plus RBV for 12 weeks in Taiwan. The sustained virologic response rates at off-treatment week 12 (SVR12) for the evaluable population (EP), modified EP, and per-protocol population (PP) were assessed. Thesafety profiles were reported. Results: The SVR12 rates in the EP, modified EP and PP were 89.7% (95% confidence interval [CI], 82.5–94.2%), 94.1% (95% CI, 87.8–97.3%), and 100% (95% CI, 96.2–100%). Number of patients who failed to achieve SVR12 were attributed to virologic failures. The SVR12 rates were comparable regardless of patient characteristics. One patient discontinued treatment because of adverse events (AEs). Twenty-four patients had serious AEs and six died, but none were related to SOF/VEL or RBV. Among the 96 patients achieving SVR12, 84.4% and 64.6% had improved Child-Pugh and model for endstage liver disease (MELD) scores. Multivariate analysis revealed that a baseline MELD score ≥15 was associated with an improved MELD score of ≥3 (odds ratio, 4.13; 95% CI, 1.16–14.71; P=0.02). Patients with chronic kidney disease (CKD) stage 1 had more significant estimated glomerular filtration rate declines than patients with CKD stage 2 (-0.42 mL/min/1.73 m2/month; P=0.01) or stage 3 (-0.56 mL/min/1.73 m2/month; P<0.001). Conclusions SOF/VEL plus RBV for 12 weeks is efficacious and well-tolerated for Child-Pugh B/C HCV-related cirrhosis.

BACKGROUND AND PURPOSE: Preceding episodes of paroxysmal atrial fibrillation (AF) among stroke patients can be easily overlooked in routine clinical practice. We aim to determine whether an unrecognized history of paroxysmal AF is associated with an increased risk of recurrent stroke. METHODS: We retrospectively identified all adult patients hospitalized with a primary diagnosis of ischemic stroke who had no AF diagnosis on their discharge records, using the Taiwan National Health Insurance Research Database between January 2001 and December 2012. Patients were categorized into two groups: unrecognized AF history and no AF. Patients with unrecognized AF history were defined as having documented AF preceding the index ischemic stroke hospitalization, but not recording at the index ischemic stroke. Primary endpoint was recurrent stroke within 1 year after the index stroke. RESULTS: Among 203,489 hospitalized ischemic stroke patients without AF diagnosed at discharge, 6,731 patients (3.3%) had an unrecognized history of prior transient AF. Patients with an unrecognized AF history, comparing to those without AF, had higher adjusted risk of all recurrent stroke ([original cohort: hazard ratio (HR), 1.41; 95% confidence interval [CI], 1.30 to 1.53], [matched cohort: HR, 1.51; 95% CI, 1.37 to 1.68]) and recurrent ischemic stroke ([original cohort: HR, 1.42; 95% CI, 1.30 to 1.55], [matched cohort: HR, 1.56; 95% CI, 1.40 to 1.74]) during the 1-year follow-up period. CONCLUSIONS: Unrecognized history of AF among patients discharged after an index ischemic stroke hospitalization is associated with higher recurrent stroke risk. Careful history review to uncover a paroxysmal AF history is important for ischemic stroke patients.
Adult ; Atrial Fibrillation ; Brain Infarction ; Cohort Studies ; Diagnosis ; Follow-Up Studies ; Hospitalization ; Humans ; Medical Records ; National Health Programs ; Retrospective Studies ; Stroke ; Taiwan