Background/Aims: Fatty liver disease is defined as a cluster of diseases with heterogeneous etiologies, and its definition continues to evolve. The novel conceptional criteria for metabolic dysfunction-associated fatty liver disease (MAFLD) were proposed in 2020 to avoid the exclusion of a certain subpopulation, but their evaluations have been limited. We aimed to examine and compare the clinical as well as histologic features of MAFLD versus nonalcoholic fatty liver disease (NAFLD) in patients with biopsy-proven hepatic steatosis. Methods: From January 2009 to December 2019, 175 patients with histology-proven hepatic steatosis and 10 with cryptogenic cirrhosis who were treated at National Taiwan University Hospital, Taipei, Taiwan, were enrolled. Patients were classified into different groups according to the diagnostic criteria of MAFLD and NAFLD. The clinical and histologic features were then analyzed and compared. Results: In total, 76 patients (41.1%) were diagnosed with both MAFLD and NAFLD, 81 patients (43.8%) were diagnosed with MAFLD alone, nine patients (4.9%) were diagnosed with NAFLD alone, and 19 patients (10.3%) were diagnosed with neither. Those with MAFLD alone exhibited a higher degree of disease severity regarding histology and laboratory data than those with NAFLD alone. Advanced fibrosis was associated with the presences of hepatitis B virus infection and metabolic diseases. Conclusions The novel diagnostic criteria for MAFLD include an additional 38.9% of patients with hepatic steatosis and can better help identify those with a high degree of disease severity for early intervention than can the previous NAFLD criteria.

Background/Aims: Fatty liver disease is defined as a cluster of diseases with heterogeneous etiologies, and its definition continues to evolve. The novel conceptional criteria for metabolic dysfunction-associated fatty liver disease (MAFLD) were proposed in 2020 to avoid the exclusion of a certain subpopulation, but their evaluations have been limited. We aimed to examine and compare the clinical as well as histologic features of MAFLD versus nonalcoholic fatty liver disease (NAFLD) in patients with biopsy-proven hepatic steatosis. Methods: From January 2009 to December 2019, 175 patients with histology-proven hepatic steatosis and 10 with cryptogenic cirrhosis who were treated at National Taiwan University Hospital, Taipei, Taiwan, were enrolled. Patients were classified into different groups according to the diagnostic criteria of MAFLD and NAFLD. The clinical and histologic features were then analyzed and compared. Results: In total, 76 patients (41.1%) were diagnosed with both MAFLD and NAFLD, 81 patients (43.8%) were diagnosed with MAFLD alone, nine patients (4.9%) were diagnosed with NAFLD alone, and 19 patients (10.3%) were diagnosed with neither. Those with MAFLD alone exhibited a higher degree of disease severity regarding histology and laboratory data than those with NAFLD alone. Advanced fibrosis was associated with the presences of hepatitis B virus infection and metabolic diseases. Conclusions The novel diagnostic criteria for MAFLD include an additional 38.9% of patients with hepatic steatosis and can better help identify those with a high degree of disease severity for early intervention than can the previous NAFLD criteria.

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.

There is growing evidence that the coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is associated with increased risks of psychiatric sequelae. Depression, anxiety, cognitive impairments, sleep disturbance, and fatigue during and after the acute phase of COVID-19 are prevalent, long-lasting, and exerting negative consequences on well-being and imposing a huge burden on healthcare systems and society. This current review presented timely updates of clinical research findings, particularly focusing on the pathogenetic mechanisms underlying the neuropsychiatric sequelae, and identified potential key targets for developing effective treatment strategies for long COVID. In addition, we introduced the Formosa Long COVID Multicenter Study (FOCuS), which aims to apply the inflammation theory to the pathogenesis and the psychosocial and nutrition treatments of post-COVID depression and anxiety.

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: 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/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.

In Taiwan, high-risk patients have been identified and tested for preventing community spread of COVID-19. Most sample collection was performed in emergency departments (EDs). Traditional sample collection requires substantial personal protective equipment (PPE), healthcare professionals, sanitation workers, and isolation space. To solve this problem, we established a multifunctional sample collection station (MSCS) for COVID-19 testing in front of our ED. The station is composed of a thick and clear acrylic board (2 cm), which completely separates the patient and medical personnel. Three pairs of gloves (length, 45 cm) are attached and fixed on the outside wall of the MSCS. The gloves are used to conduct sampling of throat/nasal swabs, sputum, and blood from patients. The gap between the board and the building is only 0.2 cm (sealed with silicone sealant). ED personnel communicate with patients using a small two-way broadcast system. Medical waste is put in specific trashcans installed in the table outside the MSCS. With full physical protection, the personnel conducting the sampling procedure need to wear only their N95 mask and gloves. After we activated the station, our PPE, sampling time, and sanitization resources were considerably conserved during the 4-week observation period. The MSCS obviously saved time and PPE. It elevated the efficiency and capacity of the ED for handling potential community infections of COVID-19.
Betacoronavirus ; Clinical Laboratory Techniques ; Coronavirus Infections ; diagnosis ; epidemiology ; Emergency Service, Hospital ; organization & administration ; Humans ; Mass Screening ; methods ; Pandemics ; Personal Protective Equipment ; supply & distribution ; Pneumonia, Viral ; diagnosis ; epidemiology ; Taiwan ; epidemiology