Background/Aims: Endoscopic ultrasound-guided fine needle biopsy (EUS-FNB) is an essential tool for tissue acquisition in solid pancreatic tumors. Rapid on-site evaluation (ROSE) by cytologists ensures diagnostic accuracy. However, the universal application of the ROSE is limited by its availability. Therefore, we aimed to investigate the feasibility of determining the end of the procedure based on the results of in-room cytological evaluation by trained endosonographers (IRCETE). Methods: A training course focusing on the cytological interpretation of common pancreatic tumors was provided to the three endosonographers. After training, the decision to terminate EUS-FNB was made based on IRCETE results. The diagnostic accuracy, concordance rate of diagnostic categories, and sample adequacy were compared with those determined by board-certified cytologists and macroscopic on-site evaluation (MOSE). Results: We enrolled 65 patients with solid pancreatic tumors, most of whom were malignant (86.2%). The diagnostic accuracy was 90.8% when the end of the procedure was determined based on IRCETE, compared to 87.7% and 98.5% when determined by MOSE and cytologists, respectively (p=0.060). Based on the cytologists’ results, the accuracy of IRCETE in diagnostic category interpretation was 97.3%. Conclusions In the absence of ROSE, IRCETE can serve as a supplementary alternative to MOSE in determining the end of tissue sampling with a high accuracy rate.

Diabetic foot (DF) is one of the most serious chronic complications of diabetes. The incidence rate among global diabetes patients is as high as 15% to 25%, and about 50% of patients will develop contralateral foot ulcers within 5 years after the first unilateral ulcer. As a non-invasive prevention and control solution, the application progress of functional insoles is mainly reflected in the following aspects:(1) Material innovation. The application of new composite materials and smart materials has significantly enhanced the pressure reduction effect and comfort. (2) Structural optimization. The development of multi-layer design and local pressure reduction structure has achieved more precise pressure distribution regulation. (3) Manufacturing process. 3D printing and parametric design have enabled the personalized customization of functional insoles. (4) Intelligent monitoring. It integrates functions such as pressure sensing and temperature monitoring, achieving real-time monitoring and early warning of foot conditions. Clinical research has confirmed that personalized functional insoles could reduce the incidence of foot ulcers and shorten the healing time of ulcers. At present, the research hotspots mainly focus on the development of smart materials, the construction of multi-functional integration and remote monitoring systems. However, in-depth research is still needed in the aspects of biomechanical mechanisms, standardized evaluation systems and long-term efficacy assessment. The development of future functional insoles should focus on the coordinated advancement of "personalization-intelligence-standardization", with the aim of providing more effective solutions for the prevention and treatment of DF.
Humans ; Diabetic Foot/therapy* ; Foot Orthoses

Background/Aims: Endoscopic ultrasound-guided fine needle biopsy (EUS-FNB) is an essential tool for tissue acquisition in solid pancreatic tumors. Rapid on-site evaluation (ROSE) by cytologists ensures diagnostic accuracy. However, the universal application of the ROSE is limited by its availability. Therefore, we aimed to investigate the feasibility of determining the end of the procedure based on the results of in-room cytological evaluation by trained endosonographers (IRCETE). Methods: A training course focusing on the cytological interpretation of common pancreatic tumors was provided to the three endosonographers. After training, the decision to terminate EUS-FNB was made based on IRCETE results. The diagnostic accuracy, concordance rate of diagnostic categories, and sample adequacy were compared with those determined by board-certified cytologists and macroscopic on-site evaluation (MOSE). Results: We enrolled 65 patients with solid pancreatic tumors, most of whom were malignant (86.2%). The diagnostic accuracy was 90.8% when the end of the procedure was determined based on IRCETE, compared to 87.7% and 98.5% when determined by MOSE and cytologists, respectively (p=0.060). Based on the cytologists’ results, the accuracy of IRCETE in diagnostic category interpretation was 97.3%. Conclusions In the absence of ROSE, IRCETE can serve as a supplementary alternative to MOSE in determining the end of tissue sampling with a high accuracy rate.

Background/Aims: Endoscopic ultrasound-guided fine needle biopsy (EUS-FNB) is an essential tool for tissue acquisition in solid pancreatic tumors. Rapid on-site evaluation (ROSE) by cytologists ensures diagnostic accuracy. However, the universal application of the ROSE is limited by its availability. Therefore, we aimed to investigate the feasibility of determining the end of the procedure based on the results of in-room cytological evaluation by trained endosonographers (IRCETE). Methods: A training course focusing on the cytological interpretation of common pancreatic tumors was provided to the three endosonographers. After training, the decision to terminate EUS-FNB was made based on IRCETE results. The diagnostic accuracy, concordance rate of diagnostic categories, and sample adequacy were compared with those determined by board-certified cytologists and macroscopic on-site evaluation (MOSE). Results: We enrolled 65 patients with solid pancreatic tumors, most of whom were malignant (86.2%). The diagnostic accuracy was 90.8% when the end of the procedure was determined based on IRCETE, compared to 87.7% and 98.5% when determined by MOSE and cytologists, respectively (p=0.060). Based on the cytologists’ results, the accuracy of IRCETE in diagnostic category interpretation was 97.3%. Conclusions In the absence of ROSE, IRCETE can serve as a supplementary alternative to MOSE in determining the end of tissue sampling with a high accuracy rate.

Purpose: Preoperative localization plays an important role in secondary hyperparathyroidism (SHPT) surgery. The advantages of neck ultrasound (US) include high availability and low cost. However, the reported sensitivity of US is 54%– 76%, and the reason for missed parathyroid glands (PGs) on US has been rarely addressed. Methods: Fifty-four patients who were diagnosed with renal SHPT from September 2020 to March 2022 were included in this retrospective study. Preoperative localization included surgeon-oriented US and technetium 99m-sestamibi singlephoton emission CT (SPECT)/CT. Results: A total of 212 PGs were pathologically confirmed, resulting in a success rate of 96.2% (52 of 54). Using echo, 193 PGs (91.0%) were accurately localized, while 19 glands (9.0%) were not identified, including those in ectopic positions (n = 12, at thymus or intrathyroid or others), of small size (<1 cm, n = 6), or overlapping with an ipsilateral PG (n = 1). US accurately detected 4 PGs in 36 (66.7%) patients, while SPECT/CT localized 4 glands in 19 patients (35.2%). Although the number of US-detectable PGs was not associated with success rate, it showed a significant negative correlation with surgical time (rs = –0.459, P = 0.002). Conclusion US detected 4 glands in 66% of SHPT patients with a sensitivity of 90% for localization. Ectopic position and small size were the most common reasons for the failure to detect PG on US. Complete preoperative echo localization might shorten operating time.

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.

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.

Crohn’s disease (CD) is a chronic, fluctuating inflammatory condition that primarily affects the gastrointestinal tract. Although the incidence of CD in Taiwan is lower than that in Western countries, the severity of CD presentation appears to be similar between Asia and the West. This observation indicates the urgency for devising revised guidelines tailored to the unique reimbursement system, and patient requirements in Taiwan. The core objectives of these updated guidelines include the updated treatment choices and the integration of the treat-to-target strategy into CD management, promoting the achievement of deep remission to mitigate complications and enhance the overall quality of life. Given the diversity in disease prevalence, severity, insurance policies, and access to medical treatments in Taiwan, a customized approach is imperative for formulating these guidelines. Such tailored strategies ensure that international standards are not only adapted but also optimized to local contexts. Since the inception of its initial guidelines in 2017, the Taiwan Society of Inflammatory Bowel Disease (TSIBD) has acknowledged the importance of continuous revisions for incorporating new therapeutic options and evolving disease management practices. The latest update leverages international standards and recent research findings focused on practical implementation within the Taiwanese healthcare system.

Lower-cost genotyping technology has promoted the generation of large genetic datasets with the evolving next-generation sequencing technology. The emergence of genome-wide association studies (GWAS) has facilitated researchers’ understanding of common complex diseases. GWAS refers to finding the sequence variations present in the human genome and screening out disease-related single nucleotide polymorphisms (SNPs). These SNPs are considered as the basis for assessing the stability of complex diseases. However, a single variation is not sufficient to assess an individual’s risk of disease. Polygenic risk score (PRS) is an emerging genetic data analysis method for quantitatively estimating an individual’s genetic risk for complex diseases by comprehensively considering multiple genetic variation sites. A single-value estimate of an individual’s genetic risk for a certain phenotype can be calculated as the cumulative impact of multiple genetic variants by building a PRS model. The finally expected risk score is weighted by the strength and direction of association of each SNP with the phenotype based on the number of alleles carried by each SNP. With the continuous development of various PRS calculation methods and the constant accumulation of genomic data, PRS has received widespread attention in the field of genetics. So far, quite a few studies at home and abroad have shown that PRS is valuable in risk prediction of different types of human traits or complex diseases, and its effectiveness has been further verified in clinical applications. At present, many studies have established PRS models based on GWAS summary statistics to quantify the genetic risk of susceptibility loci and clinical characteristics on diseases such as lung cancer, breast cancer, coronary heart disease, diabetes and Alzheimer’s disease. The disease-susceptible populations can be recognized through comparing the relative risk and absolute risk of the disease in different risk groups according to the population risk stratification results. Additionally, individual-level genotype data and omics data can also be used as data sources for PRS analysis research, especially the latter can dynamically reflect the short-term or long-term effects of environmental factors on human gene expression, and has potential application value in building early warning models to assess health risks. Since the calculation of PRS involves a large amount of genomic data analysis, there are big differences in the methods for data selection, model building and validation. Different PRS construction methods and software have different performances in disease risk prediction, and even the performance of same algorithm varies across diseases. It is worth noting that the PRS model often needs to be re-evaluated and verified for different groups of people, because PRS is affected by race and region. This review combines currently published PRS-related research and algorithms to describe the basic principles of PRS, compares their construction and verification methods, and discusses their applications and prospects. As a powerful genetic risk assessment tool, PRS has great potential in analyzing the genetic code of complex diseases and achieving precise diagnosis and personalized treatment.