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Left ventricular dysfunction is a known risk factor for morbidity and mortality in hemodialysis patients. The prognostic value of left ventricular global longitudinal strain (LV GLS) among those with preserved left ventricular ejection fraction (LVEF) remains uncertain. Subjects with end-stage renal disease initiated hemodialysis at Taipei Veteran General Hospital between 2015 and 2018 were registered. All participants received annually echocardiographic studies thereafter. Left ventricular end-systolic volume (LVESV), end-diastolic volume (LVEDV) and internal diameter in systole (LVIDs), LVEF, and LV GLS were measured. A LV GLS of > – 15.9% was defined as reduced LV GLS. Clinical outcomes of mortality and hospitalization for heart failure (HHF) were followed. A total of 319 patients with preserved LVEF (66.3 ± 15.1 years, 48.6% men) were recruited in the study. Subjects with reduced LV GLS had more coronary artery disease (CAD), higher LVESV and LVIDs, but were similar in age, gender, co-morbidities, biochemistries and other echocardiographic parameters as the counterpart. Both CAD [(odds ratio (OR) and 95% confidence intervals (CIs): 1.669, 1.023–2.724], and LVESV (OR per-1 mL and 95% CIs: 1.073, 1.004–1.146) were independent determinants of reduced LV GLS. Kaplan-Meier analysis indicated that patients with reduced LV GLS had a significantly lower event-free survival rate compared to those with preserved GLS. The multivariate Cox regression analysis further demonstrated LV GLS as a significant predictor of adverse clinical events (hazard ratio per-1% and 95% CIs: 1.055, 1.002–1.110) after accounting for age, gender, and diabetes. Among the hemodialysis patients with preserved LVEF, LV GLS but not the conventional left ventricular functional indices were associated with long-term mortality and HHF. CAD could be a modifiable risk factor among the subjects with reduced LV GLS.

BackgroundHeart failure (HF) with improved ejection fraction (HFimpEF) is a recently identified phenotype of HF, which had better cardiovascular outcomes compared with persistent HF with reduced ejection fraction (HFrEF). The present study aimed to investigate the predictive value of tissue inhibitor of metalloproteinase (TIMP)-1 and matrix metalloproteinases-9 (MMP-9) in the recovery of left ventricular ejection fraction (LVEF).MethodsSubjects who presented with acute decompensated HF and reduced LVEF of ≤40% were eligible for this study. HFimpEF was defined by a follow-up LVEF >40% and a ≥10% improvement in LVEF. Overnight fasting N-terminal pro-brain natriuretic peptide (NT-proBNP), MMP-9 and TIMP-1 were measured within 24 hours before discharge. The study participants were followed for up to 5 years.ResultsAmong a total of 91 participants (70.1±16.2 years, baseline LVEF 28.9±7.6%), 19 (20.8%) of them had HFimpEF and 72 (79.2%) had persistent HFrEF at 6 months. The receiver operating characteristic curve analyses showed the area under curve measures for TIMP-1, MMP-9 and NT-proBNP in the prediction of HFimpEF were 0.69, 0.52 and 0.65, respectively. TIMP-1 was negatively correlated with HFimpEF as continuous variables (OR per 1-SD and 95% CI 0.99 (0.98 to 1.00)) and categorical variables (cut-off value 200.68 ng/mL, OR and 95% CI 0.16 (0.05 to 0.54)) after adjustment of confounding factors. During a mean follow-up duration 34.8 months, patients with HFimpEF will have better long-term survival than those with persistent HFrEF.ConclusionsIn subjects with decompensated HFrEF, TIMP-1, but not MMP-9 was associated with the reverse remodelling in LVEF. In addition, patients with HFimpEF would have better long-term survival.

Background Echocardiography is commonly used to assess hydratation status and cardiac function in kidney failure patients, but the impact of structural or functional abnormalities on the prognosis of kidney failure patients was yet to be investigated. This study aimed to investigate the prevalence and clinical significance of echocardiographic abnormalities in kidney failure patients. Methods This study included 857 kidney failure patients who underwent echocardiography at dialysis initiation. Patients were followed up for a median of 4.2 years for the occurrence of major adverse cardiovascular events (MACE) and all-cause mortality. Results Among the 857 patients studied, 77% exhibited at least one echocardiographic abnormality. The most common abnormalities were left ventricular hypertrophy and left atrial enlargement, but they were not significantly correlated with poor outcomes. Instead, the primary predictors of both major adverse cardiovascular events and mortality in kidney failure patients were left ventricular systolic function, right ventricular systolic function, left ventricular volume index, and valvular abnormalities. Although diastolic dysfunction was linked to major adverse cardiovascular events, it was not associated with mortality. Furthermore, the study revealed that increased left ventricular volume index and left ventricular systolic dysfunction had a more significant impact on peritoneal dialysis (PD) patients than on hemodialysis (HD) patients. Conclusion This study provides insights into the echocardiographic abnormalities and their association with adverse outcomes in kidney failure patients, which can help clinicians optimize the management of patients and closely monitor possible high-risk populations. Graphical abstract

Disclosure: C. Tseng: None. C. Tseng: None. H. Chen: None. P. Chen: None. C. Huang: None. Background: Thionamide-induced agranulocytosis (TiA), is a rare adverse event with a reported incidence of around 0.1-1.75%. To reduce mortality, prompt recognition is critical but the differential diagnosis of TiA cases from non-TiA neutropenia can be challenging as other causes of neutropenia, such as concomitant chemotherapy, liver dysfunction or infection, may simultaneously exist. The present study aimed at investigating the possible factors associated with the development of TiA. Method: This is a retrospective cohort study of patients treated with anti-thyroid drugs (ATDs) in Taipei Veterans General Hospital from 2006-2018. Patients who developed a neutropenic event under treatment of ATDs were identified from the medical records. TiA was defined as (1) development of neutropenia under treatment or within 7 days of previous exposure to the same ATDs; (2) total recovery of neutropenia within one month after discontinuation of the culprit drug with absolute neutrophil count > 1500/μL; (3) exclusion of other causes for neutropenia. The incidence and risk factors for developing TiA were analyzed and compared to those with non-TiA neutropenia. Results: Among 6644 patients treated with ATDs, 66 (mean age, 53±15 years; 16.2% men) developed a neutropenic event and 20 were diagnosed with TiA (incidence: 0.3%). In univariate analysis, TiA was associated with shorter treatment duration, lesser cumulative ATD dosage, higher ATDs dosage, higher absolute neutrophil count and higher free T4 level at the time of the neutropenic event, compared to non-TiA neutropenia. After accounting for age, gender and time to neutropenia, ATDs dosage at the time of neutropenic event [odds ratio (OR) and 95% confident intervals (CIs): 635.47, 1.88-214562.36], free T4 level (OR and 95% CIs: 17.23, 1.02-290.58), and absolute neutrophil count (OR and 95% CIs: 1.00, 1.00-1.01) were still independently associated with TiA in multivariable logistic regression. Conclusions: TiA patients were more likely to have higher free T4 level, higher absolute neutrophil count at the time of neutropenic event and had received higher dosage of ATDs, compared to non-TiA cases. Presentation: Friday, June 16, 2023

Helicobacter pylori ( H. pylori ) infection is the principal cause of chronic gastritis, gastric ulcers, duodenal ulcers, and gastric cancer. In clinical practice, diagnosis of H. pylori infection by a gastroenterologists’ impression of endoscopic images is inaccurate and cannot be used for the management of gastrointestinal diseases. The aim of this study was to develop an artificial intelligence classification system for the diagnosis of H. pylori infection by pre-processing endoscopic images and machine learning methods. Endoscopic images of the gastric body and antrum from 302 patients receiving endoscopy with confirmation of H. pylori status by a rapid urease test at An Nan Hospital were obtained for the derivation and validation of an artificial intelligence classification system. The H. pylori status was interpreted as positive or negative by Convolutional Neural Network (CNN) and Concurrent Spatial and Channel Squeeze and Excitation (scSE) network, combined with different classification models for deep learning of gastric images. The comprehensive assessment for H. pylori status by scSE-CatBoost classification models for both body and antrum images from same patients achieved an accuracy of 0.90, sensitivity of 1.00, specificity of 0.81, positive predictive value of 0.82, negative predicted value of 1.00, and area under the curve of 0.88. The data suggest that an artificial intelligence classification model using scSE-CatBoost deep learning for gastric endoscopic images can distinguish H. pylori status with good performance and is useful for the survey or diagnosis of H. pylori infection in clinical practice.

This study aimed to determine how Chinese children adapt to Chinese orthography–phonology correspondence by acquiring phonetic radical awareness (PRA). This study used two important Chinese encoding approaches (rote and orthographic approaches) as the developmental trajectory, in which the present study hypothesized that phonological awareness (PA) exerts not only a direct influence on PRA but also an indirect influence through paired– associate learning (PAL). We also explored whether the association between PA and PAL is affected by the complexity of visual stimuli embedded in PAL. This study recruited 70 s-grade students to participate in various tests, which assessed (a) PA (measured by onset and rhyme awareness), (b) PRA (measured by regularity and consistency of phonetic radicals), (c) PAL (measured by learning performance on strokes; pattern-object and strokes pattern-syllable mapping), and (d) Chinese character recognition ability. Path analyses indicated that (1) character size had a significant positive correlation with PRA but not with PAL, (2) PAL fully mediated the association between PA and PRA, and (3) compared with PAL with a low stroke count, PA had a stronger relationship with PAL with a high stroke count. The results of this study were consistent with previous studies and suggest that PRA is the most important literacy skill for children in the middle of their learning-to-read stage. The results also augment existing literature by revealing that PRA acquisition is increased by PAL supported by PA, rather than by PA alone. Moreover, when the visual complexity of PAL increases, the support of PA to PAL would increase to make up for the working memory shortage.

Machine learning algorithms were used to analyze the odds and predictors of complications of thyroid damage after radiation therapy in patients with head and neck cancer. This study used decision tree (DT), random forest (RF), and support vector machine (SVM) algorithms to evaluate predictors for the data of 137 head and neck cancer patients. Candidate factors included gender, age, thyroid volume, minimum dose, average dose, maximum dose, number of treatments, and relative volume of the organ receiving X dose (X: 10, 20, 30, 40, 50, 60 Gy). The algorithm was optimized according to these factors and tenfold cross-validation to analyze the state of thyroid damage and select the predictors of thyroid dysfunction. The importance of the predictors identified by the three machine learning algorithms was ranked: the top five predictors were age, thyroid volume, average dose, V50 and V60. Of these, age and volume were negatively correlated with thyroid damage, indicating that the greater the age and thyroid volume, the lower the risk of thyroid damage; the average dose, V50 and V60 were positively correlated with thyroid damage, indicating that the larger the average dose, V50 and V60, the higher the risk of thyroid damage. The RF algorithm was most accurate in predicting the probability of thyroid damage among the three algorithms optimized using the above factors. The Area under the receiver operating characteristic curve (AUC) was 0.827 and the accuracy (ACC) was 0.824. This study found that five predictors (age, thyroid volume, mean dose, V50 and V60) are important factors affecting the chance that patients with head and neck cancer who received radiation therapy will develop hypothyroidism. Using these factors as the prediction basis of the algorithm and using RF to predict the occurrence of hypothyroidism had the highest ACC, which was 82.4%. This algorithm is quite helpful in predicting the probability of radiotherapy complications. It also provides references for assisting medical decision-making in the future.

Purpose This study aims to develop an ensemble machine learning-based (EML-based) risk prediction model for radiation dermatitis (RD) in patients with head and neck cancer undergoing proton radiotherapy, with the goal of achieving superior predictive performance compared to traditional models. Materials and methods Data from 57 head and neck cancer patients treated with intensity-modulated proton therapy at Kaohsiung Chang Gung Memorial Hospital were analyzed. The study incorporated 11 clinical and 9 dosimetric parameters. Pearson’s correlation was used to eliminate highly correlated variables, followed by feature selection via LASSO to focus on potential RD predictors. Model training involved traditional logistic regression (LR) and advanced ensemble methods such as Random Forest and XGBoost, which were optimized through hyperparameter tuning. Results Feature selection identified six key predictors, including smoking history and specific dosimetric parameters. Ensemble machine learning models, particularly XGBoost, demonstrated superior performance, achieving the highest AUC of 0.890. Feature importance was assessed using SHAP (SHapley Additive exPlanations) values, which underscored the relevance of various clinical and dosimetric factors in predicting RD. Conclusion The study confirms that EML methods, especially XGBoost with its boosting algorithm, provide superior predictive accuracy, enhanced feature selection, and improved data handling compared to traditional LR. While LR offers greater interpretability, the precision and broader applicability of EML make it more suitable for complex medical prediction tasks, such as predicting radiation dermatitis. Given these advantages, EML is highly recommended for further research and application in clinical settings.

Graptopetalum paraguayense (GP) is a folk herbal medicine with hepatoprotective effects that is used in Taiwan. The aim of this study was to evaluate the hepatoprotective and antifibrotic effects of GP on experimental hepatic fibrosis in both dimethylnitrosamine (DMN)- and carbon tetrachloride (CCl(4))-induced liver injury rats. Hepatic fibrosis-induced rats were fed with the methanolic extract of GP (MGP) by oral administration every day. Immunohistochemistry, biochemical assays, and Western blot analysis were performed. The effects of MGP on the expression of fibrotic markers and cytokines in the primary cultured hepatic stellate cells (HSCs) and Kupffer cells, respectively, were evaluated. Oral administration of MGP significantly alleviated DMN- or CCl(4)-induced liver inflammation and fibrosis. High levels of alanine transaminase, aspartate transaminase, bilirubin, prothrombin activity and mortality rates also decreased in rats treated with MGP. There were significantly decreased hydroxyproline levels in therapeutic rats compared with those of the liver-damaged rats. Collagen I and alpha smooth muscle actin (α-SMA) expression were all reduced by incubation with MGP in primary cultured rat HSCs. Furthermore, MGP induced apoptotic cell death in activated HSCs. MGP also suppressed lipopolysaccharide-stimulated rat Kupffer cell activation by decreasing nitric oxide, tumor necrosis factor-α and interleukin-6 production, and increasing interleukin-10 expression. The results show that the administration of MGP attenuated toxin-induced hepatic damage and fibrosis in vivo and inhibited HSC and Kupffer cell activation in vitro, suggesting that MGP might be a promising complementary or alternative therapeutic agent for liver inflammation and fibrosis.

The fact that many chemotherapeutic drugs cause chemoresistance and side effects during the course of colorectal cancer treatment necessitates development of novel cytotoxic agents aiming to attenuate new molecular targets. Here, we show that Astragalus membranaceus (Fischer) Bge. var. mongolicus (Bge.) Hsiao (AM), a traditional Chinese medicine, can inhibit tumor growth in vivo and elucidate the underlying molecular mechanisms. The antitumor effect of AM was assessed on the subcutaneous tumors of human colorectal cancer cell line HCT116 grafted into nude mice. The mice were treated with either water or 500 mg/kg AM once per day, before being sacrificed for extraction of tumors, which were then subjected to microarray expression profiling. The gene expression of the extraction was then profiled using microarray analysis. The identified genes differentially expressed between treated mice and controls reveal that administration of AM suppresses chromosome organization, histone modification, and regulation of macromolecule metabolic process. A separate analysis focused on differentially expressed microRNAs revealing involvement of macromolecule metabolism, and intracellular transport, as well as several cancer signaling pathways. For validation, the input of the identified genes to The Library of Integrated Network-based Cellular Signatures led to many chemopreventive agents of natural origin that produce similar gene expression profiles to that of AM. The demonstrated effectiveness of AM suggests a potential therapeutic drug for colorectal cancer.