Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Purpose: Plasmablastic lymphoma (PBL) is a rare, aggressive lymphoma that is characterized by terminal B-cell differ‑ entiation. In the West, PBL usually occurs in patients with immunodeficiencies, particularly those induced by human immunodeficiency virus (HIV) infection. We investigated the clinicopathological features of PBL at a single institute in Taiwan, where HIV infection is rare. Methods: This retrospective chart review identified PBL cases that were treated at a single institute in southern Tai‑ wan between 2008 and 2024. Results: We identified nine patients (four males and five females; median age 71 years). Of the eight patients tested for HIV, only one tested positive. Pathologically, the tumors showed plasmablastic morphology and immunopheno‑ type, and three (33%) cases tested positive for Epstein–Barr virus. Six (67%) patients presented with Stage IV disease, including five (56%) with malignant effusion. Six patients were treated with chemotherapy and the remaining three received only supportive care. During a median follow-up of 10 months, five patients died of progressive disease, two died of unrelated diseases, and two were alive with PBL relapse. Conclusion In Taiwan, PBL constitutes a rare and aggressive clinical condition and is frequently associated with malignant effusion. In contrast to Western patients, the PBL in most patients from Taiwan was unrelated to HIV infection.

Purpose: Plasmablastic lymphoma (PBL) is a rare, aggressive lymphoma that is characterized by terminal B-cell differ‑ entiation. In the West, PBL usually occurs in patients with immunodeficiencies, particularly those induced by human immunodeficiency virus (HIV) infection. We investigated the clinicopathological features of PBL at a single institute in Taiwan, where HIV infection is rare. Methods: This retrospective chart review identified PBL cases that were treated at a single institute in southern Tai‑ wan between 2008 and 2024. Results: We identified nine patients (four males and five females; median age 71 years). Of the eight patients tested for HIV, only one tested positive. Pathologically, the tumors showed plasmablastic morphology and immunopheno‑ type, and three (33%) cases tested positive for Epstein–Barr virus. Six (67%) patients presented with Stage IV disease, including five (56%) with malignant effusion. Six patients were treated with chemotherapy and the remaining three received only supportive care. During a median follow-up of 10 months, five patients died of progressive disease, two died of unrelated diseases, and two were alive with PBL relapse. Conclusion In Taiwan, PBL constitutes a rare and aggressive clinical condition and is frequently associated with malignant effusion. In contrast to Western patients, the PBL in most patients from Taiwan was unrelated to HIV infection.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Purpose: Plasmablastic lymphoma (PBL) is a rare, aggressive lymphoma that is characterized by terminal B-cell differ‑ entiation. In the West, PBL usually occurs in patients with immunodeficiencies, particularly those induced by human immunodeficiency virus (HIV) infection. We investigated the clinicopathological features of PBL at a single institute in Taiwan, where HIV infection is rare. Methods: This retrospective chart review identified PBL cases that were treated at a single institute in southern Tai‑ wan between 2008 and 2024. Results: We identified nine patients (four males and five females; median age 71 years). Of the eight patients tested for HIV, only one tested positive. Pathologically, the tumors showed plasmablastic morphology and immunopheno‑ type, and three (33%) cases tested positive for Epstein–Barr virus. Six (67%) patients presented with Stage IV disease, including five (56%) with malignant effusion. Six patients were treated with chemotherapy and the remaining three received only supportive care. During a median follow-up of 10 months, five patients died of progressive disease, two died of unrelated diseases, and two were alive with PBL relapse. Conclusion In Taiwan, PBL constitutes a rare and aggressive clinical condition and is frequently associated with malignant effusion. In contrast to Western patients, the PBL in most patients from Taiwan was unrelated to HIV infection.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Objective: To construct a prognostic model for unsuccessful removal of nasogastric tube (NGT) was the aim of our study. Methods: This study examined patients with swallowing disorders receiving NGT feeding due to stroke or traumatic brain injury in a regional hospital. Clinical data was collected, such as age, sex, body mass index (BMI), level of activities of daily living (ADLs) dependence. Additionally, gather information regarding the enhancement in Functional Oral Intake Scale (FOIS) levels and the increase in food types according to the International Dysphagia Diet Standardization Initiative (IDDSI) after one month of swallowing training. A stepwise logistic regression analysis model was employed to predict NGT removal failure using these parameters. Results: Out of 203 patients, 53 patients (26.1%) had experienced a failed removal of NGT after six months of follow-up. The strongest predictors for failed removal were age over 60 years, underweight BMI, total dependence in ADLs, and ischemic stroke. The admission prediction model categorized patients into high, moderate, and low-risk groups for removal failure. The failure rate of NGT removal was high not only in the high-risk group but also in the moderate-risk groups when there was no improvement in FOIS levels and IDDSI food types. Conclusion Our predictive model categorizes patients with brain insults into risk groups for swallowing disorders, enabling advanced interventions such as percutaneous endoscopic gastrostomy for high-risk patients struggling with NGT removal, while follow-up assessments using FOIS and IDDSI aid in guiding rehabilitation decisions for those at moderate risk.

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.

Tubulin beta 4A class IVa (TUBB4A) spectrum disorders include autosomal dominant dystonia type 4 or hypomyelination with atrophy of the basal ganglia and cerebellum (H-ABC syndrome). However, in rare cases, only mild hypomyelination in the cortex with no basal ganglia atrophy may be observed. We report a case of a family with TUBB4A mutation and complicated hereditary spasticity paraplegia (HSP). We performed quadro whole-exome sequencing (WES) on the family to identify the causative gene of progressive spastic paraparesis with isolated hypomyelination leukodystrophy. We identified a novel TUBB4A p.F341L mutation, which was present in all three affected patients but absent in the unaffected father. The affected patients presented with adult-onset TUBB4A disorder, predominant spastic paraparesis with/without ataxia, and brain hypomyelination with no cognitive impairment or extrapyramidal symptoms. In the literature, HSP is considered a TUBB4A spectrum disorder.