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.

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.

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.

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: and Purpose This study aimed to investigate early changes in interstitial fluid (ISF) flow in patients with severe carotid stenosis after carotid angioplasty and stenting (CAS). Methods: We prospectively recruited participants with carotid stenosis ≥80% undergoing CAS at our institute between October 2019 and March 2023. Magnetic resonance imaging (MRI), including diffusion tensor imaging (DTI), and the Mini-Mental State Examination (MMSE) were performed 3 days before CAS. MRI with DTI and MMSE were conducted within 24 hours and 2 months after CAS, respectively. The diffusion tensor image analysis along the perivascular space (DTI-ALPS) index was calculated from the DTI data to determine the ISF status. Increments were defined as the ratio of the difference between post- and preprocedural values to preprocedural values. Results: In total, 102 participants (age: 67.1±8.9 years; stenosis: 89.5%±5.7%) with longitudinal data were evaluated. The DTI-ALPS index increased after CAS (0.85±0.15; 0.85 [0.22] vs. 0.86±0.14; 0.86 [0.21]; P=0.022), as did the MMSE score (25.9±3.7; 24.0 [4.0] vs. 26.9±3.4; 26.0 [3.0]; P<0.001). Positive correlations between increments in the DTI-ALPS index and MMSE score were found in all patients (rs=0.468; P<0.001). Conclusion An increased 24-hour post-CAS DTI-ALPS index suggests early improvement in ISF flow efficiency. The positive correlation between the 24-hour DTI-ALPS index and 2-month MMSE score increments suggests that early ISF flow improvement may contribute to long-term cognitive improvement after CAS.

Objectives: This study aimed to present the Asia-Pacific consensus on long-term and sequential therapy for osteoporosis, offering evidence-based recommendations for the effective management of this chronic condition.The primary focus is on achieving optimal fracture prevention through a comprehensive, individualized approach. Methods: A panel of experts convened to develop consensus statements by synthesizing the current literature and leveraging clinical expertise. The review encompassed long-term anti-osteoporosis medication goals, first-line treatments for individuals at very high fracture risk, and the strategic integration of anabolic and anti resorptive agents in sequential therapy approaches. Results: The panelists reached a consensus on 12 statements. Key recommendations included advocating for anabolic agents as the first-line treatment for individuals at very high fracture risk and transitioning to anti resorptive agents following the completion of anabolic therapy. Anabolic therapy remains an option for in dividuals experiencing new fractures or persistent high fracture risk despite antiresorptive treatment. In cases of inadequate response, the consensus recommended considering a switch to more potent medications. The consensus also addressed the management of medication-related complications, proposing alternatives instead of discontinuation of treatment. Conclusions This consensus provides a comprehensive, cost-effective strategy for fracture prevention with an emphasis on shared decision-making and the incorporation of country-specific case management systems, such as fracture liaison services. It serves as a valuable guide for healthcare professionals in the Asia-Pacific region, contributing to the ongoing evolution of osteoporosis management.

Background/Aims: Laryngeal symptoms are largely treated with empiric proton pump inhibitor (PPI) therapy if no apparent pathology shown on ear, nose, and throat evaluation and reflux-related etiologies are suspected. However, treatment response remains unsatisfactory. This study aimed to investigate the clinical and physiological characteristics of patients with PPI-refractory laryngeal symptoms. Methods: Patients with persistent laryngeal symptoms despite PPI treatment for ≥ 8 weeks were recruited. A multidisciplinary evaluationcomprising validated questionnaires for laryngeal symptoms (reflux symptom index [RSI]), gastroesophageal reflux disease symptoms, psychological comorbidity (5-item brief symptom rating scale [BSRS-5]) and sleep disturbance (Pittsburgh sleep quality index [PSQI]), esophagogastroduodenoscopy, ambulatory impedance-pH monitoring, and high-resolution impedance manometry were performed.Healthy asymptomatic individuals were also recruited for comparison of psychological morbidity and sleep disturbances. Results: Ninety-seven adult patients and 48 healthy volunteers were analyzed. The patients had markedly higher prevalence of psychological distress (52.6% vs 2.1%, P < 0.001) and sleep disturbance (82.5% vs 37.5%, P < 0.001) than the healthy volunteers. There were significant correlations between RSI and BSRS-5 scores, and between RSI and PSQI scores (r = 0.26, P = 0.010, and r = 0.29, P = 0.004, respectively). Fifty-eight patients had concurrent gastroesophageal reflux disease symptoms. They had more prominent sleep disturbances (89.7% vs 71.8%, P < 0.001) than those with laryngeal symptoms alone but similar reflux profiles and esophageal motility. Conclusions PPI-refractory laryngeal symptoms are mostly associated with psychological comorbidities and sleep disturbances. Recognition of these psychosocial comorbidities may help optimize management in these patients.

Wound healing is a dynamic process that involves a series of molecular and cellular events aimed at replacing devitalized and missing cellular components and/or tissue layers. Recently, extracellular vesicles (EVs), naturally cell-secreted lipid membrane-bound vesicles laden with biological cargos including proteins, lipids, and nucleic acids, have drawn wide attention due to their ability to promote wound healing and tissue regeneration. However, current exploitation of EVs as therapeutic agents is limited by their low isolation yields and tedious isolation processes. To circumvent these challenges, bioinspired cell-derived nanovesicles (CDNs) that mimic EVs were obtained by shearing mesenchymal stem cells (MSCs) through membranes with different pore sizes. Physical characterisations and high-throughput proteomics confirmed that MSC-CDNs mimicked MSC-EVs. Moreover, these MSC-CDNs were efficiently uptaken by human dermal fibroblasts and demonstrated a dose-dependent activation of MAPK signalling pathway, resulting in enhancement of cell proliferation, cell migration, secretion of growth factors and extracellular matrix proteins, which all promoted tissue regeneration. Of note, MSC-CDNs enhanced angiogenesis in human dermal microvascular endothelial cells in a 3D PEG-fibrin scaffold and animal model, accelerating wound healing in vitro and in vivo. These findings suggest that MSC-CDNs could replace both whole cells and EVs in promoting wound healing and tissue regeneration.

Introduction: Non-adherence to antihypertensive medications is a leading cause of uncontrolled hypertension and its complications. However, data on the factors associated with non-adherence to antihypertensive medications in the communities of Sarawak, Malaysia, are limited. This study aimed to examine the prevalence and determinants of medication non-adherence among patients with uncontrolled hypertension. Methods: A cross-sectional study was conducted using the systematic sampling method in four government primary healthcare clinics in Sarawak. A self-administered questionnaire was used to obtain socio-demographic data and evaluate non-adherence. Blood pressure was measured, and relevant clinical variables were collected from medical records. Multivariate logistic regression was used to determine the determinants of medication non-adherence. Results: A total of 488 patients with uncontrolled hypertension were enrolled in this study. The prevalence of medication non-adherence was 39.3%. There were four predictors of medication non-adherence among the patients with uncontrolled hypertension: tertiary educational level (odds ratio [OR]=4.21, 95% confidence interval [CI]=1.67–10.61, P=0.010), complementary alternative medication (OR=2.03, 95% CI=1.12–3.69, P=0.020), non-usage of calcium channel blockers (OR=1.57, 95% CI=1.02–2.41, P=0.039) and 1 mmHg increase in the systolic blood pressure (OR=1.03, 95% CI=1.00–1.05, P=0.006). Conclusion Because of the high prevalence of medication non-adherence among patients with uncontrolled hypertension, primary care physicians should be more vigilant in identifying those at risk of being non-adherent. Early intervention should be conducted to address non-adherence for blood pressure control.
Patient Compliance ; Hypertension ; Primary Health Care ; Malaysia