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/Aims: Steatotic liver disease (SLD) is a common manifestation in chronic hepatitis C (CHC). Metabolic alterations in CHC are associated with metabolic dysfunction-associated steatotic liver disease (MASLD). We aimed to elucidate whether hepatitis C virus (HCV) eradication mitigates MASLD occurrence or resolution. Methods: We enrolled 5,840 CHC patients whose HCV was eradicated by direct-acting antivirals in a nationwide HCV registry. MASLD and the associated cardiometabolic risk factors (CMRFs) were evaluated at baseline and 6 months after HCV cure. Results: There were 2,147 (36.8%) patients with SLD, and 1,986 (34.0%) of them met the MASLD criteria before treatment. After treatment, HbA1c (6.0% vs. 5.9%, p<0.001) and BMI (24.8 kg/m2 vs. 24.7 kg/m2, p<0.001) decreased, whereas HDL-C (49.1 mg/dL vs. 51.9 mg/dL, p<0.001) and triglycerides (102.8 mg/dL vs. 111.9 mg/dL, p<0.001) increased significantly. The proportion of patients with SLD was 37.5% after HCV eradication, which did not change significantly compared with the pretreatment status. The percentage of the patients who had post-treatment MASLD was 34.8%, which did not differ significantly from the pretreatment status (p=0.17). Body mass index (BMI) (odds ratio [OR] 0.89; 95% confidence intervals [CI] 0.85–0.92; p<0.001) was the only factor associated with MASLD resolution. In contrast, unfavorable CMRFs, including BMI (OR 1.10; 95% CI 1.06–1.14; p<0.001) and HbA1c (OR 1.19; 95% CI 1.04–1.35; p=0.01), were independently associated with MASLD development after HCV cure. Conclusions HCV eradication mitigates MASLD in CHC patients. CMRF surveillance is mandatory for CHC patients with metabolic alterations, which are altered after HCV eradication and predict the evolution of MASLD.

Hyperpolarized (HP) carbon-13 ( 13C) MRI represents an innovative approach for noninvasive, real-time assessment of dynamic metabolic flux, with potential integration into routine clinical MRI. The use of [1- 13C]pyruvate as a probe and its conversion to [1- 13C]lactate constitute an extensively explored metabolic pathway. This review comprehensively outlines the establishment of HP 13C-MRI, covering multidisciplinary team collaboration, hardware prerequisites, probe preparation, hyperpolarization techniques, imaging acquisition, and data analysis. This article discusses the clinical applications of HP 13C-MRI across various anatomical domains, including the brain, heart, skeletal muscle, breast, liver, kidney, pancreas, andprostate. Each section highlights the specific applications and findings pertinent to these regions, emphasizing the potential versatility of HP 13C-MRI in diverse clinical contexts. This review serves as a comprehensive update, bridging technical aspects with clinical applications and offering insights into the ongoing advancements in HP 13C-MRI.

OBJECTIVE: This study evaluated the effectiveness of acupuncture treatment on postoperative pain in patients with degenerative lumbar spine disease, and explored the relationship between the postoperative analgesic effect of acupuncture and the sensation of acupuncture experienced by the patients. METHODS: This retrospective study analyzed the medical records of 97 patients who had undergone an operation by the same surgeon due to degenerative lumbar disease. These patients were divided into acupuncture group (n = 32), patient-controlled analgesia (PCA) group (n = 27), and oral analgesia group (n = 38) according to the different postoperative analgesic methods. During their hospitalization, patients completed daily evaluations of their pain using a visual analogue scale (VAS), and injection times of supplemental meperidine were recorded. Also, the Chinese version of the Massachusetts General Hospital Acupuncture Sensation Scale (C-MASS) was used in the acupuncture group. RESULTS: Each of the three treatment groups showed significant reductions in postoperative pain, as shown by reduced VAS scores. The acupuncture group, however, had less rebound pain (P < 0.05) than the other two groups. Both the acupuncture and PCA groups experienced acute analgesic effects that were superior to those in the oral analgesia group. In addition, the higher the C-MASS index on the second day after surgery, the lower the VAS score on the fourth day after surgery. There was also a significant difference in the "dull pain" in the acupuncture sensation. CONCLUSION The results demonstrated that acupuncture was beneficial for postoperative pain and discomfort after simple surgery for degenerative spinal disease. It is worth noting that there was a disproportionate relevance between the patient's acupuncture sensation and the improvement of pain VAS score.
Acupuncture Points ; Acupuncture Therapy ; Analgesia/methods* ; Analgesics/therapeutic use* ; Consensus ; Humans ; Pain, Postoperative/drug therapy* ; Prospective Studies ; Retrospective Studies ; Sensation

Background/Aims: Direct‐acting antivirals (DAAs) have been approved for hepatitis C virus (HCV) treatment in patients with end-stage renal disease (ESRD) on hemodialysis. Nevertheless, the complicated comedications and their potential drug-drug interactions (DDIs) with DAAs might limit clinical practice in this special population. Methods: The number, class, and characteristics of comedications and their potential DDIs with five DAA regimens were analyzed among HCV-viremic patients from 23 hemodialysis centers in Taiwan. Results: Of 2,015 hemodialysis patients screened in 2019, 169 patients seropositive for HCV RNA were enrolled (mean age, 65.6 years; median duration of hemodialysis, 5.8 years). All patients received at least one comedication (median number, 6; mean class number, 3.4). The most common comedication classes were ESRD-associated medications (94.1%), cardiovascular drugs (69.8%) and antidiabetic drugs (43.2%). ESRD-associated medications were excluded from DDI analysis. Sofosbuvir/velpatasvir/voxilaprevir had the highest frequency of potential contraindicated DDIs (red, 5.6%), followed by glecaprevir/pibrentasvir (4.0%), sofosbuvir/ledipasvir (1.3%), sofosbuvir/velpatasvir (1.3%), and elbasvir/grazoprevir (0.3%). For potentially significant DDIs (orange, requiring close monitoring or dose adjustments), sofosbuvir/velpatasvir/voxilaprevir had the highest frequency (19.9%), followed by sofosbuvir/ledipasvir (18.2%), glecaprevir/pibrentasvir (12.6%), sofosbuvir/velpatasvir (12.6%), and elbasvir/grazoprevir (7.3%). Overall, lipid-lowering agents were the most common comedication class with red-category DDIs to all DAA regimens (n=62), followed by cardiovascular agents (n=15), and central nervous system agents (n=10). Conclusions HCV-viremic patients on hemodialysis had a very high prevalence of comedications with a broad spectrum, which had varied DDIs with currently available DAA regimens. Elbasvir/grazoprevir had the fewest potential DDIs, and sofosbuvir/velpatasvir/voxilaprevir had the most potential DDIs.

OBJECTIVE: Altered event-related potential (ERP) performances have been noted in attention deficit hyperactivity disorder (ADHD) patients and reflect neurocognitive dysfunction. Whether these ERP alterations and correlated dysfunctions exist in healthy parents with ADHD offspring is worth exploring. METHODS: Thirteen healthy parents with ADHD offspring and thirteen healthy controls matched for age, sex and years of education were recruited. The auditory oddball paradigm was used to evaluate the P300 wave complex of the ERP, and the Wechsler Adult Intelligence Scale-Revised, Wisconsin Card Sorting Test, and continuous performance test were used to measure neurocognitive performance. RESULTS: Healthy parents with ADHD offspring had significantly longer auditory P300 latency at Fz than control group. However, no significant differences were found in cognitive performance. CONCLUSION: The presence of a subtle alteration in electro-neurophysiological activity without explicit neurocognitive dysfunction suggests potential candidate of biological marker for parents with ADHD offspring.
Adult ; Attention Deficit Disorder with Hyperactivity ; Biomarkers ; Cognition ; Education ; Evoked Potentials ; Humans ; Intelligence ; Parents ; Wisconsin