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.

Objective: We aimed to investigate whether 2-[ 18F]fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (2-[ 18F]FDG PET/CT) can aid in evaluating the risk of malignancy in ampullary tumors detected by endoscopy. Materials and Methods: This single-center retrospective cohort study analyzed 155 patients (79 male, 76 female; mean age, 65.7 ± 12.7 years) receiving 2-[ 18F]FDG PET/CT for endoscopy-detected ampullary tumors 5–87 days (median, 7 days) after the diagnostic endoscopy between June 2007 and December 2020. The final diagnosis was made based on histopathological findings. The PET imaging parameters were compared with clinical data and endoscopic features. A model to predict the risk of malignancy, based on PET, endoscopy, and clinical findings, was generated and validated using multivariable logistic regression analysis and an additional bootstrapping method. The final model was compared with standard endoscopy for the diagnosis of ampullary cancer using the DeLong test. Results: The mean tumor size was 17.1 ± 7.7 mm. Sixty-four (41.3%) tumors were benign, and 91 (58.7%) were malignant. Univariable analysis found that ampullary neoplasms with a blood-pool corrected peak standardized uptake value in earlyphase scan (SUVe) ≥ 1.7 were more likely to be malignant (odds ratio [OR], 16.06; 95% confidence interval [CI], 7.13–36.18;P < 0.001). Multivariable analysis identified the presence of jaundice (adjusted OR [aOR], 4.89; 95% CI, 1.80–13.33; P = 0.002), malignant traits in endoscopy (aOR, 6.80; 95% CI, 2.41–19.20; P < 0.001), SUVe ≥ 1.7 in PET (aOR, 5.43; 95% CI, 2.00–14.72; P < 0.001), and PET-detected nodal disease (aOR, 5.03; 95% CI, 1.16–21.86; P = 0.041) as independent predictors of malignancy. The model combining these four factors predicted ampullary cancers better than endoscopic diagnosis alone (area under the curve [AUC] and 95% CI: 0.925 [0.874–0.956] vs. 0.815 [0.732–0.873], P < 0.001). The model demonstrated an AUC of 0.921 (95% CI, 0.816–0.967) in candidates for endoscopic papillectomy. Conclusion Adding 2-[ 18F]FDG PET/CT to endoscopy can improve the diagnosis of ampullary cancer and may help refine therapeutic decision-making, particularly when contemplating endoscopic papillectomy.

Objective: Although both partners of a married couple can have mental disorders, the concordant and cross-concordant categories of disorders in couples remain unclear. Using national psychiatric population-based data only from patients with mental disorders, we examined married couples with mental disorders to examine spousal concordance and cross-disorder concordance across the full spectrum of mental disorders. Methods: Data from the 1997 to 2012 Taiwan Psychiatric Inpatient Medical Claims data set were used and a total of 662 married couples were obtained. Concordance of mental disorders was determined if both spouses were diagnosed with mental disorder of an identical category in the International Classification of Diseases, Ninth Revision, Clinical Modification; otherwise, cross-concordance was reported. Results: According to Cohen’s kappa coefficient, the most concordant mental disorder in couples was substance use disorder, followed by bipolar disorder. Depressive and anxiety disorders were the most common cross-concordant mental disorders, followed by bipolar disorder. The prevalence of the spousal concordance of mental disorders differed by monthly income and the couple’s age disparity. Conclusion Evidence of spousal concordance and cross-concordance for mental disorders may highlight the necessity of understanding the social context of marriage in the etiology of mental illness. Identifying the risk factors from a common environment attributable to mental disorders may enhance public health strategies to prevent and improve chronic mental illness of married couples.

Despite the advances in medical and device therapies for heart failure (HF), sudden cardiac death (SCD) remains a tremendous global burden in patients with HF. Among the risk factors for SCD, HF has the greatest impact. Previous studies focusing on patients with systolic dysfunction have found several predictive factors associated with SCD, lead‑ ing to the subsequent development of strategies of primary prevention, like placement of implantable cardioverterdefibrillator (ICD) in high-risk patients. Although patients with HF with preserved ejection fraction (HFpEF) were less prone to SCD compared to patients with HF with reduced ejection fraction (HFrEF), patients with HFpEF did account for a significant proportion of all HF patients who encountered SCD. The cutoff value of left ventricular ejection frac‑ tion (LVEF) to define the subset of HF did not reach consensus until 2016 when the European Society of Cardiology proposed a new classification system by LVEF. There is a great unmet need in the field of SCD in HFpEF regarding risk stratification and appropriate device therapy with ICD implantation. In this article, we will approach SCD in HFpEF from HFrEF subsets. We also aim at clarifying the mechanisms, risk factors, and prevention of SCD in HFpEF.

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