1.Predictive Modeling of Symptomatic Intracranial Hemorrhage Following Endovascular Thrombectomy: Insights From the Nationwide TREAT-AIS Registry
Jia-Hung CHEN ; I-Chang SU ; Yueh-Hsun LU ; Yi-Chen HSIEH ; Chih-Hao CHEN ; Chun-Jen LIN ; Yu-Wei CHEN ; Kuan-Hung LIN ; Pi-Shan SUNG ; Chih-Wei TANG ; Hai-Jui CHU ; Chuan-Hsiu FU ; Chao-Liang CHOU ; Cheng-Yu WEI ; Shang-Yih YAN ; Po-Lin CHEN ; Hsu-Ling YEH ; Sheng-Feng SUNG ; Hon-Man LIU ; Ching-Huang LIN ; Meng LEE ; Sung-Chun TANG ; I-Hui LEE ; Lung CHAN ; Li-Ming LIEN ; Hung-Yi CHIOU ; Jiunn-Tay LEE ; Jiann-Shing JENG ;
Journal of Stroke 2025;27(1):85-94
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.
2.Parkinsonism in Cerebral Autosomal Dominant Arteriopathy With Subcortical Infarcts and Leukoencephalopathy: Clinical Features and Biomarkers
Chih-Hao CHEN ; Te-Wei WANG ; Yu-Wen CHENG ; Yung-Tsai CHU ; Mei-Fang CHENG ; Ya-Fang CHEN ; Chin-Hsien LIN ; Sung-Chun TANG
Journal of Stroke 2025;27(1):122-127
3.Predictive Modeling of Symptomatic Intracranial Hemorrhage Following Endovascular Thrombectomy: Insights From the Nationwide TREAT-AIS Registry
Jia-Hung CHEN ; I-Chang SU ; Yueh-Hsun LU ; Yi-Chen HSIEH ; Chih-Hao CHEN ; Chun-Jen LIN ; Yu-Wei CHEN ; Kuan-Hung LIN ; Pi-Shan SUNG ; Chih-Wei TANG ; Hai-Jui CHU ; Chuan-Hsiu FU ; Chao-Liang CHOU ; Cheng-Yu WEI ; Shang-Yih YAN ; Po-Lin CHEN ; Hsu-Ling YEH ; Sheng-Feng SUNG ; Hon-Man LIU ; Ching-Huang LIN ; Meng LEE ; Sung-Chun TANG ; I-Hui LEE ; Lung CHAN ; Li-Ming LIEN ; Hung-Yi CHIOU ; Jiunn-Tay LEE ; Jiann-Shing JENG ;
Journal of Stroke 2025;27(1):85-94
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.
4.Parkinsonism in Cerebral Autosomal Dominant Arteriopathy With Subcortical Infarcts and Leukoencephalopathy: Clinical Features and Biomarkers
Chih-Hao CHEN ; Te-Wei WANG ; Yu-Wen CHENG ; Yung-Tsai CHU ; Mei-Fang CHENG ; Ya-Fang CHEN ; Chin-Hsien LIN ; Sung-Chun TANG
Journal of Stroke 2025;27(1):122-127
5.Predictive Modeling of Symptomatic Intracranial Hemorrhage Following Endovascular Thrombectomy: Insights From the Nationwide TREAT-AIS Registry
Jia-Hung CHEN ; I-Chang SU ; Yueh-Hsun LU ; Yi-Chen HSIEH ; Chih-Hao CHEN ; Chun-Jen LIN ; Yu-Wei CHEN ; Kuan-Hung LIN ; Pi-Shan SUNG ; Chih-Wei TANG ; Hai-Jui CHU ; Chuan-Hsiu FU ; Chao-Liang CHOU ; Cheng-Yu WEI ; Shang-Yih YAN ; Po-Lin CHEN ; Hsu-Ling YEH ; Sheng-Feng SUNG ; Hon-Man LIU ; Ching-Huang LIN ; Meng LEE ; Sung-Chun TANG ; I-Hui LEE ; Lung CHAN ; Li-Ming LIEN ; Hung-Yi CHIOU ; Jiunn-Tay LEE ; Jiann-Shing JENG ;
Journal of Stroke 2025;27(1):85-94
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.
6.Parkinsonism in Cerebral Autosomal Dominant Arteriopathy With Subcortical Infarcts and Leukoencephalopathy: Clinical Features and Biomarkers
Chih-Hao CHEN ; Te-Wei WANG ; Yu-Wen CHENG ; Yung-Tsai CHU ; Mei-Fang CHENG ; Ya-Fang CHEN ; Chin-Hsien LIN ; Sung-Chun TANG
Journal of Stroke 2025;27(1):122-127
8.Feline mammary carcinoma‑derived extracellular vesicle promotes liver metastasis via sphingosine kinase‑1‑mediated premetastatic niche formation
Yi‑Chih CHANG ; Hao‑Ping LIU ; Hsiao‑Li CHUANG ; Jiunn‑Wang LIAO ; Pei‑Ling KAO ; Hsun‑Lung CHAN ; Ter‑Hsin CHEN ; Yu‑Chih WANG
Laboratory Animal Research 2023;39(4):329-343
Background:
Feline mammary carcinoma (FMC) is one of the most prevalent malignancies of female cats. FMC is highly metastatic and thus leads to poor disease outcomes. Among all metastases, liver metastasis occurs in about 25% of FMC patients. However, the mechanism underlying hepatic metastasis of FMC remains largely uncharacterized.
Results:
Herein, we demonstrate that FMC-derived extracellular vesicles (FMC-EVs) promotes the liver metastasis of FMC by activating hepatic stellate cells (HSCs) to prime a hepatic premetastatic niche (PMN). Moreover, we provide evidence that sphingosine kinase 1 (SK1) delivered by FMC-EV was pivotal for the activation of HSC and the formation of hepatic PMN. Depletion of SK1 impaired cargo sorting in FMC-EV and the EV-potentiated HSC activation, and abol‑ ished hepatic colonization of FMC cells.
Conclusions
Taken together, our findings uncover a previously uncharacterized mechanism underlying liver-metas‑ tasis of FMC and provide new insights into prognosis and treatment of this feline malignancy.
9.Clinical Outcomes and Cost-Effectiveness of Osteoporosis Screening With Dual-Energy X-ray Absorptiometry
Chiao-Lin HSU ; Pin-Chieh WU ; Chun-Hao YIN ; Chung-Hwan CHEN ; King-Teh LEE ; Chih-Lung LIN ; Hon-Yi SHI
Korean Journal of Radiology 2023;24(12):1249-1259
Objective:
This study aimed to evaluate the clinical outcomes and cost-effectiveness of dual-energy X-ray absorptiometry (DXA) for osteoporosis screening.
Materials and Methods:
Eligible patients who had and had not undergone DXA screening were identified from among those aged 50 years or older at Kaohsiung Veterans General Hospital, Taiwan. Age, sex, screening year (index year), and Charlson comorbidity index of the DXA and non-DXA groups were matched using inverse probability of treatment weighting (IPTW) for propensity score analysis. For cost-effectiveness analysis, a societal perspective, 1-year cycle length, 20-year time horizon, and discount rate of 2% per year for both effectiveness and costs were adopted in the incremental cost-effectiveness (ICER) model.
Results:
The outcome analysis included 10337 patients (female:male, 63.8%:36.2%) who were screened for osteoporosis in southern Taiwan between January 1, 2012, and December 31, 2021. The DXA group had significantly better outcomes than the non-DXA group in terms of fragility fractures (7.6% vs. 12.5%, P < 0.001) and mortality (0.6% vs. 4.3%, P < 0.001). The DXA screening strategy gained an ICER of US$ -2794 per quality-adjusted life year (QALY) relative to the non-DXA at the willingness-to-pay threshold of US$ 33004 (Taiwan’s per capita gross domestic product). The ICER after stratifying by ages of 50–59, 60–69, 70–79, and ≥ 80 years were US$ -17815, US$ -26862, US$ -28981, and US$ -34816 per QALY, respectively.
Conclusion
Using DXA to screen adults aged 50 years or older for osteoporosis resulted in a reduced incidence of fragility fractures, lower mortality rate, and reduced total costs. Screening for osteoporosis is a cost-saving strategy and its effectiveness increases with age. However, caution is needed when generalizing these cost-effectiveness results to all older populations because the study population consisted mainly of women.
10.Management of Hyperacute Stroke during the Coronavirus Disease of 2019 Pandemic: The Modified Code Stroke in a Medical Center in Taiwan
Po-Yu LIN ; Yu-Ming CHANG ; Chih-Yuan HUANG ; Chih-Hao LIN ; Ming-Tsung CHUANG ; Po-Lin CHEN ; Pi-Shan SUNG ; Chih-Hung CHEN
Journal of Stroke 2020;22(2):278-281

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