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: Prior studies have shown that drivers with type 2 diabetes are more likely to be involved in motor vehicle collisions (MVCs) compared to the general population. Certain meteorological factors have been increasingly recognized as contributors to MVC risk. This study aims to examine the association of MVCs with temperature, rainfall, wind speed, and sunshine duration among drivers with type 2 diabetes. METHODS: Using Taiwan's National Health Insurance data (2019-2021), we identified individuals diagnosed with type 2 diabetes and linked their records to the Police-Reported Traffic Accident Registry to obtain daily MVC counts. Meteorological data were sourced from the Central Weather Administration. Associations between daily weather conditions and MVCs were assessed using a Distributed Lag Non-Linear Model. RESULTS: Over the 1,096-day study period, 170,468 MVC events involving drivers with type 2 diabetes were recorded. A U-shaped association was observed between same-day temperature and MVC rates. Compared with the reference temperature of 17.5 °C, both lower temperatures (≤15 °C; rate ratio [RR] = 1.014-1.053) and higher temperatures (≥30 °C; RR = 1.062) were associated with increased MVC risk. Rainfall showed an inverse relationship with MVCs. Compared with 70 mm of rainfall, the lowest MVC rate occurred at 129 mm (RR = 0.873), while the highest was on rain-free days (0 mm; RR = 1.068). Stronger effects were observed when lag periods up to 14 days were considered. Wind speed and sunshine duration were not significantly associated with MVC risk. CONCLUSIONS These findings suggest that drivers with type 2 diabetes should exercise greater caution on days with extreme temperatures or in days with lesser rainfall, as these conditions may elevate MVC risk.
Humans ; Diabetes Mellitus, Type 2/epidemiology* ; Taiwan/epidemiology* ; Accidents, Traffic/statistics & numerical data* ; Male ; Middle Aged ; Female ; Weather ; Aged ; Adult ; Temperature ; Risk Factors

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.