Background: and Purpose An intracranial vertebral artery dissecting aneurysm (iVADA) increases the risk of future subarachnoid hemorrhage, which is a severe complication with high rebleeding rates and poor outcomes. Identifying potential risk factors associated with iVADA growth is crucial for their effective management. Methods: This observational study was carried out at a single center and included patients who had been diagnosed with iVADA based on neuroimaging findings. We divided the patients into two groups: with and without iVADA growth. Growth was defined as any enlargement of a dilated region or a morphological change in follow-up imaging. We measured the vertebral artery tortuosity index (VTI) in the contralateral vertebral artery (VA), defined as its actual length divided by its straight length. We investigated the factors associated with iVADA growth. Results: This study included 124 patients. The median follow-up period was 7 months. We observed iVADA growth in 54 patients (43.5%), who were more likely to be current smokers (33.3% vs. 14.3%, p=0.012) and have a higher VTI (1.14±0.11 [mean±standard deviation] vs.1.06±0.12, p=0.035) compared with those without iVADA growth. A multivariate analysis revealed that the VTI (adjusted odds ratio=28.490, 95% confidence interval=1.025–792.046, p=0.048) was independently associated with iVADA growth. Conclusions This study has identified an independent association between VA tortuosity and iVADA growth.

Background: and Purpose An intracranial vertebral artery dissecting aneurysm (iVADA) increases the risk of future subarachnoid hemorrhage, which is a severe complication with high rebleeding rates and poor outcomes. Identifying potential risk factors associated with iVADA growth is crucial for their effective management. Methods: This observational study was carried out at a single center and included patients who had been diagnosed with iVADA based on neuroimaging findings. We divided the patients into two groups: with and without iVADA growth. Growth was defined as any enlargement of a dilated region or a morphological change in follow-up imaging. We measured the vertebral artery tortuosity index (VTI) in the contralateral vertebral artery (VA), defined as its actual length divided by its straight length. We investigated the factors associated with iVADA growth. Results: This study included 124 patients. The median follow-up period was 7 months. We observed iVADA growth in 54 patients (43.5%), who were more likely to be current smokers (33.3% vs. 14.3%, p=0.012) and have a higher VTI (1.14±0.11 [mean±standard deviation] vs.1.06±0.12, p=0.035) compared with those without iVADA growth. A multivariate analysis revealed that the VTI (adjusted odds ratio=28.490, 95% confidence interval=1.025–792.046, p=0.048) was independently associated with iVADA growth. Conclusions This study has identified an independent association between VA tortuosity and iVADA growth.

Background: and Purpose An intracranial vertebral artery dissecting aneurysm (iVADA) increases the risk of future subarachnoid hemorrhage, which is a severe complication with high rebleeding rates and poor outcomes. Identifying potential risk factors associated with iVADA growth is crucial for their effective management. Methods: This observational study was carried out at a single center and included patients who had been diagnosed with iVADA based on neuroimaging findings. We divided the patients into two groups: with and without iVADA growth. Growth was defined as any enlargement of a dilated region or a morphological change in follow-up imaging. We measured the vertebral artery tortuosity index (VTI) in the contralateral vertebral artery (VA), defined as its actual length divided by its straight length. We investigated the factors associated with iVADA growth. Results: This study included 124 patients. The median follow-up period was 7 months. We observed iVADA growth in 54 patients (43.5%), who were more likely to be current smokers (33.3% vs. 14.3%, p=0.012) and have a higher VTI (1.14±0.11 [mean±standard deviation] vs.1.06±0.12, p=0.035) compared with those without iVADA growth. A multivariate analysis revealed that the VTI (adjusted odds ratio=28.490, 95% confidence interval=1.025–792.046, p=0.048) was independently associated with iVADA growth. Conclusions This study has identified an independent association between VA tortuosity and iVADA growth.

Background: and Purpose The accurate prediction of functional outcomes in patients with acute ischemic stroke (AIS) is crucial for informed clinical decision-making and optimal resource utilization. As such, this study aimed to construct an ensemble deep learning model that integrates multimodal imaging and clinical data to predict the 90-day functional outcomes after AIS. Methods: We used data from the Korean Stroke Neuroimaging Initiative database, a prospective multicenter stroke registry to construct an ensemble model integrated individual 3D convolutional neural networks for diffusion-weighted imaging and fluid-attenuated inversion recovery (FLAIR), along with a deep neural network for clinical data, to predict 90-day functional independence after AIS using a modified Rankin Scale (mRS) of 3–6. To evaluate the performance of the ensemble model, we compared the area under the curve (AUC) of the proposed method with that of individual models trained on each modality to identify patients with AIS with an mRS score of 3–6. Results: Of the 2,606 patients with AIS, 993 (38.1%) achieved an mRS score of 3–6 at 90 days post-stroke. Our model achieved AUC values of 0.830 (standard cross-validation [CV]) and 0.779 (time-based CV), which significantly outperformed the other models relying on single modalities: b-value of 1,000 s/mm2 (P<0.001), apparent diffusion coefficient map (P<0.001), FLAIR (P<0.001), and clinical data (P=0.004). Conclusion The integration of multimodal imaging and clinical data resulted in superior prediction of the 90-day functional outcomes in AIS patients compared to the use of a single data modality.

Objectives: Limited information is available concerning the epidemiology of stroke and acute myocardial infarction (AMI) in the Republic of Korea. This study aimed to develop a national surveillance system to monitor the incidence of stroke and AMI using national claims data. Methods: We developed and validated identification algorithms for stroke and AMI using claims data. This validation involved a 2-stage stratified sampling method with a review of medical records for sampled cases. The weighted positive predictive value (PPV) and negative predictive value (NPV) were calculated based on the sampling structure and the correspondingsampling rates. Incident cases and the incidence rates of stroke and AMI in the Republic ofKorea were estimated by applying the algorithms and weighted PPV and NPV to the 2018National Health Insurance Service claims data. Results: In total, 2,200 cases (1,086 stroke cases and 1,114 AMI cases) were sampled from the 2018 claims database. The sensitivity and specificity of the algorithms were 94.3% and 88.6% for stroke and 97.9% and 90.1% for AMI, respectively. The estimated number of cases, including recurrent events, was 150,837 for stroke and 40,529 for AMI in 2018. The age- and sex-standardized incidence rate for stroke and AMI was 180.2 and 46.1 cases per 100,000 person-years, respectively, in 2018. Conclusion This study demonstrates the feasibility of developing a national surveillance system based on claims data and identification algorithms for stroke and AMI to monitor their incidence rates.

Background: and Purpose We investigated the impact of comorbidity burden on troponin elevation, with separate consideration of neurological conditions, in patients with acute ischemic stroke (AIS). Methods: This prospective, observational cohort study consecutively enrolled patients with AIS for 2 years. Serum cardiac troponin I was repeatedly measured, and disease-related biomarkers were collected for diagnosis of preassigned comorbidities, including atrial fibrillation (AF), ischemic heart disease (IHD), myocardial hypertrophy (MH), heart failure (HF), renal insufficiency (RI), and active cancer. The severity of neurological deficits and insular cortical ischemic lesions were assessed as neurological conditions. Adjusted associations between these factors and troponin elevation were determined using a multivariate ordinal logistic regression model and area under the receiver operating characteristic curve (AUC). Cox proportional hazards model was used to determine the prognostic significance of comorbidity beyond neurological conditions. Results: Among 1,092 patients (66.5±12.4 years, 63.3% male), 145 (13.3%) and 335 (30.7%) had elevated (≥0.040 ng/mL) and minimally-elevated (0.040–0.010 ng/mL) troponin, respectively. In the adjusted analysis, AF, MH, HF, RI, active cancer, and neurological deficits were associated with troponin elevation. The multivariate model with six comorbidities and two neurological conditions exhibited an AUC of 0.729 (95% confidence interval [CI], 0.698–0.759). In Cox regression, AF, IHD, and HF were associated with adverse cardio-cerebrovascular events, whereas HF and active cancer were associated with mortality. Conclusion Troponin elevation in patients with AIS can be explained by the burden of comorbidities in combination with neurological status, which explains the prognostic significance of troponin assay.