Radiomics using non-contrast CT to predict hemorrhagic transformation risk in stroke patients undergoing revascularization.

OBJECTIVES: This study explores whether textural features from initial non-contrast CT scans of infarcted brain tissue are linked to hemorrhagic transformation susceptibility. MATERIALS AND METHODS: Stroke patients undergoing thrombolysis or thrombectomy from Jan 2012 to Jan 2022 were analyzed retrospectively. Hemorrhagic transformation was defined using follow-up magnetic resonance imaging. A total of 94 radiomic features were extracted from the infarcted tissue on initial NCCT scans. Patients were divided into training and test sets (7:3 ratio). Two models were developed with fivefold cross-validation: one incorporating first-order and textural radiomic features, and another using only textural radiomic features. A clinical model was also constructed using logistic regression with clinical variables, and test set validation was performed. RESULTS: Among 362 patients, 218 had hemorrhagic transformations. The LightGBM model with all radiomics features had the best performance, with an area under the receiver operating characteristic curve (AUROC) of 0.986 (95% confidence interval [CI], 0.971-1.000) on the test dataset. The ExtraTrees model performed best when textural features were employed, with an AUROC of 0.845 (95% CI, 0.774-0.916). Minimum, maximum, and ten percentile values were significant predictors of hemorrhagic transformation. The clinical model showed an AUROC of 0.544 (95% CI, 0.431-0.658). The performance of the radiomics models was significantly better than that of the clinical model on the test dataset (p < 0.001). CONCLUSIONS: The radiomics model can predict hemorrhagic transformation using NCCT in stroke patients. Low Hounsfield unit was a strong predictor of hemorrhagic transformation, while textural features alone can predict hemorrhagic transformation. CLINICAL RELEVANCE STATEMENT: Using radiomic features extracted from initial non-contrast computed tomography, early prediction of hemorrhagic transformation has the potential to improve patient care and outcomes by aiding in personalized treatment decision-making and early identification of at-risk patients. KEY POINTS: • Predicting hemorrhagic transformation following thrombolysis in stroke is challenging since multiple factors are associated. • Radiomics features of infarcted tissue on initial non-contrast CT are associated with hemorrhagic transformation. • Textural features on non-contrast CT are associated with the frailty of the infarcted tissue.

Association between substantia nigra degeneration and functional outcome in patients with basal ganglia infarction.

BACKGROUND AND PURPOSE: Cerebral infarction in the basal ganglia may cause secondary and delayed neuronal degeneration in the substantia nigra (SN). However, the clinical significance of SN degeneration remains poorly understood. METHODS: This retrospective observational study included patients with acute ischemic stroke in the basal ganglia on initial diffusion-weighted imaging who underwent follow-up diffusion-weighted imaging between 4 and 30 days after symptom onset. SN degeneration was defined as a hyperintensity lesion in the SN observed on diffusion-weighted imaging. We compared functional outcomes at 3 months between patients with and without SN degeneration. A poor outcome was defined as a score of 3-6 (functional dependence or death) on the modified Rankin Scale. RESULTS: Of 350 patients with basal ganglia infarction (median age = 74.0 years, 53.7% male), 125 (35.7%) had SN degeneration. The proportion of functional dependence or death was 79.2% (99/125 patients) in patients with SN degeneration, which was significantly higher than that in those without SN degeneration (56.4%, 127/225 patients, p < 0.001). SN degeneration was more frequent in patients with functional dependence or death (99/226 patients, 43.8%) than in those with functional independence (26/124 patients, 21.0%, p < 0.001). Multivariable logistic regression analysis showed a significant association between SN degeneration and functional dependence or death (odds ratio = 2.91, 95% confidence interval = 1.17-7.21, p = 0.021). CONCLUSIONS: The study showed that patients with degeneration of SN were associated with functional dependence or death at 3 months, suggesting that secondary degeneration is a predictor of poor stroke outcomes and a potential therapeutic target.

Coagulation Factor Expression and Composition of Arterial Thrombi in Cancer-Associated Stroke.

BACKGROUND: Cancer is associated with an increased risk of stroke. Tumor cells activate platelets, induce a coagulation cascade, and generate thrombin. The composition of thrombi may reflect the mechanism of thrombosis, aiding the determination of the treatment strategy. Here, we investigated the composition and expression of coagulation factors in the thrombi of patients with cancer-associated stroke. METHODS: Patients with stroke who underwent endovascular thrombectomy between September 2014 and June 2020 and whose cerebral thrombi were obtained were divided into those with cancer-associated stroke (cancer group) and propensity score-matched patients without cancer (control group), using 1:1 matching based on age and sex. Immunohistochemistry was performed of the thrombi, and the composition and expression of coagulation factors were compared between groups. RESULTS: Among the 320 patients who underwent endovascular thrombectomy and who had thrombi obtained, this study included 23 patients with cancer and 23 matched controls. In both groups, the median age was 65 years, and 12 patients (52.2%) were men. Platelet composition was significantly higher in the cancer group than in the control group (median [interquartile range], 51.3% [28.0%-61.4%] versus 9.5% [4.8%-14.0%]; P<0.001). Among coagulation factors, thrombin (26.2% [16.2%-52.7%] versus 4.5% [1.3%-7.2%]; P<0.001) and tissue factors (0.60% [0.34%-2.06%] versus 0.37% [0.22%-0.60%]; P=0.024) were higher and factor X was lower (1.25% [0.39%-3.60%] versus 2.33% [1.67%-4.48%]; P=0.034) in the cancer group. There was a positive correlation between thrombin and platelets in the cancer group (r=0.666; P=0.001) but not in the control group (r=-0.167; P=0.627). CONCLUSIONS: Cerebral thrombi in patients with cancer-associated stroke showed higher proportions of platelets, thrombin, and tissue factors, suggesting their key roles in arterial thrombosis in cancer and providing a therapeutic perspective for preventing stroke in patients with cancer-associated stroke.

Cancer Prediction With Machine Learning of Thrombi From Thrombectomy in Stroke: Multicenter Development and Validation.

BACKGROUND: We aimed to develop and validate machine learning models to diagnose patients with ischemic stroke with cancer through the analysis of histopathologic images of thrombi obtained during endovascular thrombectomy. METHODS: This was a retrospective study using a prospective multicenter registry which enrolled consecutive patients with acute ischemic stroke from South Korea who underwent endovascular thrombectomy. This study included patients admitted between July 1, 2017 and December 31, 2021 from 6 academic university hospitals. Whole-slide scanning was performed for immunohistochemically stained thrombi. Machine learning models were developed using transfer learning with image slices as input to classify patients into 2 groups: cancer group or other determined cause group. The models were developed and internally validated using thrombi from patients of the primary center, and external validation was conducted in 5 centers. The model was also applied to patients with hidden cancer who were diagnosed with cancer within 1 month of their index stroke. RESULTS: The study included 70 561 images from 182 patients in both internal and external datasets (119 patients in internal and 63 in external). Machine learning models were developed for each immunohistochemical staining using antibodies against platelets, fibrin, and erythrocytes. The platelet model demonstrated consistently high accuracy in classifying patients with cancer, with area under the receiver operating characteristic curve of 0.986 (95% CI, 0.983-0.989) during training, 0.954 (95% CI, 0.937-0.972) during internal validation, and 0.949 (95% CI, 0.891-1.000) during external validation. When applied to patients with occult cancer, the model accurately predicted the presence of cancer with high probabilities ranging from 88.5% to 99.2%. CONCLUSIONS: Machine learning models may be used for prediction of cancer as the underlying cause or detection of occult cancer, using platelet-stained immunohistochemical slide images of thrombi obtained during endovascular thrombectomy.

Patent Foramen Ovale and Risk of Recurrence in Stroke of Determined Etiology.

OBJECTIVE: Patent foramen ovale (PFO) is often found in stroke patients with determined etiologies. PFO may be the actual cause of stroke in some of them. We determined whether the risk of recurrent ischemic stroke differs with PFO status in stroke patients with determined etiologies. METHODS: This study included consecutive patients with stroke of determined etiology who underwent transesophageal echocardiography. We compared the rates of recurrent cerebral infarction in patients with versus without PFO, and according to PFO-Associated Stroke Causal Likelihood (PASCAL) classification. RESULTS: Of 2,314 included patients, 827 (35.7%) had PFO. During a median follow-up of 4.4 years, cerebral infarction recurred in 202 (8.7%). In multivariate modified Cox regression analyses, recurrence of infarction did not significantly differ between patients with PFO and those without PFO (hazard ratio [HR] = 0.86, 95% confidence interval [CI] = 0.64-1.17, p = 0.339). Interaction analysis showed a significant effect of PFO in patients aged <65 years (adjusted p for interaction = 0.090). PFO was independently associated with a decreased risk of recurrent infarction in patients younger than 65 years (HR = 0.41, 95% CI = 0.20-0.85, adjusted p = 0.016). Patients with probable PFO-associated stroke on the PASCAL classification had a significantly lower risk of recurrent infarction than those without PFO (HR = 0.31, 95% CI = 0.10-0.97, p = 0.044). INTERPRETATION: Considering the generally low risk of recurrence in PFO-associated stroke, PFO may be the actual cause of stroke in some patients with determined etiologies, especially younger patients or those with PFO features of probable PFO-associated stroke. ANN NEUROL 2022;92:596-606.

Prediction of cerebral hemorrhagic transformation after thrombectomy using a deep learning of dual-energy CT.

OBJECTIVES: To develop and validate a deep learning model for predicting hemorrhagic transformation after endovascular thrombectomy using dual-energy computed tomography (CT). MATERIALS AND METHODS: This was a retrospective study from a prospective registry of acute ischemic stroke. Patients admitted between May 2019 and February 2023 who underwent endovascular thrombectomy for acute anterior circulation occlusions were enrolled. Hemorrhagic transformation was defined using follow-up magnetic resonance imaging or CT. The deep learning model was developed using post-thrombectomy dual-energy CT to predict hemorrhagic transformation within 72 h. Temporal validation was performed with patients who were admitted after July 2022. The deep learning model's performance was compared with a logistic regression model developed from clinical variables using the area under the receiver operating characteristic curve (AUC). RESULTS: Total of 202 patients (mean age 71.4 years ± 14.5 [standard deviation], 92 men) were included, with 109 (54.0%) patients having hemorrhagic transformation. The deep learning model performed consistently well, showing an average AUC of 0.867 (95% confidence interval [CI], 0.815-0.902) upon five-fold cross validation and AUC of 0.911 (95% CI, 0.774-1.000) with the test dataset. The clinical variable model showed an AUC of 0.775 (95% CI, 0.709-0.842) on the training dataset (p < 0.01) and AUC of 0.634 (95% CI, 0.385-0.883) on the test dataset (p = 0.06). CONCLUSION: A deep learning model was developed and validated for prediction of hemorrhagic transformation after endovascular thrombectomy in patients with acute stroke using dual-energy computed tomography. CLINICAL RELEVANCE STATEMENT: This study demonstrates that a convolutional neural network (CNN) can be utilized on dual-energy computed tomography (DECT) for the accurate prediction of hemorrhagic transformation after thrombectomy. The CNN achieves high performance without the need for region of interest drawing. KEY POINTS: • Iodine leakage on dual-energy CT after thrombectomy may be from blood-brain barrier disruption. • A convolutional neural network on post-thrombectomy dual-energy CT enables individualized prediction of hemorrhagic transformation. • Iodine leakage is an important predictor of hemorrhagic transformation following thrombectomy for ischemic stroke.

Intensive vs Conventional Blood Pressure Lowering After Endovascular Thrombectomy in Acute Ischemic Stroke: The OPTIMAL-BP Randomized Clinical Trial.

Importance: Optimal blood pressure (BP) control after successful reperfusion with endovascular thrombectomy (EVT) for patients with acute ischemic stroke is unclear. Objective: To determine whether intensive BP management during the first 24 hours after successful reperfusion leads to better clinical outcomes than conventional BP management in patients who underwent EVT. Design, Setting, and Participants: Multicenter, randomized, open-label trial with a blinded end-point evaluation, conducted across 19 stroke centers in South Korea from June 2020 to November 2022 (final follow-up, March 8, 2023). It included 306 patients with large vessel occlusion acute ischemic stroke treated with EVT and with a modified Thrombolysis in Cerebral Infarction score of 2b or greater (partial or complete reperfusion). Interventions: Participants were randomly assigned to receive intensive BP management (systolic BP target <140 mm Hg; n = 155) or conventional management (systolic BP target 140-180 mm Hg; n = 150) for 24 hours after enrollment. Main Outcomes and Measures: The primary outcome was functional independence at 3 months (modified Rankin Scale score of 0-2). The primary safety outcomes were symptomatic intracerebral hemorrhage within 36 hours and death related to the index stroke within 3 months. Results: The trial was terminated early based on the recommendation of the data and safety monitoring board, which noted safety concerns. Among 306 randomized patients, 305 were confirmed eligible and 302 (99.0%) completed the trial (mean age, 73.0 years; 122 women [40.4%]). The intensive management group had a lower proportion achieving functional independence (39.4%) than the conventional management group (54.4%), with a significant risk difference (-15.1% [95% CI, -26.2% to -3.9%]) and adjusted odds ratio (0.56 [95% CI, 0.33-0.96]; P = .03). Rates of symptomatic intracerebral hemorrhage were 9.0% in the intensive group and 8.1% in the conventional group (risk difference, 1.0% [95% CI, -5.3% to 7.3%]; adjusted odds ratio, 1.10 [95% CI, 0.48-2.53]; P = .82). Death related to the index stroke within 3 months occurred in 7.7% of the intensive group and 5.4% of the conventional group (risk difference, 2.3% [95% CI, -3.3% to 7.9%]; adjusted odds ratio, 1.73 [95% CI, 0.61-4.92]; P = .31). Conclusions and Relevance: Among patients who achieved successful reperfusion with EVT for acute ischemic stroke with large vessel occlusion, intensive BP management for 24 hours led to a lower likelihood of functional independence at 3 months compared with conventional BP management. These results suggest that intensive BP management should be avoided after successful EVT in acute ischemic stroke. Trial Registration: ClinicalTrials.gov Identifier: NCT04205305.

Impact of Renal Function on Short-Term Outcome After Reperfusion Therapy in Patients With Ischemic Stroke.

BACKGROUND: A high and low estimated glomerular filtration rate (eGFR) could affect outcomes after reperfusion therapy for ischemic stroke. This study aimed to determine whether renal function based on eGFR affects mortality risk in patients with ischemic stroke within 6 months following reperfusion therapy. METHODS: This prospective registry-based cohort study included 2266 patients who received reperfusion therapy between January 2000 and September 2019 and were registered in the SECRET (Selection Criteria in Endovascular Thrombectomy and Thrombolytic Therapy) study or the Yonsei Stroke Cohort. A high and low eGFR were based on the Chronic Kidney Disease Epidemiology Collaboration equation and defined, respectively, as the 5th and 95th percentiles of age- and sex-specific eGFR. Occurrence of death within 6 months was compared among the groups according to their eGFR such as low, normal, or high eGFR. RESULTS: Of the 2266 patients, 2051 (90.5%) had a normal eGFR, 110 (4.9%) a low eGFR, and 105 (4.6%) a high eGFR. Patients with high eGFR were younger or less likely to have hypertension, diabetes, or atrial fibrillation than the other groups. Active cancer was more prevalent in the high-eGFR group. During the 6-month follow-up, there were 24 deaths (22.9%) in the high-eGFR group, 37 (33.6%) in the low-eGFR group, and 237 (11.6%) in the normal-eGFR group. After adjusting for variables with P<0.10 in the univariable analysis, 6-month mortality was independently associated with high eGFR (hazard ratio, 2.22 [95% CI, 1.36-3.62]; P=0.001) and low eGFR (HR, 2.29 [95% CI, 1.41-3.72]; P=0.001). These associations persisted regardless of treatment modality or various baseline characteristics. CONCLUSIONS: High eGFR as well as low eGFR were independently associated with 6-month mortality after reperfusion therapy. Kidney function could be considered a prognostic factor in patients with ischemic stroke after reperfusion therapy.

Immediate and Long-Term Outcomes of Reperfusion Therapy in Patients With Cancer.

Background and Purpose: Patients with acute stroke are often accompanied by comorbidities, such as active cancer. However, adequate treatment guidelines are not available for these patients. The purpose of this study was to evaluate the association between cancer and the outcomes of reperfusion therapy in patients with stroke. Methods: We compared treatment outcomes in patients who underwent reperfusion therapy, using a nationwide reperfusion therapy registry. We divided the patients into 3 groups according to cancer activity: active cancer, nonactive cancer, and without a history of cancer. We investigated reperfusion processes, 24-hour neurological improvement, adverse events, 3-month functional outcome, and 6-month survival and related factors after reperfusion therapy. Results: Among 1338 patients who underwent reperfusion therapy, 62 patients (4.6%) had active cancer, 78 patients (5.8%) had nonactive cancer, and 1198 patients (89.5%) had no history of cancer. Of the enrolled patients, 969 patients received intravenous thrombolysis and 685 patients underwent endovascular treatment (316 patients received combined therapy). Patients with active cancer had more comorbidities and experienced more severe strokes; however, they showed similar 24-hour neurological improvement and adverse events, including cerebral hemorrhage, compared with the other groups. Although the functional outcome at 3 months was poorer than the other groups, 36.4% of patients with active cancer showed functional independence. Additionally, 52.9% of the patients with determined stroke etiology showed functional independence despite active cancer. During the 6-month follow-up, 46.6% of patients with active cancer died, and active cancer was independently associated with poor survival (hazard ratio, 3.973 [95% CI, 2.528­6.245]). Conclusions: In patients with active cancer, reperfusion therapy showed similar adverse events and short-term outcomes to that of other groups. While long-term prognosis was worse in the active cancer group than the nonactive cancer groups, not negligible number of patients had good functional outcomes, especially those with determined stroke mechanisms.

The role of cardiac CT throughout the full cardiac cycle in diagnosing patent foramen ovale in patients with acute stroke.

OBJECTIVES: We explored the hypothesis that the diagnostic performance of cardiac computed tomography (CT) throughout the full cardiac cycle would be superior to single-phase CT and comparable to transesophageal echocardiography (TEE) in diagnosing patent foramen ovale (PFO). METHODS AND RESULTS: From May 2011 to April 2015, 978 patients with stroke were diagnosed with PFO by TEE. In patients with stroke, cardiac CT was performed if the patients had more than two cardiovascular risk factors. We prospectively enrolled 70 patients with an indication for cardiac CT. Cardiac CT images were reconstructed at 10% increments of the R-R interval. The sensitivity of cardiac CT throughout the full cardiac cycle in diagnosing PFO was compared to that for TEE and single-phase cardiac CT. To evaluate the specificity of cardiac CT, we analyzed patients without PFO confirmed by TEE who underwent cardiac CT within 1 month of pre-cardiac surgery. Sixty-six patients with cardiac CT and TEE were included in the final analysis. Throughout the full cardiac cycle, cardiac CT had a sensitivity of 89.4% and a specificity of 92.3% in diagnosing PFO, compared to TEE as a reference. PFO was primarily detected in the 60% and 70% intervals in 10-phase reconstructed images. The sensitivity of PFO diagnosis with cardiac CT was 81.8% when analyzing both the 60% and 70% intervals instead of the full cardiac cycle. CONCLUSION: Cardiac CT throughout the full cardiac cycle outperforms single-phase cardiac CT in detecting PFO. Cardiac CT can be used as an alternative method to TEE for detecting PFO in stroke patients. KEY POINTS: • Throughout the full cardiac cycle, cardiac computed tomography (CT) had a sensitivity of 89.4% and a specificity of 92.3% in diagnosing patent foramen ovale (PFO), compared to transesophageal echocardiography. • The sensitivity of diagnosing patent foramen ovale with cardiac CT was 81.8% when analyzing 60% and 70% R-R intervals instead of the full cardiac cycle. • Cardiac CT with retrospective electrocardiographic gating throughout the full cardiac cycle can increase the detectability of PFO, compared to single-phase cardiac CT.

Clinical impact of estradiol/testosterone ratio in patients with acute ischemic stroke.

BACKGROUND: Sex hormones may be associated with a higher incidence of ischemic stroke or stroke-related events. In observational studies, lower testosterone concentrations are associated with infirmity, vascular disease, and adverse cardiovascular risk factors. Currently, female sexual hormones are considered neuroprotective agents. The purpose of this study was to assess the role of sex hormones and the ratio of estradiol/testosterone (E/T) in patients with acute ischemic stroke (AIS). METHODS: Between January 2011 and December 2016, 146 male patients with AIS and 152 age- and sex-matched control subjects were included in this study. Sex hormones, including estradiol, progesterone, and testosterone, were evaluated in the AIS patient and control groups. We analyzed the clinical and physiological levels of sex hormones and hormone ratios in these patients. RESULTS: The E/T ratio was significantly elevated among patients in the stroke group compared to those in the control group (P = 0.001). Categorization of data into tertiles revealed that patients with the highest E/T ratio were more likely to have AIS [odds ratio (OR) 3.084; 95% Confidence interval (CI): 1.616-5.886; P < 0.001) compared with those in the first tertile. The E/T ratio was also an independent unfavorable outcome predictor with an adjusted OR of 1.167 (95% CI: 1.053-1.294; P = 0.003). CONCLUSIONS: These findings support the hypothesis that increased estradiol and reduced testosterone levels are associated with AIS in men.

Cilostazol Versus Aspirin in Ischemic Stroke Patients With High-Risk Cerebral Hemorrhage: Subgroup Analysis of the PICASSO Trial.

Background and Purpose- Although cilostazol has shown less hemorrhagic events than aspirin, only marginal difference was observed in hemorrhagic stroke events among patients at high risk for cerebral hemorrhage. To identify patients who would most benefit from cilostazol, this study analyzed interactions between treatment and subgroups of the PICASSO trial (Prevention of Cardiovascular Events in Asian Ischemic Stroke Patients With High Risk of Cerebral Hemorrhage). Methods- Ischemic stroke patients with a previous intracerebral hemorrhage or multiple microbleeds were randomized to treatment with cilostazol or aspirin and followed up for a mean 1.8 years. Efficacy, defined as the composite of any stroke, myocardial infarction, and vascular death, and safety, defined as the incidence of hemorrhagic stroke, were analyzed in the 2 groups. Interactions between treatment and age, sex, presence of hypertension and diabetes mellitus, index of high-risk cerebral hemorrhage, and white matter lesion burden were analyzed for primary and key secondary outcomes. Changes in vital signs and laboratory results were compared in the 2 groups. Results- Among all 1534 patients enrolled, a significant interaction between treatment group and index of high risk for cerebral hemorrhage on hemorrhagic stroke (P for interaction, 0.03) was observed. Hemorrhagic stroke was less frequent in the cilostazol than in the aspirin group in patients with multiple microbleeds (1 versus 13 events; hazard ratio, 0.08 [95% CI, 0.01-0.61]; P=0.01). A marginal interaction between treatment group and white matter change on any stroke (P for interaction, 0.08) was observed. Cilostazol reduced any stroke significantly in patients with mild (5 versus 16 events; hazard ratio, 0.36 [95% CI, 0.13-0.97]; P=0.04)-to-moderate (16 versus 32 events; hazard ratio, 0.50 [95% CI, 0.29-0.92]; P=0.03) white matter changes. Heart rate and HDL (high-density lipoprotein) cholesterol level were significantly higher in the cilostazol group than in the aspirin group at follow-up. Conclusions- Cilostazol may be more beneficial for ischemic stroke patients with multiple cerebral microbleeds and before white matter changes are extensive. Registration- URL: https://www.clinicaltrials.gov. Unique identifier: NCT01013532.

Nonalcoholic Fatty Liver Disease and Sarcopenia Are Independently Associated With Cardiovascular Risk.

OBJECTIVES: Nonalcoholic fatty liver disease (NAFLD) and sarcopenia have a close association with an increased risk of atherosclerotic cardiovascular disease (ASCVD). This study investigated the influence of NAFLD and sarcopenia on ASCVD risk. METHODS: Data from the 2008-2011 Korean National Health and Nutrition Examination Surveys database were analyzed (n = 7,191). The sarcopenia index was calculated using dual-energy x-ray absorptiometry. Sarcopenia was defined as the lowest quintile sarcopenia index value (cutoffs = 0.882 for men and 0.582 for women). NAFLD was defined as a comprehensive NAFLD score ≥40. Liver fibrosis was assessed using the fibrosis-4 (FIB-4) index. ASCVD risk was evaluated using American College of Cardiology/American Heart Association guidelines. High probability of ASCVD was defined as ASCVD risk >10%. RESULTS: The prevalence rates of NAFLD and sarcopenia were 31.2% (n = 2,241) and 19.5% (n = 1,400), respectively. The quartile-stratified ASCVD risk scores were positively associated with NAFLD and sarcopenia (all P for trend < 0.001). Subjects with both NAFLD and sarcopenia had a higher risk for high probability of ASCVD (odds ratio = 1.83, P = 0.014) compared with controls without NAFLD and sarcopenia. Among subjects with NAFLD, FIB-4-defined significant liver fibrosis and sarcopenia additively raised the risk for high probability of ASCVD (odds ratio = 3.56, P < 0.001) compared with controls without FIB-4-defined significant liver fibrosis or sarcopenia. DISCUSSION: NAFLD and sarcopenia were significantly associated with an increased risk of ASCVD in the general population. In addition, NAFLD with significant liver fibrosis and sarcopenia were significantly associated with an increased risk of ASCVD in subjects with NAFLD.

Histological features of intracranial thrombi in stroke patients with cancer.

The histological features of thrombus in stroke patients with cancer are not well known. Using immunohistochemical staining of thrombi retrieved during mechanical thrombectomy in stroke patients, thrombus compositions were compared between 16 patients with active cancer, 16 patients with inactive cancer, and 16 patients without any history of cancer. The active cancer group showed higher platelet and lower erythrocyte fractions than the inactive cancer or the control group. Four patients with vegetation showed very high platelet and low erythrocyte fractions. Patients with cryptogenic etiology in the active cancer group showed a similar pattern to those with vegetation. These findings may aid the determination of treatment strategies in cancer-associated stroke. ANN NEUROL 2019.

Advanced Liver Fibrosis Predicts Unfavorable Long-Term Prognosis in First-Ever Ischemic Stroke or Transient Ischemic Attack.

INTRODUCTION: There are a limited number of studies investigating the relationship between the degree of liver fibrosis and the long-term prognosis, especially ischemic stroke (IS) recurrence, in first-ever IS or transient ischemic attack (TIA). OBJECTIVE: We investigated whether there are differences in the long-term all-cause and cardiovascular mortalities and IS recurrence based on the degree of liver fibrosis in first-ever IS or TIA. METHODS: This analysis included 2,504 patients with first-ever IS or TIA recruited from a prospective stroke cohort. Liver fibrosis was predicted using the fibrosis-4 (FIB-4) index, and advanced fibrosis was defined as an FIB-4 index of >3.25. Using Cox regression models, we compared the all-cause and cardiovascular mortalities and IS recurrence. As measures for the additive predictive value of the FIB-4 index for prediction of all-cause mortality, the integrated area under the receiver operating characteristic curve (iAUC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI) were used. RESULTS: There were 231 (9.2%) patients with advanced fibrosis. During a median follow-up of 1.2 years, the cumulative all-cause and cardiovascular mortalities were 6.4 and 1.9%, and IS recurrence was observed in 5.3%. The advanced fibrosis was associated with an increased risk of all-cause mortality (hazard ratio [HR] = 3.98, 95% confidence interval [CI] = 2.40-6.59), cardiovascular mortality (HR = 4.48, 95% CI = 1.59-12.65), and IS recurrence (HR = 1.95, 95% CI = 1.05-3.65). Adding the FIB-4 index to the model consisting of traditional cardiovascular risk factors improved the predictive accuracy for all-cause mortality as measured using the iAUC (from 0.7594 to 0.7729) and for all-cause mortality at 1 year as measured using the NRI (38.6%) and IDI (0.037). CONCLUSIONS: The burden of liver fibrosis is associated with unfavorable long-term prognosis, including recurrent IS, in first-ever IS or TIA.

Automatic Grading of Stroke Symptoms for Rapid Assessment Using Optimized Machine Learning and 4-Limb Kinematics: Clinical Validation Study.

BACKGROUND: Subtle abnormal motor signs are indications of serious neurological diseases. Although neurological deficits require fast initiation of treatment in a restricted time, it is difficult for nonspecialists to detect and objectively assess the symptoms. In the clinical environment, diagnoses and decisions are based on clinical grading methods, including the National Institutes of Health Stroke Scale (NIHSS) score or the Medical Research Council (MRC) score, which have been used to measure motor weakness. Objective grading in various environments is necessitated for consistent agreement among patients, caregivers, paramedics, and medical staff to facilitate rapid diagnoses and dispatches to appropriate medical centers. OBJECTIVE: In this study, we aimed to develop an autonomous grading system for stroke patients. We investigated the feasibility of our new system to assess motor weakness and grade NIHSS and MRC scores of 4 limbs, similar to the clinical examinations performed by medical staff. METHODS: We implemented an automatic grading system composed of a measuring unit with wearable sensors and a grading unit with optimized machine learning. Inertial sensors were attached to measure subtle weaknesses caused by paralysis of upper and lower limbs. We collected 60 instances of data with kinematic features of motor disorders from neurological examination and demographic information of stroke patients with NIHSS 0 or 1 and MRC 7, 8, or 9 grades in a stroke unit. Training data with 240 instances were generated using a synthetic minority oversampling technique to complement the imbalanced number of data between classes and low number of training data. We trained 2 representative machine learning algorithms, an ensemble and a support vector machine (SVM), to implement auto-NIHSS and auto-MRC grading. The optimized algorithms performed a 5-fold cross-validation and were searched by Bayes optimization in 30 trials. The trained model was tested with the 60 original hold-out instances for performance evaluation in accuracy, sensitivity, specificity, and area under the receiver operating characteristics curve (AUC). RESULTS: The proposed system can grade NIHSS scores with an accuracy of 83.3% and an AUC of 0.912 using an optimized ensemble algorithm, and it can grade with an accuracy of 80.0% and an AUC of 0.860 using an optimized SVM algorithm. The auto-MRC grading achieved an accuracy of 76.7% and a mean AUC of 0.870 in SVM classification and an accuracy of 78.3% and a mean AUC of 0.877 in ensemble classification. CONCLUSIONS: The automatic grading system quantifies proximal weakness in real time and assesses symptoms through automatic grading. The pilot outcomes demonstrated the feasibility of remote monitoring of motor weakness caused by stroke. The system can facilitate consistent grading with instant assessment and expedite dispatches to appropriate hospitals and treatment initiation by sharing auto-MRC and auto-NIHSS scores between prehospital and hospital responses as an objective observation.

Non-vitamin K oral anticoagulants as first-line regimen for acute ischemic stroke with non-valvular atrial fibrillation.

PURPOSE: There are various patterns in determining the choice of the first-line antithrombotic agent for acute stroke with non-valvular atrial fibrillation. We investigated the efficacy and safety of non-vitamin K oral anticoagulants as first-line antithrombotics for patients with acute stroke and non-valvular atrial fibrillation. MATERIALS AND METHODS: Patients with non-valvular atrial fibrillation and ischemic stroke or transient ischemic attack within 24 h from stroke onset were included. On the basis of the first regimen used and the regimen within 7 days after admission, the study population was divided into three groups: 1) antiplatelet switched to warfarin (A-W), 2) antiplatelet switched to NOAC (A-N), and 3) NOAC only (N only). We compared the occurrence of early neurologic deterioration, symptomatic intracranial hemorrhage, systemic bleeding, and poor functional outcome at 90 days. RESULTS: Of 314 included patients, 164, 53, and 97 were classified into the A-W, A-N, and N only groups, respectively. Early neurologic deterioration was most frequently observed in the A-W group (9.1%), followed by the A-N (5.7%) and N only (1.0%) groups (p = 0.017). Multivariable analysis adjusting for potential confounders demonstrated that the N only group was independently associated with a lower rate of early neurologic deterioration (odds ratio [OR] 0.104, 95% CI 0.013-0.831) or poor functional outcome at 90 days (OR 0.450, 95% CI 0.215-0.940) than the A-W group. However, the rate of symptomatic intracranial hemorrhage or any systemic bleeding event did not differ among the groups. CONCLUSION: Using non-vitamin K oral anticoagulants as the first-line regimen for acute ischemic stroke may help prevent early neurologic deterioration without increasing the bleeding risk.

Short-Term Outcome of Ischemic Stroke Patients With Systemic Malignancy.

Background and Purpose- Recent guidelines have suggested the potential benefit of intravenous thrombolysis in stroke patients with systemic malignancy who have a reasonable life expectancy of >6 months. However, it is difficult to determine which patients with cancer will have a life expectancy of >6 months. Therefore, we identified the factors associated with 6-month mortality in patients with acute ischemic stroke and systemic malignancy. Methods- Consecutive stroke patients with systemic malignancy were retrospectively analyzed. We classified the patients into 3 groups: the nonactive cancer, active nonmetastatic cancer, and metastatic cancer groups. We compared the baseline characteristics and 6-month survival rates. Results- Of the 468 ischemic stroke patients with systemic malignancy during an 8-year period, 223 patients had nonactive cancer, 105 patients had active nonmetastatic cancer, and 140 patients had metastasis. During the 6-month follow-up, 122 patients (26.1%) died (nonactive cancer group [7.2%, 16/223], active nonmetastatic cancer group [11.4%, 12/105], and metastatic cancer group [67.1%, 94/140]). Multivariate Cox regression analysis revealed that the presence of metastasis (hazard ratio, 4.527; 95% CI, 2.175-9.422) was independently associated with 6-month mortality. However, the active nonmetastatic cancer group exhibited similar 6-month mortality to the nonactive cancer group (hazard ratio, 0.711; 95% CI, 0.282-1.795). Gastric/esophageal cancer and pancreatic cancer were also independently associated with 6-month mortality (hazard ratio, 2.068 and 2.389, respectively). Conclusions- In stroke patients with active cancer, the presence of metastasis and the cancer type were crucial factors associated with 6-month mortality.

Machine Learning-Based Model for Prediction of Outcomes in Acute Stroke.

Background and Purpose- The prediction of long-term outcomes in ischemic stroke patients may be useful in treatment decisions. Machine learning techniques are being increasingly adapted for use in the medical field because of their high accuracy. This study investigated the applicability of machine learning techniques to predict long-term outcomes in ischemic stroke patients. Methods- This was a retrospective study using a prospective cohort that enrolled patients with acute ischemic stroke. Favorable outcome was defined as modified Rankin Scale score 0, 1, or 2 at 3 months. We developed 3 machine learning models (deep neural network, random forest, and logistic regression) and compared their predictability. To evaluate the accuracy of the machine learning models, we also compared them to the Acute Stroke Registry and Analysis of Lausanne (ASTRAL) score. Results- A total of 2604 patients were included in this study, and 2043 (78%) of them had favorable outcomes. The area under the curve for the deep neural network model was significantly higher than that of the ASTRAL score (0.888 versus 0.839; P<0.001), while the areas under the curves of the random forest (0.857; P=0.136) and logistic regression (0.849; P=0.413) models were not significantly higher than that of the ASTRAL score. Using only the 6 variables that are used for the ASTRAL score, the performance of the machine learning models did not significantly differ from that of the ASTRAL score. Conclusions- Machine learning algorithms, particularly the deep neural network, can improve the prediction of long-term outcomes in ischemic stroke patients.

Effect of Cumulative Case Volume on Procedural and Clinical Outcomes in Endovascular Thrombectomy.

Background and Purpose- The effect of endovascular thrombectomy (EVT) cumulative case volume (EVT-CCV) on outcomes of acute stroke patients has not been studied. This study investigated whether EVT-CCV was associated with outcomes. Methods- We identified all patients who underwent EVT for anterior circulation large vessel occlusion. Patients who met enrollment criteria were grouped into 5 based on the number of previous cases at each hospital. The number of cases that were recruited from each hospital and then assigned to each group (n) was designed to increase by the function of 10×2(n-1); group 1 consisted of cases 1 to 10 at each hospital, group 2 was cases 11 to 30, group 3 was cases 31 to 70, group 4 was cases 71 to 150, and group 5 was cases ≥151. We tested whether EVT-CCV group was associated with procedural and clinical outcomes. Results- Nine hundred fifty-five patients fulfilled the enrollment criteria. Recanalization and good outcome positively correlated with EVT-CCV group ( P<0.001 [correlation coefficient, r=0.122] for recanalization; P=0.002 [ r=0.099] for good outcome), whereas symptomatic intracranial hemorrhage and mortality negatively correlated ( P=0.039 [ r=-0.067] for symptomatic intracranial hemorrhage; P=0.016 [ r=-0.078] for mortality). EVT-CCV group was independently associated with recanalization (odds ratio, 1.182; 95% CI, 1.029-1.358) and good outcome (odds ratio, 1.187; 95% CI, 1.053-1.337). Conclusions- With increased EVT-CCV, recanalization and good outcome increased, whereas symptomatic intracranial hemorrhage and mortality decreased. Increased EVT-CCV was independently associated with recanalization and good outcome.