Functional Outcomes Associated With Blood Pressure Decrease After Endovascular Thrombectomy.

Importance: The associations between blood pressure (BP) decreases induced by medication and functional outcomes in patients with successful endovascular thrombectomy remain uncertain. Objective: To evaluate whether BP reductions induced by intravenous BP medications are associated with poor functional outcomes at 3 months. Design, Setting, and Participants: This cohort study was a post hoc analysis of the Outcome in Patients Treated With Intra-Arterial Thrombectomy-Optimal Blood Pressure Control trial, a comparison of intensive and conventional BP management during the 24 hours after successful recanalization from June 18, 2020, to November 28, 2022. This study included 302 patients who underwent endovascular thrombectomy, achieved successful recanalization, and exhibited elevated BP within 2 hours of successful recanalization at 19 stroke centers in South Korea. Exposure: A BP decrease was defined as at least 1 event of systolic BP less than 100 mm Hg. Patients were divided into medication-induced BP decrease (MIBD), spontaneous BP decrease (SpBD), and no BP decrease (NoBD) groups. Main Outcomes and Measures: The primary outcome was a modified Rankin scale score of 0 to 2 at 3 months, indicating functional independence. Primary safety outcomes were symptomatic intracerebral hemorrhage within 36 hours and mortality due to index stroke within 3 months. Results: Of the 302 patients (median [IQR] age, 75 [66-82] years; 180 [59.6%] men), 47 (15.6%)were in the MIBD group, 39 (12.9%) were in the SpBD group, and 216 (71.5%) were in the NoBD group. After adjustment for confounders, the MIBD group exhibited a significantly smaller proportion of patients with functional independence at 3 months compared with the NoBD group (adjusted odds ratio [AOR], 0.45; 95% CI, 0.20-0.98). There was no significant difference in functional independence between the SpBD and NoBD groups (AOR, 1.41; 95% CI, 0.58-3.49). Compared with the NoBD group, the MIBD group demonstrated higher odds of mortality within 3 months (AOR, 5.15; 95% CI, 1.42-19.4). The incidence of symptomatic intracerebral hemorrhage was not significantly different among the groups (MIBD vs NoBD: AOR, 1.89; 95% CI, 0.54-5.88; SpBD vs NoBD: AOR, 2.75; 95% CI, 0.76-9.46). Conclusions and Relevance: In this cohort study of patients with successful endovascular thrombectomy after stroke, MIBD within 24 hours after successful recanalization was associated with poor outcomes at 3 months. These findings suggested lowering systolic BP to below 100 mm Hg using BP medication might be harmful.

Long-term outcomes of patients with embolic stroke of undetermined source according to subtype.

The prognosis of patients with embolic stroke of undetermined source (ESUS) may vary according to the underlying cause. Therefore, we aimed to divide ESUS into subtypes and assess the long-term outcomes. Consecutive patients with acute ischemic stroke who underwent a comprehensive workup, including transesophageal echocardiography and prolonged electrocardiography monitoring, were enrolled. We classified ESUS into minor cardioembolic (CE) ESUS, arteriogenic ESUS, two or more causes ESUS, and no cause ESUS. Arteriogenic ESUS was sub-classified into complex aortic plaque (CAP) ESUS and non-stenotic (< 50%) relevant artery plaque (NAP) ESUS. A total of 775 patients were enrolled. During 1286 ± 748 days follow-up, 116 major adverse cardiovascular events (MACE) occurred (4.2 events/100 patient-years). Among the ESUS subtypes, CAP ESUS was associated with the highest MACE frequency (9.7/100 patient-years, p = 0.021). Cox regression analyses showed that CAP ESUS was associated with MACE (hazard ratio 2.466, 95% confidence interval 1.305-4.660) and any stroke recurrence (hazard ratio 2.470, 95% confidence interval, 1.108-5.508). The prognosis of ESUS varies according to the subtype, with CAP ESUS having the worst prognosis. Categorizing ESUS into subtypes could improve patient care and refine clinical trials.

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.

Effectiveness of endovascular treatment for in-hospital stroke vs. community-onset stroke: a propensity score-matched analysis.

BACKGROUND: The effectiveness of endovascular treatment for in-hospital stroke remains debatable. We aimed to compare the outcomes between patients with in-hospital stroke and community-onset stroke who received endovascular treatment. METHODS: This prospective registry-based cohort study included consecutive patients who underwent endovascular treatment from January 2013 to December 2022 and were registered in the Selection Criteria in Endovascular Thrombectomy and Thrombolytic Therapy study and Yonsei Stroke Cohort. Functional outcomes at day 90, radiological outcomes, and safety outcomes were compared between the in-hospital and community-onset groups using logistic regression and propensity score-matched analysis. RESULTS: Of 1,219 patients who underwent endovascular treatment, 117 (9.6%) had in-hospital stroke. Patients with in-hospital onset were more likely to have a pre-stroke disability and active cancer than those with community-onset. The interval from the last known well to puncture was shorter in the in-hospital group than in the community-onset group (155 vs. 355 min, p<0.001). No significant differences in successful recanalization or safety outcomes were observed between the groups; however, the in-hospital group exhibited worse functional outcomes and higher mortality at day 90 than the community-onset group (all p<0.05). After propensity score matching including baseline characteristics, functional outcomes after endovascular treatment did not differ between the groups (OR: 1.19, 95% CI 0.78-1.83, p=0.4). Safety outcomes did not significantly differ between the groups. CONCLUSION: Endovascular treatment is a safe and effective treatment for eligible patients with in-hospital stroke. Our results will help physicians in making decisions when planning treatment and counseling caregivers or patients.

Combined use of anticoagulant and antiplatelet on outcome after stroke in patients with nonvalvular atrial fibrillation and systemic atherosclerosis.

This study aimed to investigate whether there was a difference in one-year outcome after stroke between patients treated with antiplatelet and anticoagulation (OAC + antiplatelet) and those with anticoagulation only (OAC), when comorbid atherosclerotic disease was present with non-valvular atrial fibrillation (NVAF). This was a retrospective study using a prospective cohort of consecutive patients with ischemic stroke. Patients with NVAF and comorbid atherosclerotic disease were assigned to the OAC + antiplatelet or OAC group based on discharge medication. All-cause mortality, recurrent ischemic stroke, hemorrhagic stroke, myocardial infarction, and bleeding events within 1 year after the index stroke were compared. Of the 445 patients included in this study, 149 (33.5%) were treated with OAC + antiplatelet. There were no significant differences in all outcomes between groups. After inverse probability of treatment weighting, OAC + antiplatelet was associated with a lower risk of all-cause mortality (hazard ratio 0.48; 95% confidence interval 0.23-0.98; P = 0.045) and myocardial infarction (0% vs. 3.0%, P < 0.001). The risk of hemorrhagic stroke was not significantly different (P = 0.123). OAC + antiplatelet was associated with a decreased risk of all-cause mortality and myocardial infarction but an increased risk of ischemic stroke among patients with NVAF and systemic atherosclerotic diseases.

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.

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.

Prognostic value of central blood pressure on the outcomes of embolic stroke of undetermined source.

We investigated the prognostic impact of central blood pressure (BP) on outcomes in patients with embolic stroke of undetermined source (ESUS). The prognostic value of central BP according to ESUS subtype was also evaluated. We recruited patients with ESUS and data on their central BP parameters (central systolic BP [SBP], central diastolic BP [DBP], central pulse pressure [PP], augmentation pressure [AP], and augmentation index [AIx]) during admission. ESUS subtype classification was arteriogenic embolism, minor cardioembolism, two or more causes, and no cause. Major adverse cardiovascular event (MACE) was defined as recurrent stroke, acute coronary syndrome, hospitalization for heart failure, or death. Over a median of 45.8 months, 746 patients with ESUS were enrolled and followed up. Patients had a mean age of 62.8 years, and 62.2% were male. Multivariable Cox regression analysis showed that central SBP and PP were associated with MACE. All-cause mortality was independently associated with AIx. In patients with no cause ESUS, central SBP and PP, AP, and AIx were independently associated with MACE. AP and AIx were independently associated with all-cause mortality (all p < 0.05). We demonstrated that central BP can predict poor long-term prognosis in patients with ESUS, especially those with the no cause ESUS subtype.

Acute Brain Infarction in Antineutrophil Cytoplasmic Antibody-Associated Vasculitis: A Korean Single-Center Study.

OBJECTIVES: This study investigated the clinical and radiological features of antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) patients with acute brain infarction, using a cohort of Korean patients with AAV. METHODS: This study included 263 patients with AAV. Acute brain infarction was defined as infarction that occurred within 7 days or less. The brain territories affected by acute brain infarction were investigated. Active AAV was arbitrarily defined as the highest tertile of Birmingham Vasculitis Activity Score (BVAS). RESULTS: The median age at diagnosis was 59.0 years, and 35.4% were male. Fourteen cases of acute brain infarction occurred in 12 patients (4.6%), which was calculated as 1332.2 per 100,000 patient-years and 10 times higher than the incidence rate in the Korean general population. Patients with AAV with acute brain infarction exhibited significantly older age, increased BVAS at diagnosis, and a more frequent history of prior brain infarction compared with those without. The brain territories affected in AAV patients were middle cerebral artery (50.0%), multiple territories (35.7%), and posterior cerebral artery (14.3%). Lacunar infarction and microhemorrhage were observed in 42.9% and 71.4% of cases, respectively. Prior brain infarction and BVAS at diagnosis were independently associated with acute brain infarction (hazard ratios, 7.037 and 1.089). Patients with AAV with prior brain infarction or BVAS for active AAV exhibited significantly lower cumulative acute brain infarction-free survival rates than those without. CONCLUSION: Acute brain infarction was observed in 4.6% of AAV patients, and both prior brain infarction and BVAS at diagnosis were independently associated with acute brain infarction.

Impact of Left Atrial or Left Atrial Appendage Thrombus on Stroke Outcome: A Matched Control Analysis.

BACKGROUND AND PURPOSE: Left atrial or left atrial appendage (LA/LAA) thrombi are frequently observed during cardioembolic evaluation in patients with ischemic stroke. This study aimed to investigate stroke outcomes in patients with LA/LAA thrombus. METHODS: This retrospective study included patients admitted to a single tertiary center in Korea between January 2012 and December 2020. Patients with nonvalvular atrial fibrillation who underwent transesophageal echocardiography or multi-detector coronary computed tomography were included in the study. Poor outcome was defined as modified Rankin Scale score >3 at 90 days. The inverse probability of treatment weighting analysis was performed. RESULTS: Of the 631 patients included in this study, 68 (10.7%) had LA/LAA thrombi. Patients were likely to have a poor outcome when an LA/LAA thrombus was detected (42.6% vs. 17.4%, P<0.001). Inverse probability of treatment weighting analysis yielded a higher probability of poor outcomes in patients with LA/LAA thrombus than in those without LA/LAA thrombus (P<0.001). Patients with LA/LAA thrombus were more likely to have relevant arterial occlusion on angiography (36.3% vs. 22.4%, P=0.047) and a longer hospital stay (8 vs. 7 days, P<0.001) than those without LA/LAA thrombus. However, there was no difference in early neurological deterioration during hospitalization or major adverse cardiovascular events within 3 months between the two groups. CONCLUSIONS: Patients with ischemic stroke who had an LA/LAA thrombus were at risk of a worse functional outcome after 3 months, which was associated with relevant arterial occlusion and prolonged hospital stay.

Association between blood viscosity and early neurological deterioration in lacunar infarction.

Background: Understanding the factors related to early neurologic deterioration (END) is crucial in the management of patients with lacunar infarction. Blood viscosity is a significant factor for microvascular perfusion. We investigated the association between blood viscosity and occurrence of END in lacunar infarction. Methods: We included consecutive patients admitted for lacunar infarction within 72 h from symptoms onset. END was defined as an increase in the National Institute of Health Stroke Scale (NIHSS) score ≥2 within 24 h of admission. Viscosity was measured within 24 h of hospitalization with a scanning capillary tube viscometer. Viscosity measured at a shear rate of 300 s-1 was defined as systolic blood viscosity (SBV), whereas that measured at a shear rate of 5 s-1 as diastolic blood viscosity (DBV). Results: Of the 178 patients included (median age, 65.5; interquartile range [IQR], 56.0, 76.0], END occurred in 33 (18.5%). DBV was significantly higher in patients with END than those without END (13.3 mPa·s [IQR 11.8, 16.0] vs. 12.3 mPa·s [IQR11.0, 13.5]; P = 0.023). In the multivariate analysis, DBV was independently associated with the occurrence of END (odds ratio 1.17; 95% confidence interval 1.01-1.36; P = 0.043). Subgroup analysis showed no heterogeneity in the effect of viscosity on the occurrence of END. Conclusions: Blood viscosity at a low shear rate (DBV) was associated with the occurrence of END in patients with lacunar infarction. Blood rheology may be important in pathophysiology of END in patients with lacunar infarction.

Association between CHADS2, CHA2DS2-VASc, ATRIA, and Essen Stroke Risk Scores and Functional Outcomes in Acute Ischemic Stroke Patients Who Received Endovascular Thrombectomy.

Background: CHADS2, CHA2DS2-VASc, ATRIA, and Essen stroke risk scores are used to estimate thromboembolism risk. We aimed to investigate the association between unfavorable outcomes and stroke risk scores in patients who received endovascular thrombectomy (EVT). Methods: This study was performed using data from a nationwide, multicenter registry to explore the selection criteria for patients who would benefit from reperfusion therapies. We calculated pre-admission CHADS2, CHA2DS2-VASc, ATRIA, and Essen scores for each patient who received EVT and compared the relationship between these scores and 3-month modified Rankin Scale (mRS) records. Results: Among the 404 patients who received EVT, 213 (52.7%) patients had unfavorable outcomes (mRS 3−6). All scores were significantly higher in patients with unfavorable outcomes than in those with favorable outcomes. Multivariable logistic regression analysis indicated that CHADS2 and the ATRIA score were positively correlated with unfavorable outcomes after adjusting for body mass index and variables with p < 0.1 in the univariable analysis (CHADS2 score: odds ratio [OR], 1.484; 95% confidence interval [CI], 1.290−1.950; p = 0.005, ATRIA score, OR, 1.128; 95% CI, 1.041−1.223; p = 0.004). Conclusions: The CHADS2 and ATRIA scores were positively correlated with unfavorable outcomes and could be used to predict unfavorable outcomes in patients who receive EVT.

Early depression screening and short-term functional outcome in hospitalized patients for acute ischemic stroke.

Background: Patients with ischemic stroke are at high risk for post-stroke depression (PSD). There are limited data regarding the clinical impact of early PSD, assessed in hospitalized patients with acute ischemic stroke. Methods: This hospital-based observational cohort study included consecutive patients with acute ischemic stroke or transient ischemic attack between July 2019 and June 2021. In the study hospital, all admitted patients were systematically screened for depression. The depression was screened using the Patient Health Questionnaire-9 (PHQ-9), and PHQ-9 positivity indicated early PSD, which was defined as a score of >4. Logistic regression analyses were used to compare the rates of poor functional outcomes at 3 months in patients with and without PHQ-9 positivity. Results: Among 1339 patients admitted during the study period, 775 were included, with a median age of 68.0 years, and 316 (40.8%) were women. A total of 111 (14.3%) patients were PHQ-9 positive. History of cancer and early neurological deterioration were independently associated with PHQ-9 positivity. Poor functional outcomes at 3 months were observed in 147 patients (18.8%). PHQ-9 positivity independently showed a 2.2-fold increased risk of poor functional outcome at 3 months (Odds ratio 2.23; 95% confidence interval 1.05-4.73, P = 0.037). Conclusions: Patients with history of cancer and early neurological deterioration were at risk for early PSD. Early PSD was independently associated with poor functional outcomes at 3 months. The identification of early depression could offer opportunities for further questioning and exploration of symptoms, as well as interventions.

Association between Low Ankle-Brachial Index and Poor Outcomes in Patients with Embolic Stroke of Undetermined Source.

We investigated the association of low ankle-brachial index (ABI < 0.9) with major adverse cardiovascular events (MACE) and all-cause mortality in patients with embolic stroke of undetermined source (ESUS) as well as whether the association differed by ESUS subtype. This retrospective single-center study included ESUS patients who underwent transesophageal echocardiography and ABI during hospitalization. ESUS was classified as ESUS with minor cardioembolic source, arteriogenic embolism, two or more causes, or no cause. Arteriogenic embolism was defined and classified as complex aortic or non-stenotic relevant artery plaque. MACE was defined as stroke recurrence, acute coronary syndrome, hospitalization for heart failure, or death. Overall, 829 patients were included, with a median follow-up of 45.8 months. Of these, 42 (5.1%) and 370 (44.6%) had low ABI and arteriogenic embolism, respectively. ABI < 0.9 was independently associated with MACE (hazard ratio [HR]: 2.038, 95% confidence interval [CI]: 1.093−3.801) and all-cause mortality (HR: 3.608, 95% CI: 1.538−8.465) according to the multivariable Cox regression analysis. Between ESUS subtypes, low ABI was independently associated with MACE (HR: 2.513, 95% CI: 1.257−5.023) and all-cause mortality (HR: 5.681, 95% CI: 2.151−15.008) in arteriogenic embolism patients, especially in those with complex aortic plaque. However, in non-arteriogenic embolism patients, low ABI was not related to MACE and mortality. In ESUS patients, low ABI was linked to MACE and all-cause mortality, especially in those with arteriogenic embolisms from complex aortic plaque.

Validation of Machine Learning Models to Predict Adverse Outcomes in Patients with COVID-19: A Prospective Pilot Study.

PURPOSE: We previously developed learning models for predicting the need for intensive care and oxygen among patients with coronavirus disease (COVID-19). Here, we aimed to prospectively validate the accuracy of these models. MATERIALS AND METHODS: Probabilities of the need for intensive care [intensive care unit (ICU) score] and oxygen (oxygen score) were calculated from information provided by hospitalized COVID-19 patients (n=44) via a web-based application. The performance of baseline scores to predict 30-day outcomes was assessed. RESULTS: Among 44 patients, 5 and 15 patients needed intensive care and oxygen, respectively. The area under the curve of ICU score and oxygen score to predict 30-day outcomes were 0.774 [95% confidence interval (CI): 0.614-0.934] and 0.728 (95% CI: 0.559-0.898), respectively. The ICU scores of patients needing intensive care increased daily by 0.71 points (95% CI: 0.20-1.22) after hospitalization and by 0.85 points (95% CI: 0.36-1.35) after symptom onset, which were significantly different from those in individuals not needing intensive care (p=0.002 and <0.001, respectively). Trends in daily oxygen scores overall were not markedly different; however, when the scores were evaluated within <7 days after symptom onset, the patients needing oxygen showed a higher daily increase in oxygen scores [1.81 (95% CI: 0.48-3.14) vs. -0.28 (95% CI: 1.00-0.43), p=0.007]. CONCLUSION: Our machine learning models showed good performance for predicting the outcomes of COVID-19 patients and could thus be useful for patient triage and monitoring.

Prediction of Hidden Coronary Artery Disease Using Machine Learning in Patients With Acute Ischemic Stroke.

BACKGROUND AND OBJECTIVES: A machine learning technique for identifying hidden coronary artery disease (CAD) might be useful. We developed and validated machine learning models to predict patients with hidden CAD and to assess long-term outcomes in patients with acute ischemic stroke. METHODS: Multidetector coronary CT was performed for patients without a known history of CAD. Primary outcomes were defined as having any degree of CAD and having obstructive CAD (≥50% stenosis). Demographic variables, risk factors, laboratory results, Trial of ORG 10172 in Acute Stroke Treatment classification, NIH Stroke Scale score, blood pressure, and carotid artery stenosis were used to develop and validate machine learning models to predict CAD. Area under the receiver operating characteristic curves (AUC) was calculated for performance analysis, and Kaplan-Meier and Cox survival analyses of long-term outcomes were performed. Major adverse cardiovascular events (MACEs) were defined as ischemic stroke, myocardial infarction, unstable angina, urgent coronary revascularization, and cardiovascular mortality. RESULTS: Overall, 1,710 patients were included for the training dataset and 348 patients for the validation dataset. An extreme gradient boosting model was developed to predict any degree of CAD, which showed an AUC of 0.763 (95% CI 0.711-0.814) on validation. A logistic regression model was used to predict obstructive CAD and had an AUC of 0.714 (95% CI 0.692-0.799). During the first 5 years of follow-up, MACEs occurred more frequently with predictions of any CAD (p = 0.022) or obstructive CAD (p < 0.001). Cox proportional analysis showed that the hazard ratio of MACE was 1.5 (95% CI 1.1-2.2; p = 0.016) with prediction of any CAD, whereas it was 1.9 (95% CI 1.3-2.6; p < 0.001) for obstructive CAD. DISCUSSION: We demonstrated that machine learning may help identify hidden CAD in patients with acute ischemic stroke. Long-term outcomes were also associated with prediction results. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that in patients with acute ischemic stroke with CAD risk factors but no known history of CAD, a machine learning model predicts CAD on multidetector coronary CT with an AUC of 0.763 (95% CI 0.711-0.814).

Impact of Sarcopenia on Functional Outcomes Among Patients With Mild Acute Ischemic Stroke and Transient Ischemic Attack: A Retrospective Study.

Introduction: Sarcopenia, a age-related disease characterized by loss of muscle mass accompanied by loss of function, is associated with nutrition imbalance, physical inactivity, insulin resistance, inflammation, metabolic syndrome, and atherosclerosis which are risk factors for cardiovascular disease. However, its association with outcomes after ischemic stroke has not been well-established. This study investigated whether functional outcomes of patients with acute ischemic stroke is associated with sarcopenia. Methods: Data were collected from 568 consecutive patients with acute ischemic stroke with National Institute of Health Stroke Scale 0-5 or transient ischemic attack who underwent bioelectrical impedance analysis between March 2018 and March 2021. Sarcopenia was defined, as low muscle mass, as measured by bioelectrical impedance analysis, and low muscle strength, as indicated by the Medical Research Council score. Unfavorable functional outcome was defined as mRS score of 2-6 at 90 days after discharge. The relationship between functional outcomes and the presence of sarcopenia or its components was determined. Results: Of the 568 patients included (mean age 65.5 ± 12.6 years, 64.6% male), sarcopenia was detected in 48 (8.5%). After adjusting for potential confounders, sarcopenia was independently and significantly associated with unfavorable functional outcome (odds ratio 2.37, 95% confidence interval 1.15-4.73 for unfavorable functional outcome, odds ratio 2.10, 95% confidence interval 1.18-3.71 for an increase in the mRS score). Each component of sarcopenia was also independently associated with unfavorable functional outcome (odds ratio 1.76, 95% confidence interval 1.05-2.95 with low muscle mass, odds ratio 2.64, 95% confidence interval 1.64-4.23 with low muscle strength). The impact of low muscle mass was larger in men than in women, and in patients with lower muscle mass of the lower extremities than in those with lower muscle mass of the upper extremities. Conclusions: In this study, the prevalence of sarcopenia in patients with stroke was lower than most of previous studies and patients with sarcopenia showed higher likelihood for unfavorable functional outcomes at 90 days after acute ischemic stroke or TIA. Further investigation of the interventions for treating sarcopenia and its impact on the outcome of ischemic stroke patients is needed.