scholarly journals Rich-Club organization: an important determinant of functional outcome after acute ischemic stroke

2019 ◽  
Author(s):  
Markus D. Schirmer ◽  
Sofia Ira Ktena ◽  
Marco J. Nardin ◽  
Kathleen L. Donahue ◽  
Anne-Katrin Giese ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Functional Outcome ◽  
Prediction Models ◽  
Brain Magnetic Resonance Imaging ◽  
Lesion Volume ◽  
Stroke Outcome ◽  
Rich Club ◽  
The Rich ◽  
Magnetic Resonance Imaging Mri

AbstractObjectiveTo determine whether the rich-club organization, essential for information transport in the human connectome, is an important biomarker of functional outcome after acute ischemic stroke (AIS).MethodsConsecutive AIS patients (N=344) with acute brain magnetic resonance imaging (MRI) (<48 hours) were eligible for this study. Each patient underwent a clinical MRI protocol, which included diffusion weighted imaging (DWI). All DWIs were registered to a template on which rich-club regions have been defined. Using manual outlines of stroke lesions, we automatically counted the number of affected rich-club regions and assessed its effect on the National Institute of Health Stroke Scale (NIHSS) and modified Rankin Scale (mRS; obtained at 90 days post-stroke) scores through ordinal regression.ResultsOf 344 patients (median age 65, inter-quartile range 54-76 years) with a median DWI lesion volume (DWIv) of 3cc, 64% were male. We established that an increase in number of rich-club regions affected by a stroke increases the odds of poor stroke outcome, measured by NIHSS (OR: 1.77, 95%CI 1.41-2.21) and mRS (OR: 1.38, 95%CI 1.11-1.73). Additionally, we demonstrated that the OR exceeds traditional markers, such as DWIv (ORNIHSS 1.08, 95%CI 1.06-1.11; ORmRs 1.05, 95%CI 1.03-1.07) and age (ORNIHSS 1.03, 95%CI 1.01-1.05; ORmRs 1.05, 95%CI 1.03-1.07).ConclusionIn this proof-of-concept study, the number of rich-club nodes affected by a stroke lesion presents a translational biomarker of stroke outcome, which can be readily assessed using standard clinical AIS imaging protocols and considered in functional outcome prediction models beyond traditional factors.

Pre-Stroke Cholinesterase Inhibitor Treatment Is Beneficially Associated with Functional Outcome in Patients with Acute Ischemic Stroke and Pre-Stroke Dementia: The Fukuoka Stroke Registry

2021 ◽  
pp. 1-7
Author(s):  
Yoshinobu Wakisaka ◽  
Ryu Matsuo ◽  
Kuniyuki Nakamura ◽  
Tetsuro Ago ◽  
Masahiro Kamouchi ◽  
...  
Keyword(s):  
Cohort Study ◽  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Functional Outcome ◽  
Neurological Deterioration ◽  
Stroke Outcome ◽  
Matched Cohort ◽  
Poor Functional Outcome ◽  
Stroke Registry ◽  
Chei Treatment

Introduction: Pre-stroke dementia is significantly associated with poor stroke outcome. Cholinesterase inhibitors (ChEIs) might reduce the risk of stroke in patients with dementia. However, the association between pre-stroke ChEI treatment and stroke outcome remains unresolved. Therefore, we aimed to determine this association in patients with acute ischemic stroke and pre-stroke dementia. Methods: We enrolled 805 patients with pre-stroke dementia among 13,167 with ischemic stroke within 7 days of onset who were registered in the Fukuoka Stroke Registry between June 2007 and May 2019 and were independent in basic activities of daily living (ADLs) before admission. Primary and secondary study outcomes were poor functional outcome (modified Rankin Scale [mRS] score: 3–6) at 3 months after stroke onset and neurological deterioration (≥2-point increase in the NIH Stroke Scale [NIHSS] during hospitalization), respectively. Logistic regression analysis was used to evaluate associations between pre-stroke ChEI treatment and study outcomes. To improve covariate imbalance, we further conducted a propensity score (PS)-matched cohort study. Results: Among the participants, 212 (26.3%) had pre-stroke ChEI treatment. Treatment was negatively associated with poor functional outcome (odds ratio: 0.68 [95% confidence interval: 0.46–0.99]) and neurological deterioration (0.52 [0.31–0.88]) after adjusting for potential confounding factors. In the PS-matched cohort study, the same trends were observed between pre-stroke ChEI treatment and poor functional outcome (0.61 [0.40–0.92]) and between the treatment and neurological deterioration (0.47 [0.25–0.86]). Conclusions: Our findings suggest that pre-stroke ChEI treatment is associated with reduced risks for poor functional outcome and neurological deterioration after acute ischemic stroke in patients with pre-stroke dementia who are independent in basic ADLs before the onset of stroke.

scholarly journals Associations of Ischemic Lesion Volume With Functional Outcome in Patients With Acute Ischemic Stroke

Stroke ◽  
2017 ◽  
Vol 48 (5) ◽  
pp. 1233-1240 ◽  
Author(s):  
Amber Bucker ◽  
Anna M. Boers ◽  
Joseph C.J. Bot ◽  
Olvert A. Berkhemer ◽  
Hester F. Lingsma ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Functional Outcome ◽  
Lesion Volume ◽  
Ischemic Lesion

scholarly journals Rich-Club Organization: An Important Determinant of Functional Outcome After Acute Ischemic Stroke

2019 ◽  
Vol 10 ◽  
Author(s):  
Markus D. Schirmer ◽  
Sofia Ira Ktena ◽  
Marco J. Nardin ◽  
Kathleen L. Donahue ◽  
Anne-Katrin Giese ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Functional Outcome ◽  
Important Determinant ◽  
Rich Club

scholarly journals Outcome Prediction Models for Endovascular Treatment of Ischemic Stroke: Systematic Review and External Validation

Stroke ◽  
2021 ◽  
Author(s):  
Femke Kremers ◽  
Esmee Venema ◽  
Martijne Duvekot ◽  
Lonneke Yo ◽  
Reinoud Bokkers ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
The Netherlands ◽  
Endovascular Treatment ◽  
Acute Ischemic Stroke ◽  
Functional Outcome ◽  
Prediction Models ◽  
Predictive Performance ◽  
Data Availability ◽  
Vascular Events ◽  
Discriminative Performance

Background and Purpose: Prediction models for outcome of patients with acute ischemic stroke who will undergo endovascular treatment have been developed to improve patient management. The aim of the current study is to provide an overview of preintervention models for functional outcome after endovascular treatment and to validate these models with data from daily clinical practice. Methods: We systematically searched within Medline, Embase, Cochrane, Web of Science, to include prediction models. Models identified from the search were validated in the MR CLEAN (Multicenter Randomized Clinical Trial of Endovascular Treatment for Acute Ischemic Stroke in the Netherlands) registry, which includes all patients treated with endovascular treatment within 6.5 hours after stroke onset in the Netherlands between March 2014 and November 2017. Predictive performance was evaluated according to discrimination (area under the curve) and calibration (slope and intercept of the calibration curve). Good functional outcome was defined as a score of 0–2 or 0–3 on the modified Rankin Scale depending on the model. Results: After screening 3468 publications, 19 models were included in this validation. Variables included in the models mainly addressed clinical and imaging characteristics at baseline. In the validation cohort of 3156 patients, discriminative performance ranged from 0.61 (SPAN-100 [Stroke Prognostication Using Age and NIH Stroke Scale]) to 0.80 (MR PREDICTS). Best-calibrated models were THRIVE (The Totaled Health Risks in Vascular Events; intercept −0.06 [95% CI, −0.14 to 0.02]; slope 0.84 [95% CI, 0.75–0.95]), THRIVE-c (intercept 0.08 [95% CI, −0.02 to 0.17]; slope 0.71 [95% CI, 0.65–0.77]), Stroke Checkerboard score (intercept −0.05 [95% CI, −0.13 to 0.03]; slope 0.97 [95% CI, 0.88–1.08]), and MR PREDICTS (intercept 0.43 [95% CI, 0.33–0.52]; slope 0.93 [95% CI, 0.85–1.01]). Conclusions: The THRIVE-c score and MR PREDICTS both showed a good combination of discrimination and calibration and were, therefore, superior in predicting functional outcome for patients with ischemic stroke after endovascular treatment within 6.5 hours. Since models used different predictors and several models had relatively good predictive performance, the decision on which model to use in practice may also depend on simplicity of the model, data availability, and the comparability of the population and setting.

scholarly journals Machine Learning-Based Three-Month Outcome Prediction in Acute Ischemic Stroke: A Single Cerebrovascular-Specialty Hospital Study in South Korea

Diagnostics ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 1909
Author(s):  
Dougho Park ◽  
Eunhwan Jeong ◽  
Haejong Kim ◽  
Hae Wook Pyun ◽  
Haemin Kim ◽  
...  
Keyword(s):  
Machine Learning ◽  
Logistic Regression ◽  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Functional Outcome ◽  
Outcome Prediction ◽  
Prediction Models ◽  
Gradient Boosting ◽  
Support Vector ◽  
Extreme Gradient Boosting

Background: Functional outcomes after acute ischemic stroke are of great concern to patients and their families, as well as physicians and surgeons who make the clinical decisions. We developed machine learning (ML)-based functional outcome prediction models in acute ischemic stroke. Methods: This retrospective study used a prospective cohort database. A total of 1066 patients with acute ischemic stroke between January 2019 and March 2021 were included. Variables such as demographic factors, stroke-related factors, laboratory findings, and comorbidities were utilized at the time of admission. Five ML algorithms were applied to predict a favorable functional outcome (modified Rankin Scale 0 or 1) at 3 months after stroke onset. Results: Regularized logistic regression showed the best performance with an area under the receiver operating characteristic curve (AUC) of 0.86. Support vector machines represented the second-highest AUC of 0.85 with the highest F1-score of 0.86, and finally, all ML models applied achieved an AUC > 0.8. The National Institute of Health Stroke Scale at admission and age were consistently the top two important variables for generalized logistic regression, random forest, and extreme gradient boosting models. Conclusions: ML-based functional outcome prediction models for acute ischemic stroke were validated and proven to be readily applicable and useful.

NIHSS cut point for predicting outcome in supra- vs infratentorial acute ischemic stroke

Neurology ◽  
2018 ◽  
Vol 91 (18) ◽  
pp. e1695-e1701 ◽  
Author(s):  
Sohei Yoshimura ◽  
Richard I. Lindley ◽  
Cheryl Carcel ◽  
Shoichiro Sato ◽  
Candice Delcourt ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Functional Outcome ◽  
Controlled Trial ◽  
Additional Treatment ◽  
Clinical Severity ◽  
Stroke Outcome ◽  
Operating Characteristics ◽  
Cut Point ◽  
Significant Difference

ObjectiveTo determine the optimal cut point on the NIH Stroke Scale (NIHSS) for predicting poor 90-day clinical outcome in patients with supratentorial and infratentorial acute ischemic stroke (AIS).MethodsData are from participants of the alteplase-dose arm of the randomized controlled trial, Enhanced Control of Hypertension and Thrombolysis Stroke Study (ENCHANTED). Associations between baseline characteristics of clinically defined supratentorial and infratentorial AIS patients and poor functional outcome, defined by scores 3–6 on the modified Rankin Scale, were evaluated in logistic regression models, with area under the curve (AUC) receiver operating characteristics defining the optimal NIHSS predictor cut point.ResultsPatients with infratentorial AIS (n = 289) had lower baseline NIHSS scores than those with supratentorial AIS (n = 2,613) (median 7 vs 9; p < 0.001). NIHSS cut points for poor outcome were 10 (AUC 76, sensitivity 65%, specificity 73%) and 6 (AUC 69, sensitivity 72%, specificity 56%) in supratentorial and infratentorial AIS, respectively. There was no significant difference in functional outcome or symptomatic intracranial hemorrhage between AIS types.ConclusionsIn thrombolysis-eligible AIS patients, the NIHSS may underestimate clinical severity for infratentorial compared to supratentorial lesions for a similar prognosis for recovery. Because thrombolysis treatment has low effect on stroke outcome in patients with infratentorial AIS when baseline NIHSS score is more than 6, additional treatment such as endovascular treatment should be considered to improve stroke outcome.Clinicaltrials.gov identifierNCT01422616.

scholarly journals Posttreatment Ischemic Lesion Evolution Is Associated With Reduced Favorable Functional Outcome in Patients With Stroke

Stroke ◽  
2021 ◽  
Author(s):  
Praneeta Konduri ◽  
Henk van Voorst ◽  
Amber Bucker ◽  
Katinka van Kranendonk ◽  
Anna Boers ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Functional Outcome ◽  
Odds Ratio ◽  
Interaction Analysis ◽  
Univariate Analysis ◽  
Arterial Occlusion ◽  
Lesion Volume ◽  
Ischemic Lesion ◽  
Favorable Functional Outcome

Background and Purpose: Ischemic lesion volume can increase even 24 hours after onset of an acute ischemic stroke. In this study, we investigated the association of lesion evolution with functional outcome and the influence of successful recanalization on this association. Methods: We included patients from the MR CLEAN trial (Multicenter Randomized Clinical Trial of Endovascular Treatment for Acute Ischemic Stroke in the Netherlands) who received good quality noncontrast CT images 24 hours and 1 week after stroke onset. The ischemic lesion delineations included infarct, edema, and hemorrhagic transformation. Lesion evolution was defined as the difference between the volumes measured on the 1-week and 24-hour noncontrast CTs. The association of lesion evolution with functional outcome was evaluated using unadjusted and adjusted logistic regression. Adjustments were made for baseline, clinical, and imaging parameters that were associated P <0.10) in univariate analysis with favorable functional outcome, defined as modified Rankin Scale score of ≤2. Interaction analysis was performed to evaluate the influence of successful recanalization, defined as modified Arterial Occlusion Lesion score of 3 points, on this association. Results: Of the 226 patients who were included, 69 (31%) patients achieved the favorable functional outcome. Median lesion evolution was 22 (interquartile range, 10–45) mL. Lesion evolution was significantly inversely correlated with favourable functional outcome: unadjusted odds ratio, 0.76 (95% CI, 0.66–0.86; per 10 mL of lesion evolution; P <0.01) and adjusted odds ratio: 0.85 (95% CI, 0.72–0.97; per 10 mL of lesion evolution; P =0.03). There was no significant interaction of successful recanalization on the association of lesion evolution and favorable functional outcome (odds ratio, 1.01 [95% CI, 0.77–1.36]; P =0.94). Conclusions: In our population, subacute ischemic lesion evolution is associated with unfavorable functional outcome. This study suggests that even 24 hours after onset of stroke, deterioration of the brain continues, which has a negative effect on functional outcome. This finding may warrant additional treatment in the subacute phase.

scholarly journals Accuracy of prehospital ambulance stroke test in terms of diagnosis of patients with acute ischemic stroke: A multi-center study

2021 ◽  
Author(s):  
Somayeh Karimi ◽  
Farhad Heydari ◽  
Sahar Mirbaha ◽  
Mohamed Elfil ◽  
Alireza Baratloo
Keyword(s):  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Scoring System ◽  
Brain Magnetic Resonance Imaging ◽  
Mri Findings ◽  
Cross Sectional ◽  
Point Score ◽  
Accuracy Study ◽  
Magnetic Resonance Imaging Mri ◽  
Multi Center Study

Background: Andsberg et al. have recently introduced a novel scoring system entitled “PreHospital Ambulance Stroke Test (PreHAST)”, which helps to early identification of patients with acute ischemic stroke (AIS) even in prehospital setting. Its validity has not been assessed in a study yet, and the purpose of this study was to assess this scoring system on a larger scale to provide further evidence in this regard. Methods: This was a cross-sectional multi-center accuracy study, in which, sampling was performed prospectively. All patients over 18 years of age admitted to the emergency department (ED) and suspected as AIS cases were included. All required data were recorded in a form consisting of 3 parts: baseline characteristics, neurological examination findings required for calculating PreHAST score, and the ultimate diagnosis made from interpretation of their brain magnetic resonance imaging (MRI). Results: Data from 805 patients (57.5% men) with the mean age of 67.1 ± 13.6 years were analyzed. Of all the patients presenting with suspected AIS, 562 (69.8%) had AIS based on their MRI findings. At the suggested cut-off point (score ≥ 1), PreHAST had a specificity of 46.5% [95% confidence interval (CI): 40.1%-53.0%) and a sensitivity of 93.2% (95%CI: 90.8%-95.2%). Conclusion: According to the findings of our study, at the suggested cut-off point (score ≥ 1), PreHAST had 93.2% sensitivity and 46.5% specificity in detection of patients with AIS, which were somewhat different from those reported in the original study, where 100% sensitivity and 40% specificity were reported for this scoring system.

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