A score to predict early risk of recurrence after ischemic stroke

Ay, Hakan; Güngör, Levent; Arsava, Ethem Murat; Rosand, Jonathan; Vangel, Mark; Benner, Thomas; Schwamm, Lee H.; Furie, Karen L.; Koroshetz, Walter J.; Sorensen, A. Gregory

doi:10.1212/wnl.0b013e3181ca9cff

Cited by 129 publications

(134 citation statements)

References 39 publications

(59 reference statements)

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“…Similarly, we did not distinguish some other factors that may have yielded further prognostic information such as vascular territory, region (cortical vs subcortical), age, or multiplicity of infarcts. 35 Studies of the prognostic yield of plain CT scanning after TIA have yielded conflicting results. However, studies have tended to recruit subjects in the subacute phase, reported longer-term vascular outcomes and survival, and analyzed other imaging abnormalities such as leukoaraiosis in addition to infarction.…”

Section: Figure Pooled Analysis Of Association Between Abcd2 Score Anmentioning

confidence: 99%

Early stroke risk and ABCD2 score performance in tissue- vs time-defined TIA

Giles¹,

Albers²,

Amarenco³

et al. 2011

Neurology

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Objectives: Stroke risk immediately after TIA defined by time-based criteria is high, and prognostic scores (ABCD2 and ABCD3-I) have been developed to assist management. The American Stroke Association has proposed changing the criteria for the distinction between TIA and stroke from time-based to tissue-based. Research using these definitions is lacking. In a multicenter observational cohort study, we have investigated prognosis and performance of the ABCD2 score in TIA, subcategorized as tissue-positive or tissue-negative on diffusion-weighted imaging (DWI) or CT imaging according to the newly proposed criteria.Methods: Twelve centers provided data on ABCD2 scores, DWI or CT brain imaging, and follow-up in cohorts of patients with TIA diagnosed by time-based criteria. Stroke rates at 7 and 90 days were studied in relation to tissue-positive or tissue-negative subcategorization, according to the presence or absence of brain infarction. The predictive power of the ABCD2 score was determined using area under receiver operator characteristic curve (AUC) analyses.Results: A total of 4,574 patients were included. Among DWI patients (n ϭ 3,206), recurrent stroke rates at 7 days were 7.1% (95% confidence interval 5.5-9.1) after tissue-positive and 0.4% (0.2-0.7) after tissue-negative events (p diff Ͻ 0.0001). Corresponding rates in CT-imaged patients were 12.8% (9.3-17.4) and 3.0% (2.0-4.

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Section: Figure Pooled Analysis Of Association Between Abcd2 Score Anmentioning

confidence: 99%

Early stroke risk and ABCD2 score performance in tissue- vs time-defined TIA

Giles¹,

Albers²,

Amarenco³

et al. 2011

Neurology

Self Cite

146

107

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“…This difference could be explained by possible different frequencies of tested polymorphisms in general population. Patients with embolic stroke, particularly cardioembolic stroke caused by atrial fibrillation as was the case in 77% of our respondents, have a 5-7% risk for embolic stroke recurrences within 7-12 days after the initial stroke, with immediate risk for intracerebral hemorrhage as the result of damage related to the nature of the disease (20,21). For this vulnerable group of patients (who are under-or over anticoagulated), it is crucial to achieve anticoagulant effect and stable therapeutic dose as soon as possible, while pharmacogenetic testing seems valuable and promising.…”

Section: Discussionmentioning

confidence: 63%

“…These patients are at a 5-7% risk of embolic stroke recurrence within the first week. At the same time they have an increased risk of bleeding into the infarct zone due to the nature of the ischemic brain damage or to thrombolytic therapy side effects, with subsequent deterioration of neurological deficits (19)(20)(21)(22)(23). Therefore, those patients are also at increased risk of warfarin dosage side effects, notably of warfarin-induced brain hemorrhage and it is essential for them to have their initial doses selected on the basis of individual genotype to prevent the additional risk of dosage related complications.…”

Section: Introductionmentioning

confidence: 99%

Prevalence of genetic polymorphisms of CYP2C9 and VKORC1 — Implications for warfarin management and outcome in Croatian patients with acute stroke

Šupe

Božina

Matijević

et al. 2014

Journal of the Neurological Sciences

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“…Back propagation is by far the most popular neural network training algorithm that has been used to perform learning for multilayer feed-forward neural networks (Russell and Norving, 1995). Ay et al (2010) there is currently no instrument to stratify patients presenting with ischemic stroke according to early risk of recurrent stroke. However, in the Communications and Public Liaison, (2008) the symptoms of stroke are distinct because they happen quickly, for instance Sudden numbness or weakness of the face, arm, or leg (especially on one side of the body), Sudden confusion, trouble speaking or understanding speech, Sudden trouble seeing in one or both eyes, Sudden trouble walking, dizziness, loss of balance or coordination and Sudden severe headache with no known cause.…”

Section: Resultsmentioning

confidence: 99%

Cerebrovascular Accident Attack Classification Using Multilayer Feed Forward Artificial Neural Network with Back Propagation Error

Ogunmakinde¹,

Olabode²

2012

Journal of Computer Science

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Problem statement: Most important problems of medical diagnosis. When there is a cerebrovascular accident attach the chances of a successful treatment depends essentially on the early diagnosis. In practice the part of medical errors while diagnosing a stroke type comes to 20-45% even for experienced doctors and the scope of methods of neurovisualization at stroke diagnosis are limited. Approach: In this research study, attempt was made to model the application of Artificial Neural Networks to the classification of patient Cerebrovascular Accident Attack. The Network for the consisted of a three-layer feed forward artificial neural network with back-propagation error method. Results: Data were collected from 100 records of patients at Federal Medical Centre Owo, Nigeria and the Artificial Neural Networks classifier was trained using gradient decent backward propagation algorithm with flexible sigmoid activation function at one hidden layer, with 16 inputs nodes representing stroke onset symptoms at the input layer, 10 nodes at the hidden layer and one node at the output layer representing the type of the attack. Conclusion: The learning Rate γ was set between 0.1 and 0.9 while the epoch set at 150. Initial weight set at Rand (-0.5 and 0.5). The simulation results showed that the model was capable of producing a reasonable forecasting accuracy in short.

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A score to predict early risk of recurrence after ischemic stroke

Abstract: Background: There is currently no instrument to stratify patients presenting with ischemic stroke

Cited by 129 publications

References 39 publications

Early stroke risk and ABCD2 score performance in tissue- vs time-defined TIA

Early stroke risk and ABCD2 score performance in tissue- vs time-defined TIA

Prevalence of genetic polymorphisms of CYP2C9 and VKORC1 — Implications for warfarin management and outcome in Croatian patients with acute stroke

Cerebrovascular Accident Attack Classification Using Multilayer Feed Forward Artificial Neural Network with Back Propagation Error

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