A Novel Neuroimaging Model to Predict Early Neurological Deterioration After Acute Ischemic Stroke

Author(s): Yen-Chu Huang* , Yuan-Hsiung Tsai , Jiann-Der Lee , Jen-Tsung Yang , Yi-Ting Pan .

Journal Name: Current Neurovascular Research

Volume 15 , Issue 2 , 2018

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Abstract:

Objective: In acute ischemic stroke, early neurological deterioration (END) may occur in up to one-third of patients. However, there is still no satisfying or comprehensive predictive model for all the stroke subtypes. We propose a practical model to predict END using magnetic resonance imaging (MRI).

Method: Patients with anterior circulation infarct were recruited and they underwent an MRI within 24 hours of stroke onset. END was defined as an elevation of ≥2 points on the National Institute of Health Stroke Scale (NIHSS) within 72 hours of stroke onset. We examined the relationships of END to individual END models, including: A, infarct swelling; B, small subcortical infarct; C, mismatch; and D, recurrence.

Results: There were 163 patients recruited and 43 (26.4%) of them had END. The END models A, B and C significantly predicted END respectively after adjusting for confounding factors (p=0.022, p=0.007 and p<0.001 respectively). In END model D, we examined all imaging predictors of Recurrence Risk Estimator (RRE) individually and only the “multiple acute infarcts” pattern was significantly associated with END (p=0.032). When applying END models A, B, C and D, they successfully predicted END (p<0.001; odds ratio: 17.5[95% confidence interval: 5.1– 60.8]), with 93.0% sensitivity, 60.0% specificity, 45.5% positive predictive value and 96.0% negative predictive value.

Conclusion: The results demonstrate that the proposed model could predict END in all stroke subtypes of anterior circulation infarction. It provides a practical model for clinical physicians to select high-risk patients for more aggressive treatment to prevent END.

Keywords: Early Neurological Deterioration (END), acute ischemic stroke, MRI, perfusion, stroke, MR.

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Article Details

VOLUME: 15
ISSUE: 2
Year: 2018
Page: [129 - 137]
Pages: 9
DOI: 10.2174/1567202615666180516120022

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