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Abstract Details

Early Prediction of Malignant Brain Edema After Ischemic Stroke: a Systematic Review and Meta-Analysis
Neuro Trauma, Critical Care, and Sports Neurology
P3 - Poster Session 3 (5:30 PM-6:30 PM)
4-010
To identify reliable markers for the development of malignant brain edema after ischemic stroke.
Malignant brain edema after ischemic stroke has high mortality and is difficult to treat. Early prediction is important to inform targeted prevention and more intensive monitoring. However, there is no reliable predictors for malignant brain edema.
We searched Medline and Embase from inception to March 2018 and included studies assessing predictors or predictive models for malignant brain edema after ischemic stroke. Study quality was assessed by a 17-item tool. Odds ratios, mean differences, or standardized mean differences were synthesized in random-effects modeling. Predictive models were descriptively analyzed.
We included 38 studies (3278 patients) with 24 clinical factors, 7 domains of imaging markers, 13 serum biomarkers, and 4 models. Generally, the included studies were small and showed potential publication bias. Malignant brain edema was associated with younger age (n=2075; mean difference, −4.42, 95% confidence interval [CI], −6.63 to −2.22), higher admission National Institute of Health Stroke Scale scores (n=807, median 17–20 versus 5.5–15), and parenchymal hypoattenuation >50% of the middle cerebral artery territory on initial computed tomography (n=420; odds ratio, 5.33; 95% CI, 2.93–9.68). Revascularization (n=1600, odds ratio, 0.37; 95% CI, 0.24–0.57) were associated with a lower risk for malignant edema. Four predictive models all showed an overall C statistic >0.70, with a risk of overfitting.
Younger age, higher National Institute of Health Stroke Scale, and larger parenchymal hypoattenuation on computed tomography are reliable early predictors for malignant edema. Revascularization reduces the risk of malignant edema. No firm conclusion could be drawn for other factors due to the limited data and diversity in study characteristics. Future studies with robust design are needed to explore optimal cutoff age and National Institute of Health Stroke Scale scores and to validate and improve existing models.
Authors/Disclosures

PRESENTER
No disclosure on file
No disclosure on file
Yanan Wang No disclosure on file
No disclosure on file
No disclosure on file
No disclosure on file
No disclosure on file
Liu Ming No disclosure on file