A Nomogram Model to Predict Malignant Cerebral Edema in Ischemic Stroke Patients Treated with Endovascular

Mingyang Du1,2, Xianjun Huang3,4, Shun Li2

  • 1Department of Neurology, Jinling Clinical College of Nanjing Medical University, Nanjing 210002, Jiangsu Province, People's Republic of China.

Abstract

Insights

Malignant cerebral edema (MCE) is a risk after endovascular thrombectomy (EVT) for stroke. A new nomogram predicts MCE risk using age, stroke severity, glucose, and recanalization, aiding treatment decisions.

Area of Science:

  • Neurology
  • Neurosurgery
  • Stroke Medicine

Background:

  • Malignant cerebral edema (MCE) is a serious complication following endovascular thrombectomy (EVT) for ischemic stroke.
  • MCE can significantly reduce the benefits of EVT and increase patient morbidity and mortality.

Purpose of the Study:

  • To develop and validate a predictive model (nomogram) for MCE risk in patients undergoing EVT for anterior circulation large vessel occlusion stroke.
  • To identify key clinical and imaging factors associated with MCE development post-EVT.

Main Methods:

  • Retrospective analysis of 370 patients treated with EVT for anterior circulation large vessel occlusion stroke.
  • MCE definition included midline shift >5 mm or need for decompressive hemicraniectomy.
  • A multivariate logistic regression model was used to construct the nomogram, with discrimination assessed by AUC-ROC and calibration by the Hosmer-Lemeshow test.

Main Results:

  • 19.2% of patients developed MCE post-EVT.
  • Independent predictors of MCE identified were age, baseline National Institutes of Health Stroke Scale score, collateral circulation, blood glucose level, and recanalization.
  • The nomogram demonstrated good predictive performance with an AUC-ROC of 0.805 and good calibration (P=0.681).

Conclusions:

  • The developed nomogram effectively predicts MCE risk in ischemic stroke patients undergoing EVT.
  • The nomogram incorporates readily available clinical and imaging parameters, facilitating clinical application.
  • This tool can aid in patient selection and management strategies to mitigate MCE complications.