Frontiers in Neurology (Sep 2022)

A nomogram for predicting malignant cerebral artery infarction in the modern thrombectomy era

  • Wenting Guo,
  • Jiali Xu,
  • Wenbo Zhao,
  • Wenbo Zhao,
  • Mengke Zhang,
  • Jin Ma,
  • Jian Chen,
  • Jiangang Duan,
  • Qingfeng Ma,
  • Haiqing Song,
  • Sijie Li,
  • Sijie Li,
  • Xunming Ji,
  • Xunming Ji,
  • Xunming Ji

DOI
https://doi.org/10.3389/fneur.2022.934051
Journal volume & issue
Vol. 13

Abstract

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ObjectiveThis study aimed to develop and validate a nomogram to predict malignant cerebral artery infarction (MMI) after endovascular treatment (EVT) in patients with acute ischemic stroke (AIS) in the modern thrombectomy era.MethodsWe retrospectively analyzed data from a prospective cohort of consecutive patients with AIS who underwent EVT at Xuanwu hospital between January 2013 and June 2021. A multivariable logistic regression model was employed to construct the nomogram for predicting MMI after EVT. The discrimination and calibration of the nomogram were assessed both in the derivation and validation cohorts.ResultsA total of 605 patients were enrolled in this study, with 425 in the derivation cohort and 180 in the validation cohort. The nomogram was developed based on admission systolic blood pressure (SBP), the National Institute of Health Stroke Score (NIHSS), the Alberta Stroke Program Early Computed Tomography Score (ASPECTS), vessel occlusion site, EVT time window, and recanalization status. The nomogram displayed good discrimination with the area under the receiver operating characteristics (ROCs) curve (AUC) of 0.783 [95% confidence interval (CI), 0.726–0.840] in the derivation cohort and 0.806 (95% CI, 0.738–0.874) in the validation cohort. The calibration of the nomogram was good as well, with the Hosmer–Lemeshow test of p = 0.857 in the derivation cohort and p = 0.275 in the validation cohort.ConclusionIn the modern thrombectomy era, a nomogram containing admission SBP, NIHSS, ASPECTS, vessel occlusion site, EVT time window, and recanalization status may predict the risk of MMI after EVT in patients with AIS.

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