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A Web Based Dynamic MANA Nomogram for Predicting the Malignant Cerebral Edema in patients with large hemispheric infarction

BMC Neurology, 2020

2020. This work is published under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;DOI: 10.21203/rs.3.rs-31715/v4

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  • Title:
    A Web Based Dynamic MANA Nomogram for Predicting the Malignant Cerebral Edema in patients with large hemispheric infarction
  • Author: Sun, Wenzhe ; Guo, Li ; Yang, Song ; Zhu, Zhou ; Yang, Zhaoxia ; Chen, Yuxi ; Miao, Jinfeng ; Song, Xiaoyan ; Yan, Lan ; Qiu, Xiuli ; Zhu, Suiqiang ; Fan, Yebin
  • Subjects: Edema ; Medical personnel ; Patients
  • Is Part Of: BMC Neurology, 2020
  • Description: Background: For large hemispheric infarction (LHI), malignant cerebral edema (MCE) is a life-threatening complication with a mortality rate approaching 80%. Establishing a convenient prediction model of MCE after LHI is vital for the rapid identification of high-risk patients as well as for a better understanding of the potential mechanism underlying MCE. Methods: 142 consecutive patients with LHI within 24h of onset between January 1, 2016 and August 31, 2019 were retrospectively reviewed. MCE was defined as patient death or received decompressive hemicraniectomy (DHC) with obvious mass effect (≥ 5mm midline shift or Basal cistern effacement). Binary logistic regression was performed to identify independent predictors of MCE. Independent prognostic factors were incorporated to build a dynamic nomogram for MCE prediction. Results: After adjusting for confounders, four independent factors were identified, including previously known atrial fibrillation (KAF), midline shift (MLS), National Institutes of Health Stroke Scale (NIHSS) and anterior cerebral artery (ACA) territory involvement. To facilitate the nomogram use for clinicians, we used the “Dynnom” package to build a dynamic MANA (acronym for MLS, ACA territory involvement, NIHSS and KAF) nomogram on web (http://www.MANA-nom.com) to calculate the exact probability of developing MCE. The MANA nomogram’s C-statistic was up to 0.887 ± 0.041 and the AUC-ROC value in this cohort was 0.887 (95%CI, 0.828~0.934). Conclusions: Independent MCE predictors included KAF, MLS, NIHSS, and ACA territory involvement. The dynamic MANA nomogram is a convenient, practical and effective clinical decision-making tool for predicting MCE after LHI in Chinese patients.
  • Publisher: Durham: Research Square
  • Language: English
  • Identifier: DOI: 10.21203/rs.3.rs-31715/v4
  • Source: AUTh Library subscriptions: ProQuest Central
    ProQuest Central
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