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A web based dynamic MANA Nomogram for predicting the malignant cerebral edema in patients with large hemispheric infarction

Authors :
Wenzhe Sun
Guo Li
Yang Song
Zhou Zhu
Zhaoxia Yang
Yuxi Chen
Jinfeng Miao
Xiaoyan Song
Yan Lan
Xiuli Qiu
Suiqiang Zhu
Yebin Fan
Source :
BMC Neurology, Vol 20, Iss 1, Pp 1-8 (2020)
Publication Year :
2020
Publisher :
BMC, 2020.

Abstract

Abstract 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 One hundred forty-two consecutive patients with LHI within 24 h 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 (≥ 5 mm 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.

Details

Language :
English
ISSN :
14712377
Volume :
20
Issue :
1
Database :
Directory of Open Access Journals
Journal :
BMC Neurology
Publication Type :
Academic Journal
Accession number :
edsdoj.f7d8850fc3384836b0205feccc8597fb
Document Type :
article
Full Text :
https://doi.org/10.1186/s12883-020-01935-6