Literature DB >> 33679575

Scoring Model to Predict Functional Outcome in Poor-Grade Aneurysmal Subarachnoid Hemorrhage.

Jie Shen1, Jianbo Yu1, Sicong Huang1, Rajneesh Mungur1, Kaiyuan Huang1, Xinfa Pan1, Guofeng Yu2, Zhikai Xie1, Lihui Zhou1, Zongchi Liu1, Dexin Cheng1, Jianwei Pan1, Renya Zhan1.   

Abstract

Background: Patients with poor-grade aneurysmal subarachnoid hemorrhage (aSAH), defined as World Federation of Neurosurgical Societies (WFNS) grades IV-V have high rates of disability and mortality. The objective of this study was to accurately prognosticate the outcomes of patients with poor-grade aSAH by developing a new scoring model.
Methods: A total of 147 poor-grade aSAH patients in our center were enrolled. Risk variables identified by multivariate logistic regression analysis were used to devise a scoring model (total score, 0-9 points). The scores were estimated on the basis of β coefficients. A cohort of 68 patients from another institute was used to validate the model.
Results: Multivariate logistic regression analysis revealed that modified Fisher grade >2 [odds ratio [OR], 2.972; P = 0.034], age ≥65 years (OR, 3.534; P = 0.006), conservative treatment (OR, 5.078; P = 0.019), WFNS grade V (OR, 2.638; P = 0.029), delayed cerebral ischemia (OR, 3.170; P = 0.016), shunt-dependent hydrocephalus (OR, 3.202; P = 0.032), and cerebral herniation (OR, 7.337; P < 0.001) were significant predictors for poor prognosis [modified Rankin Scale [mRS] ≥3]. A scoring system was constructed by the integration of these factors and divided the poor-grade aSAH patients into three categories: low risk (0-1 points), intermediate risk (2-3 points), and high risk (4-9 points), with predicted risks of poor prognosis of 11, 52, and 87%, respectively (P < 0.001). The area under the curve in the derivation cohort was 0.844 (95% CI, 0.778-0.909). The AUC in the validation cohort was 0.831 (95% CI, 0.732-0.929). Conclusions: The new scoring model can improve prognostication and help decision-making for subsequent complementary treatment in patients with aSAH.
Copyright © 2021 Shen, Yu, Huang, Mungur, Huang, Pan, Yu, Xie, Zhou, Liu, Cheng, Pan and Zhan.

Entities:  

Keywords:  aneurysmal subarachnoid hemorrhage; model; poor-grade; prognosis; scoring system

Year:  2021        PMID: 33679575      PMCID: PMC7930831          DOI: 10.3389/fneur.2021.601996

Source DB:  PubMed          Journal:  Front Neurol        ISSN: 1664-2295            Impact factor:   4.003


  5 in total

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Authors:  Runting Li; Fa Lin; Yu Chen; Junlin Lu; Heze Han; Li Ma; Yahui Zhao; Debin Yan; Ruinan Li; Jun Yang; Shihao He; Zhipeng Li; Haibin Zhang; Kexin Yuan; Ke Wang; Qiang Hao; Xun Ye; Hao Wang; Hongliang Li; Linlin Zhang; Guangzhi Shi; Jianxin Zhou; Yang Zhao; Yukun Zhang; Youxiang Li; Shuo Wang; Xiaolin Chen; Yuanli Zhao
Journal:  Transl Stroke Res       Date:  2022-05-14       Impact factor: 6.829

2.  DCI after Aneurysmal Subarachnoid Hemorrhage Is Related to the Expression of MFG-E8.

Authors:  Xianjun Chen; Yong'an Jiang; Jiayu Liu; Changfeng Wang; Dengfeng Wan; Ai'jun Liang; Jingxing Leng; Yu Yang; Hui Xiang; Ru'en Liu
Journal:  Biomed Res Int       Date:  2021-12-31       Impact factor: 3.411

3.  Admission Homocysteine as a Potential Predictor for Delayed Cerebral Ischemia After Aneurysmal Subarachnoid Hemorrhage.

Authors:  Tiesong Zhang; Luyuan Zhang; Kehui Nie; Jun Yang; Haiyan Lou; Jincheng Wang; Sicong Huang; Chenjie Gu; Min Yan; Renya Zhan; Jianwei Pan
Journal:  Front Surg       Date:  2022-02-08

4.  Mortality among patients treated for aneurysmal subarachnoid hemorrhage in Eastern Denmark 2017-2019.

Authors:  Agnes T Stauning; Frank Eriksson; Goetz Benndorf; Anders V Holst; John Hauerberg; Trine Stavngaard; Lars Poulsgaard; Per Rochat; Vagn Eskesen; Peter Birkeland; Tiit Mathiesen; Tina N Munch
Journal:  Acta Neurochir (Wien)       Date:  2022-07-22       Impact factor: 2.816

5.  Ultra-early endovascular treatment improves prognosis in High grade aneurysmal subarachnoid hemorrhage: A single-center retrospective study.

Authors:  Botao Wu; Zhe Huang; Huan Liu; Jiayao He; Yan Ju; Ziwei Chen; Taiwei Zhang; Fuxin Yi
Journal:  Front Neurol       Date:  2022-08-12       Impact factor: 4.086

  5 in total

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