Literature DB >> 28201763

The Barrow Neurological Institute Scale Revisited: Predictive Capabilities for Cerebral Infarction and Clinical Outcome in Patients With Aneurysmal Subarachnoid Hemorrhage.

Nora F Dengler1, Dominik Diesing1, Asita Sarrafzadeh2, Stefan Wolf1, Peter Vajkoczy1.   

Abstract

BACKGROUND: In 2012, a new computed tomography (CT) grading scale was introduced by the Barrow Neurological Institute group ("BNI scale") to predict angiographic and symptomatic vasospasm in aneurysmal subarachnoid hemorrhage.
OBJECTIVE: To address the question of whether BNI grading is reliable in the prediction of cerebral infarction and clinical outcome and to compare BNI scores to existing radiographic and clinical models of outcome prediction.
METHODS: Consecutive data of 260 patients with aneurysmal subarachnoid hemorrhage was retrospectively analyzed with respect to radiographic and clinical parameters.
RESULTS: Patients presenting with more severe BNI grades were older ( P = .002), displayed lower Glasgow Coma Scale scores at admission ( P < .001) and were more often diagnosed with intraventricular hemorrhage ( P < .001). An increasing BNI grade was associated with higher rates of severe angiographic vasospasm ( P = .007), the occurrence of new cerebral infarction ( P < .001), and poor patient outcome ( P < .001). In contrast, analysis according to the Fisher grading system did not show a significant relationship to any outcome parameter. Multivariate analysis combining radiographic and clinical parameters showed significant results for clinical scores (Hunt and Hess and World Federation of Neurosurgical Societies) with radiographic information losing its predictive capability.
CONCLUSION: The BNI scale is easily applicable and superior to the original Fisher scale regarding prediction of angiographic vasospasm, new cerebral infarction, and patient outcome. Presence of intraventricular hemorrhage and intracerebral hemorrhage are additional radiographic factors with outcome relevance that are not part of the BNI scale. Established clinical scores like World Federation of Neurosurgical Societies and Hunt and Hess grading were more relevant for outcome prediction than any radiographic information.
Copyright © 2017 by the Congress of Neurological Surgeons.

Entities:  

Keywords:  Aneurysmal subarachnoid hemorrhage; CT grading; Cerebral infarction; Intracerebral hemorrhage; Intraventricular hemorrhage; Patient outcome

Mesh:

Year:  2017        PMID: 28201763     DOI: 10.1093/neuros/nyw141

Source DB:  PubMed          Journal:  Neurosurgery        ISSN: 0148-396X            Impact factor:   4.654


  5 in total

1.  Prediction of Outcome Using Quantified Blood Volume in Aneurysmal SAH.

Authors:  W E van der Steen; H A Marquering; L A Ramos; R van den Berg; B A Coert; A M M Boers; M D I Vergouwen; G J E Rinkel; B K Velthuis; Y B W E M Roos; C B L M Majoie; W P Vandertop; D Verbaan
Journal:  AJNR Am J Neuroradiol       Date:  2020-05-14       Impact factor: 3.825

2.  Radiological scales predicting delayed cerebral ischemia in subarachnoid hemorrhage: systematic review and meta-analysis.

Authors:  Wessel E van der Steen; Eva L Leemans; René van den Berg; Yvo B W E M Roos; Henk A Marquering; Dagmar Verbaan; Charles B L M Majoie
Journal:  Neuroradiology       Date:  2019-01-28       Impact factor: 2.804

3.  Corticothalamic Connectivity in Aneurysmal Subarachnoid Hemorrhage: Relationship with Disordered Consciousness and Clinical Outcomes.

Authors:  Peter B Forgacs; Baxter B Allen; Xian Wu; Linda M Gerber; Srikanth Boddu; Malik Fakhar; Philip E Stieg; Nicholas D Schiff; Halinder S Mangat
Journal:  Neurocrit Care       Date:  2021-10-20       Impact factor: 3.210

4.  Effect of Premorbid Antiplatelet Medication Use on Delayed Cerebral Ischemia After Aneurysmal Subarachnoid Hemorrhage: A Propensity Score-matched Study.

Authors:  Alejandro Enriquez-Marulanda; Mohamed M Salem; Krishnan Ravindran; Luis C Ascanio; Georgios A Maragkos; Santiago Gomez-Paz; Abdulrahman Y Alturki; Christopher S Ogilvy; Ajith J Thomas; Justin Moore
Journal:  Cureus       Date:  2019-09-09

5.  Outcome prediction in aneurysmal subarachnoid hemorrhage: a comparison of machine learning methods and established clinico-radiological scores.

Authors:  Nora Franziska Dengler; Vince Istvan Madai; Meike Unteroberdörster; Esra Zihni; Sophie Charlotte Brune; Adam Hilbert; Michelle Livne; Stefan Wolf; Peter Vajkoczy; Dietmar Frey
Journal:  Neurosurg Rev       Date:  2021-01-20       Impact factor: 3.042

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.