Literature DB >> 24103667

The SAH Score: a comprehensive communication tool.

Neeraj S Naval1, Robert G Kowalski2, Tiffany R Chang2, Filissa Caserta2, J Ricardo Carhuapoma3, Rafael J Tamargo4.   

Abstract

BACKGROUND: The Hunt and Hess grade and World Federation of Neurological Surgeons (WFNS) scale are commonly used to predict mortality after aneurysmal subarachnoid hemorrhage (aSAH). Our objective was to improve the accuracy of mortality prediction compared with the aforementioned scales by creating the "SAH score."
METHODS: The aSAH database at our institution was analyzed for factors affecting in-hospital mortality using multiple logistic regression analysis. Scores were weighted based on relative risk of mortality after stratification of each of these variables. Glasgow Coma Scale (GCS) was subdivided into groups of 3-4 (score = 1), 5-8 (score = 2), 9-13 (score = 3), and 14-15 (score = 4). Age was categorized into 4 subgroups: 18-49 (score = 1), 50-69 (score = 2), 70-79 (score = 3), and 80 years or more (score = 4). Medical comorbidities were subdivided into none (score = 1), 1 (score = 2), or 2 or more (score = 3).
RESULTS: In total, 1134 patients were included; all-cause SAH hospital mortality was 18.3%. Admission GCS, age, and medical comorbidities significantly affected mortality after multivariate analysis (P < .05). Summated scores ranged from 0 to 8 with escalating mortality at higher scores (0 = 2%, 1 = 6%, 2 = 8%, 3 = 15%, 4 = 30%, 5 = 58%, 6 = 79%, 7 = 87%, and 8 = 100%). Positive predictive value (PPV) for scores in the range 7-8 was 88.5%, whereas 6-8 was 83%. Negative predictive value (NPV) was 94% for range 0-2 and 92% for 0-3. The area under the curve (AUC) for the SAH score was .821 (good accuracy), compared with the WFNS scale (AUC .777, fair accuracy) and the Hunt and Hess grade (AUC .771, fair accuracy).
CONCLUSIONS: The SAH score was found to be more accurate in predicting aSAH mortality compared with the Hunt and Hess grade and WFNS scale.
Copyright © 2014 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Subarachnoid hemorrhage; aneurysm; mortality; outcome; stroke

Mesh:

Year:  2013        PMID: 24103667     DOI: 10.1016/j.jstrokecerebrovasdis.2013.07.035

Source DB:  PubMed          Journal:  J Stroke Cerebrovasc Dis        ISSN: 1052-3057            Impact factor:   2.136


  13 in total

1.  Factors associated with clinical and radiological status on admission in patients with aneurysmal subarachnoid hemorrhage.

Authors:  Daniel W Zumofen; Michel Roethlisberger; Rita Achermann; Schatlo Bawarjan; Martin N Stienen; Christian Fung; Donato D'Alonzo; Nicolai Maldaner; Andrea Ferrari; Marco V Corniola; Daniel Schoeni; Johannes Goldberg; Daniele Valsecchi; Thomas Robert; Rodolfo Maduri; Martin Seule; Jan-Karl Burkhardt; Serge Marbacher; Philippe Bijlenga; Kristine A Blackham; Heiner C Bucher; Luigi Mariani; Raphael Guzman
Journal:  Neurosurg Rev       Date:  2018-02-10       Impact factor: 3.042

2.  Monocyte-based inflammatory indices predict outcomes following aneurysmal subarachnoid hemorrhage.

Authors:  James Feghali; Jennifer Kim; Abhishek Gami; Sarah Rapaport; Justin M Caplan; Cameron G McDougall; Judy Huang; Rafael J Tamargo; Christopher M Jackson
Journal:  Neurosurg Rev       Date:  2021-04-10       Impact factor: 3.042

3.  Ethnic disparities in end-of-life care after subarachnoid hemorrhage.

Authors:  H Alex Choi; Andres Fernandez; Sang-Beom Jeon; J Michael Schmidt; E Sander Connolly; Stephan A Mayer; Jan Claassen; Neeraj Badjatia; Kenneth M Prager; Kiwon Lee
Journal:  Neurocrit Care       Date:  2015-06       Impact factor: 3.210

4.  Machine Learning to Predict Delayed Cerebral Ischemia and Outcomes in Subarachnoid Hemorrhage.

Authors:  Jude P J Savarraj; Georgene W Hergenroeder; Liang Zhu; Tiffany Chang; Soojin Park; Murad Megjhani; Farhaan S Vahidy; Zhongming Zhao; Ryan S Kitagawa; H Alex Choi
Journal:  Neurology       Date:  2020-11-12       Impact factor: 9.910

5.  Predictor's of Mortality in Patients with Aneurysmal Subarachnoid Haemorrhage and Reebleding.

Authors:  Dannys Rivero Rodríguez; Claudio Scherle Matamoros; Leda Fernández Cúe; Jose Luis Miranda Hernández; Yanelis Pernas Sánchez; Jesús Pérez Nellar
Journal:  Neurol Res Int       Date:  2015-02-05

6.  Development and external validation of new nomograms by adding ECG changes (ST depression or tall T wave) and age to conventional scoring systems to improve the predictive capacity in patients with subarachnoid haemorrhage: a retrospective, observational study in Korea.

Authors:  Ju Young Hong; Je Sung You; Min Joung Kim; Hye Sun Lee; Yoo Seok Park; Sung Phil Chung; Incheol Park
Journal:  BMJ Open       Date:  2019-02-20       Impact factor: 2.692

7.  Gap Analysis Regarding Prognostication in Neurocritical Care: A Joint Statement from the German Neurocritical Care Society and the Neurocritical Care Society.

Authors:  Katja E Wartenberg; David Y Hwang; Karl Georg Haeusler; Susanne Muehlschlegel; Oliver W Sakowitz; Dominik Madžar; Hajo M Hamer; Alejandro A Rabinstein; David M Greer; J Claude Hemphill; Juergen Meixensberger; Panayiotis N Varelas
Journal:  Neurocrit Care       Date:  2019-10       Impact factor: 3.210

8.  Nitric Oxide-Based Treatment of Poor-Grade Patients After Severe Aneurysmal Subarachnoid Hemorrhage.

Authors:  Angelika Ehlert; Jitka Starekova; Gerd Manthei; Annette Ehlert-Gamm; Joachim Flack; Marie Gessert; Joachim Gerss; Volker Hesselmann
Journal:  Neurocrit Care       Date:  2020-06       Impact factor: 3.210

9.  Comparison of aneurysmal subarachnoid hemorrhage grading scores in patients with aneurysm clipping and coiling.

Authors:  Yuanjian Fang; Jianan Lu; Jingwei Zheng; Haijian Wu; Camila Araujo; Cesar Reis; Cameron Lenahan; Suijun Zhu; Sheng Chen; Jianmin Zhang
Journal:  Sci Rep       Date:  2020-06-08       Impact factor: 4.379

Review 10.  Multimorbidity and Critical Care Neurosurgery: Minimizing Major Perioperative Cardiopulmonary Complications.

Authors:  Rami Algahtani; Amedeo Merenda
Journal:  Neurocrit Care       Date:  2020-08-13       Impact factor: 3.210

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