Réza Behrouz1, Asma Zakaria2. 1. Associate Professor, Division of Cerberovascular Diseases and Neurosciences Critical Care, Department of Neurology, The Ohio State Univerisity College of Medicine, Columbus, OH, USA. 2. Staff Physician, Neuro Critical Care Unit , Division of Neurosciences, MetroHealth Medical Center, Cleveland, OH, USA.
Abstract
BACKGROUND: Many scoring systems have been developed for the purpose of estimating of mortality and outcomes in intracerebral hemorrhage (ICH). However, the utility of the World Federation of Neurosurgical Society (WFNS) classification, which is routinely used in patients with subarachnoid hemorrhage, has never been specifically assessed in ICH. METHODS: A retrospective review of the records of consecutive ICH patients admitted over a 2-year period was carried out. Collected data included ICH size, location, intraventricular hemorrhage, age, admission Glasgow Coma Scale scores, and outcomes on discharge. Linear regression was performed to confirm correlations of the WFNS scale and the ICH score separately with good outcome, poor outcome, and in-hospital mortality. Receiver-operator characteristic (ROC) curve was employed to plot WFNS and ICH scores each in relation to in-hospital mortality and poor outcome. Accuracy was estimated by calculating the area under the curves (AUC). RESULTS: In this study, 128 patients were included. The overall mortality rate was 34.4%. Linear regression showed appropriate fit for both the ICH Score and the WFNS in relation to poor outcome and mortality. The ROC curves for the scales in relation to in-hospital death produced an AUC estimate 0.93 for WFNS and 0.92 for the ICH Score (p = 0.81). For poor outcome, the AUC values were 0.91 and 0.90 for the WFNS and the ICH Score, respectively (p = 0.9). For good outcome, the AUC for WFNS was 0.86 and for the ICH score, 0.85 (p = 0.74). CONCLUSION: The WFNS classification is as accurate as the ICH score in predicting discharge outcomes and in-hospital mortality. It is a simple clinical scale that can be used to predict outcomes in both ICH and subarachnoid hemorrhage patients.
BACKGROUND: Many scoring systems have been developed for the purpose of estimating of mortality and outcomes in intracerebral hemorrhage (ICH). However, the utility of the World Federation of Neurosurgical Society (WFNS) classification, which is routinely used in patients with subarachnoid hemorrhage, has never been specifically assessed in ICH. METHODS: A retrospective review of the records of consecutive ICHpatients admitted over a 2-year period was carried out. Collected data included ICH size, location, intraventricular hemorrhage, age, admission Glasgow Coma Scale scores, and outcomes on discharge. Linear regression was performed to confirm correlations of the WFNS scale and the ICH score separately with good outcome, poor outcome, and in-hospital mortality. Receiver-operator characteristic (ROC) curve was employed to plot WFNS and ICH scores each in relation to in-hospital mortality and poor outcome. Accuracy was estimated by calculating the area under the curves (AUC). RESULTS: In this study, 128 patients were included. The overall mortality rate was 34.4%. Linear regression showed appropriate fit for both the ICH Score and the WFNS in relation to poor outcome and mortality. The ROC curves for the scales in relation to in-hospital death produced an AUC estimate 0.93 for WFNS and 0.92 for the ICH Score (p = 0.81). For poor outcome, the AUC values were 0.91 and 0.90 for the WFNS and the ICH Score, respectively (p = 0.9). For good outcome, the AUC for WFNS was 0.86 and for the ICH score, 0.85 (p = 0.74). CONCLUSION: The WFNS classification is as accurate as the ICH score in predicting discharge outcomes and in-hospital mortality. It is a simple clinical scale that can be used to predict outcomes in both ICH and subarachnoid hemorrhagepatients.
Authors: Lewis B Morgenstern; J Claude Hemphill; Craig Anderson; Kyra Becker; Joseph P Broderick; E Sander Connolly; Steven M Greenberg; James N Huang; R Loch MacDonald; Steven R Messé; Pamela H Mitchell; Magdy Selim; Rafael J Tamargo Journal: Stroke Date: 2010-07-22 Impact factor: 7.914
Authors: Brian Y Hwang; Geoffrey Appelboom; Christopher P Kellner; Amanda M Carpenter; Michael A Kellner; Paul R Gigante; E Sander Connolly Journal: Neurocrit Care Date: 2010-08 Impact factor: 3.210
Authors: Adrian R Parry-Jones; Kamran A Abid; Mario Di Napoli; Craig J Smith; Andy Vail; Hiren C Patel; Andrew T King; Pippa J Tyrrell Journal: Stroke Date: 2013-05-16 Impact factor: 7.914