Mattishent, K, Kwok, CS, Ashkir, L, Pelpola, K, Myint, PK and Loke, YK (2015) Prognostic Tools for Early Mortality in Hemorrhagic Stroke: Systematic Review and Meta-Analysis. Journal of Clinical Neurology, 11 (4). pp. 339-348. ISSN 2005-5013

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Background and Purpose
Several risk scores have been developed to predict mortality in intracerebral hemorrhage (ICH). We aimed to systematically determine the performance of published prognostic tools.

We searched MEDLINE and EMBASE for prognostic models (published between 2004 and April 2014) used in predicting early mortality (<6 months) after ICH. We evaluated the discrimination performance of the tools through a random-effects meta-analysis of the area under the receiver operating characteristic curve (AUC) or c-statistic. We evaluated the following components of the study validity: study design, collection of prognostic variables, treatment pathways, and missing data.

We identified 11 articles (involving 41,555 patients) reporting on the accuracy of 12 different tools for predicting mortality in ICH. Most studies were either retrospective or post-hoc analyses of prospectively collected data; all but one produced validation data. The Hemphill-ICH score had the largest number of validation cohorts (9 studies involving 3,819 patients) within our systematic review and showed good performance in 4 countries, with a pooled AUC of 0.80 [95% confidence interval (CI)=0.77-0.85]. We identified several modified versions of the Hemphill-ICH score, with the ICH-Grading Scale (GS) score appearing to be the most promising variant, with a pooled AUC across four studies of 0.87 (95% CI=0.84-0.90). Subgroup testing found statistically significant differences between the AUCs obtained in studies involving Hemphill-ICH and ICH-GS scores (p=0.01).

Our meta-analysis evaluated the performance of 12 ICH prognostic tools and found greater supporting evidence for 2 models (Hemphill-ICH and ICH-GS), with generally good performance overall.

Item Type: Article
Uncontrolled Keywords: stroke, prognostic scores, risk prediction model, mortality
Subjects: R Medicine > R Medicine (General)
Divisions: Faculty of Medicine and Health Sciences > School of Primary, Community and Social Care
Depositing User: Symplectic
Date Deposited: 15 Feb 2016 09:53
Last Modified: 28 Feb 2020 11:47

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