Prognostic Tools for Early Mortality in Hemorrhagic Stroke

Systematic Review and Meta-Analysis

Katharina Mattishent, Chun Shing Kwok, Liban Ashkir, Kelum Pelpola, Phyo Kyaw Myint, Yoon Kong Loke

Research output: Contribution to journalArticle

8 Citations (Scopus)
4 Downloads (Pure)

Abstract

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.

METHODS: 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.

RESULTS: 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).

CONCLUSIONS: 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.

Original languageEnglish
Pages (from-to)339-348
Number of pages10
JournalJournal of Clinical Neurology
Volume11
Issue number4
Early online date6 Aug 2015
DOIs
Publication statusPublished - Oct 2015

Fingerprint

Cerebral Hemorrhage
Meta-Analysis
Stroke
Mortality
Area Under Curve
Confidence Intervals
MEDLINE
ROC Curve
Cohort Studies

Keywords

  • Systematic review
  • Meta-analysis
  • Haemorrhagic stroke
  • Prognosis tools
  • Mortality

Cite this

Prognostic Tools for Early Mortality in Hemorrhagic Stroke : Systematic Review and Meta-Analysis. / Mattishent, Katharina; Kwok, Chun Shing; Ashkir, Liban; Pelpola, Kelum; Myint, Phyo Kyaw; Loke, Yoon Kong.

In: Journal of Clinical Neurology, Vol. 11, No. 4, 10.2015, p. 339-348.

Research output: Contribution to journalArticle

Mattishent, Katharina ; Kwok, Chun Shing ; Ashkir, Liban ; Pelpola, Kelum ; Myint, Phyo Kyaw ; Loke, Yoon Kong. / Prognostic Tools for Early Mortality in Hemorrhagic Stroke : Systematic Review and Meta-Analysis. In: Journal of Clinical Neurology. 2015 ; Vol. 11, No. 4. pp. 339-348.
@article{52ec37456ade48f286c116c0ff60e01c,
title = "Prognostic Tools for Early Mortality in Hemorrhagic Stroke: Systematic Review and Meta-Analysis",
abstract = "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.METHODS: 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.RESULTS: 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).CONCLUSIONS: 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.",
keywords = "Systematic review, Meta-analysis, Haemorrhagic stroke, Prognosis tools, Mortality",
author = "Katharina Mattishent and Kwok, {Chun Shing} and Liban Ashkir and Kelum Pelpola and Myint, {Phyo Kyaw} and Loke, {Yoon Kong}",
year = "2015",
month = "10",
doi = "10.3988/jcn.2015.11.4.339",
language = "English",
volume = "11",
pages = "339--348",
journal = "Journal of Clinical Neurology",
issn = "1738-6586",
publisher = "Korean Neurological Association",
number = "4",

}

TY - JOUR

T1 - Prognostic Tools for Early Mortality in Hemorrhagic Stroke

T2 - Systematic Review and Meta-Analysis

AU - Mattishent, Katharina

AU - Kwok, Chun Shing

AU - Ashkir, Liban

AU - Pelpola, Kelum

AU - Myint, Phyo Kyaw

AU - Loke, Yoon Kong

PY - 2015/10

Y1 - 2015/10

N2 - 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.METHODS: 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.RESULTS: 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).CONCLUSIONS: 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.

AB - 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.METHODS: 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.RESULTS: 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).CONCLUSIONS: 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.

KW - Systematic review

KW - Meta-analysis

KW - Haemorrhagic stroke

KW - Prognosis tools

KW - Mortality

U2 - 10.3988/jcn.2015.11.4.339

DO - 10.3988/jcn.2015.11.4.339

M3 - Article

VL - 11

SP - 339

EP - 348

JO - Journal of Clinical Neurology

JF - Journal of Clinical Neurology

SN - 1738-6586

IS - 4

ER -