Prognostic Tools for Early Mortality in Hemorrhagic Stroke: Systematic Review and Meta-Analysis
2
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
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) afer ICH. We evaluated the discrimination performance of the tools through a random-efects 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 identifed 11 articles (involving 41,555 patients) reporting on the accuracy of 12 diferent tools for predicting mortality in ICH. Most studies were either retrospective or posthoc analyses of prospectively collected data; all but one produced validation data. Te 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% confdence interval (CI)=0.77–0.85]. We identifed several modifed 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 signifcant diferences 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.
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) afer ICH. We evaluated the discrimination performance of the tools through a random-efects 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 identifed 11 articles (involving 41,555 patients) reporting on the accuracy of 12 diferent tools for predicting mortality in ICH. Most studies were either retrospective or posthoc analyses of prospectively collected data; all but one produced validation data. Te 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% confdence interval (CI)=0.77–0.85]. We identifed several modifed 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 signifcant diferences 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.
참고문헌 (24)
- Thrift AG, "Incidence of the major stroke subtypes: initial findings from the North East Melbourne stroke incidence study (NEMESIS)", Stroke, 32, pp.1732~1738 (2001)
- Krishnamurthi RV, "Global and regional burden of first-ever ischaemic and haemorrhagic stroke during 1990-2010: findings from the Global Burden of Disease Study 2010", Lancet Glob Health, 1, pp.e259~e281 (2013)
- Garrett JS, "Validation of clinical prediction scores in patients with primary intracerebral hemorrhage", Neurocrit Care, 19, pp.329~335 (2013)
- Weimar C, "Development and validation of the Essen Intracerebral Haemorrhage Score", J Neurol Neurosurg Psychiatry, 77, pp.601~605 (2006), German Stroke Study Collaboration
- Ariesen MJ, "Applicability and relevance of models that predict short term outcome after intracerebral haemorrhage", J Neurol Neurosurg Psychiatry, 76, pp.839~844 (2005)
- Counsell C, "Systematic review of prognostic models in patients with acute stroke", Cerebrovasc Dis, 12, pp.159~170 (2001)
- Agarwal D, "P-152. Prognostic accuracy of the iCh score on initial evaluation of patients presenting with non-traumatic intracerebral hemorrhage; a systematic review and meta-analysis", Can J Neurol Sci, 37(3), pp.S83~S84 (2010)
- Austin PC, "Interpreting the concordance statistic of a logistic regression model: relation to the variance and odds ratio of a continuous explanatory variable", BMC Med Res Methodol, 12, pp.82~ (2012)
- Hanley JA, "The meaning and use of the area under a receiver operating characteristic (ROC) curve", Radiology, 143, pp.29~36 (1982)
- Vellutino FR, "Handbook of response to intervention: the science and practice of assessment and intervention", pp.194~ (2007), Springer
- Clarke JL, "Hemphill JC 3rd. External validation of the ICH score", Neurocrit Care, 1, pp.53~60 (2004)
- Li YF, "A new simple model for prediction of hospital mortality in patients with intracerebral hemorrhage", CNS Neurosci Ther, 18, pp.482~486 (2012)
- Matchett SC, "Predicting mortality after intracerebral hemorrhage: comparison of scoring systems and influence of withdrawal of care", J Stroke Cerebrovasc Dis, 15, pp.144~150 (2006)
- Parry-Jones AR, "Accuracy and clinical usefulness of intracerebral hemorrhage grading scores: a direct comparison in a UK population", Stroke, 44, pp.1840~1845 (2013)
- Peng SY, "Random forest can predict 30-day mortality of spontaneous intracerebral hemorrhage with remarkable discrimination", Eur J Neurol, 17, pp.945~950 (2010)
- Romano LM, "Predicting mortality and externally validation of the original intracerebral haemorrhage score after spontaneous intracerebral haemorrhage", Revista Neurológica Argentina, 32, pp.94~99 (2007)
- Ruiz-Sandoval JL, "Grading scale for prediction of outcome in primary intracerebral hemorrhages", Stroke, 38, pp.1641~1644 (2007)
- Smith EE, "A risk score for in-hospital death in patients admitted with ischemic or hemorrhagic stroke", J Am Heart Assoc, 2, pp.e005207~ (2013)
- Takahashi O, "Risk stratification for in-hospital mortality in spontaneous intracerebral haemorrhage: a Classification and Regression Tree analysis", QJM, 99, pp.743~750 (2006)
- Chuang YC, "Risk stratification for predicting 30-day mortality of intracerebral hemorrhage", Int J Qual Health Care, 21, pp.441~447 (2009)
- Hemphill JC 3rd, "The ICH score: a simple, reliable grading scale for intracerebral hemorrhage", Stroke, 32, pp.891~897 (2001)
- Bushnell CD, "Retrospective assessment of initial stroke severity: comparison of the NIH Stroke Scale and the Canadian Neurological Scale", Stroke, 32, pp.656~660 (2001)
- Perry JJ, "Emergency physicians’ management of transient ischemic attack and desired sensitivity of a clinical decision rule for stroke in three countries", CJEM, 13, pp.19~27 (2011)