title: Prognostic indices for early mortality in ischaemic stroke - meta-analysis.
abstract: OBJECTIVE
  Several models have been developed to predict mortality in ischaemic stroke. We aimed to evaluate systematically the performance of published stroke prognostic scores.
  
  
  METHODS
  We searched MEDLINE and EMBASE in February 2014 for prognostic models (published between 2003 and 2014) used in predicting early mortality (<6 months) after ischaemic stroke. We evaluated discriminant ability of the tools through meta-analysis of the area under the curve receiver operating characteristic curve (AUROC) or c-statistic. We evaluated the following components of study validity: collection of prognostic variables, neuroimaging, treatment pathways and missing data.
  
  
  RESULTS
  We identified 18 articles (involving 163 240 patients) reporting on the performance of prognostic models for mortality in ischaemic stroke, with 15 articles providing AUC for meta-analysis. Most studies were either retrospective, or post hoc analyses of prospectively collected data; all but three reported validation data. The iSCORE had the largest number of validation cohorts (five) within our systematic review and showed good performance in four different countries, pooled AUC 0.84 (95% CI 0.82-0.87). We identified other potentially useful prognostic tools that have yet to be as extensively validated as iSCORE - these include SOAR (2 studies, pooled AUC 0.79, 95% CI 0.78-0.80), GWTG (2 studies, pooled AUC 0.72, 95% CI 0.72-0.72) and PLAN (1 study, pooled AUC 0.85, 95% CI 0.84-0.87).
  
  
  CONCLUSIONS
  Our meta-analysis has identified and summarized the performance of several prognostic scores with modest to good predictive accuracy for early mortality in ischaemic stroke, with the iSCORE having the broadest evidence base.
authors.affiliation: Norwich Medical School, University of East Anglia, Norwich, UK.
authors.forename: K
authors.initials: K
authors.lastname: Mattishent
authors.affiliation: Norwich Medical School, University of East Anglia, Norwich, UK.
authors.forename: C S
authors.initials: CS
authors.lastname: Kwok
authors.affiliation: Norwich Medical School, University of East Anglia, Norwich, UK.
authors.forename: A
authors.initials: A
authors.lastname: Mahtani
authors.affiliation: Southend University Hospital Trust, Westcliff-on-Sea, UK.
authors.forename: K
authors.initials: K
authors.lastname: Pelpola
authors.affiliation: Epidemiology Group, Institute of Applied Health Sciences, School of Medicine & Dentistry, University of Aberdeen, Aberdeen, UK.
authors.forename: P K
authors.initials: PK
authors.lastname: Myint
authors.affiliation: Norwich Medical School, University of East Anglia, Norwich, UK.
authors.forename: Y K
authors.initials: YK
authors.lastname: Loke
mesh_terms: D000369:Aged, 80 and over; D019540:Area Under Curve; D002545:Brain Ischemia / Q000175:diagnosis* / Q000401:mortality*; D005260:Female; D006801:Humans; D008297:Male; D008962:Models, Theoretical; D009026:Mortality / Q000639:trends; D011237:Predictive Value of Tests; D011379:Prognosis; D011446:Prospective Studies; D012372:ROC Curve; D012189:Retrospective Studies; D020521:Stroke / Q000175:diagnosis* / Q000401:mortality*
keywords: mortality; prognostic scores; risk prediction model; stroke