Document Detail


Clinical prediction models for aneurysmal subarachnoid hemorrhage: a systematic review.
MedLine Citation:
PMID:  23138544     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
BACKGROUND: Clinical prediction models can enhance clinical decision-making and research. However, available prediction models in aneurysmal subarachnoid hemorrhage (aSAH) are rarely used. We evaluated the methodological validity of SAH prediction models and the relevance of the main predictors to identify potentially reliable models and to guide future attempts at model development.
METHODS: We searched the EMBASE, MEDLINE, and Web of Science databases from January 1995 to June 2012 to identify studies that reported clinical prediction models for mortality and functional outcome in aSAH. Validated methods were used to minimize bias.
RESULTS: Eleven studies were identified; 3 developed models from datasets of phase 3 clinical trials, the others from single hospital records. The median patient sample size was 340 (interquartile range 149-733). The main predictors used were age (n = 8), Fisher grade (n = 6), World Federation of Neurological Surgeons grade (n = 5), aneurysm size (n = 5), and Hunt and Hess grade (n = 3). Age was consistently dichotomized. Potential predictors were prescreened by univariate analysis in 36 % of studies. Only one study was penalized for model optimism. Details about model development were often insufficiently described and no published studies provided external validation.
CONCLUSIONS: While clinical prediction models for aSAH use a few simple predictors, there are substantial methodological problems with the models and none have had external validation. This precludes the use of existing models for clinical or research purposes. We recommend further studies to develop and validate reliable clinical prediction models for aSAH.
Authors:
Blessing N R Jaja; Michael D Cusimano; Nima Etminan; Daniel Hanggi; David Hasan; Don Ilodigwe; Hector Lantigua; Peter Le Roux; Benjamin Lo; Ada Louffat-Olivares; Stephan Mayer; Andrew Molyneux; Audrey Quinn; Tom A Schweizer; Thomas Schenk; Julian Spears; Michael Todd; James Torner; Mervyn D I Vergouwen; George K C Wong; Jeff Singh; R Loch Macdonald
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Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't; Review    
Journal Detail:
Title:  Neurocritical care     Volume:  18     ISSN:  1556-0961     ISO Abbreviation:  Neurocrit Care     Publication Date:  2013 Feb 
Date Detail:
Created Date:  2013-02-05     Completed Date:  2013-08-07     Revised Date:  2014-02-20    
Medline Journal Info:
Nlm Unique ID:  101156086     Medline TA:  Neurocrit Care     Country:  United States    
Other Details:
Languages:  eng     Pagination:  143-53     Citation Subset:  IM    
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MeSH Terms
Descriptor/Qualifier:
Decision Support Techniques*
Humans
Recovery of Function*
Subarachnoid Hemorrhage / mortality*
Treatment Outcome
Grant Support
ID/Acronym/Agency:
G0700479//Medical Research Council; //Canadian Institutes of Health Research; //Medical Research Council

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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