Neurosurgery Blog: Clinical Prediction Models for Aneurysmal Subarachnoid Hemorrhage: A Systematic Review

Abstract

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.

Content Type Journal Article
Category Original Article
Pages 1-11
DOI 10.1007/s12028-012-9792-z
Authors
- Blessing N. R. Jaja, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada
- Michael D. Cusimano, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada
- Nima Etminan, Heinrich Heine University, Düsseldorf, Germany
- Daniel Hanggi, Heinrich Heine University, Düsseldorf, Germany
- David Hasan, University of Iowa, Iowa, IA, USA
- Don Ilodigwe, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada
- Hector Lantigua, Columbia University, New York, NY, USA
- Peter Le Roux, University of Pennsylvania, Philadelphia, PA, USA
- Benjamin Lo, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada
- Ada Louffat-Olivares, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada
- Stephan Mayer, Columbia University, New York, NY, USA
- Andrew Molyneux, Oxford University, Oxford, UK
- Audrey Quinn, Leeds Teaching Hospitals NHS Trust, Leeds, UK
- Tom A. Schweizer, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada
- Thomas Schenk, King's College London, London, UK
- Julian Spears, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada
- Michael Todd, University of Iowa, Iowa, IA, USA
- James Torner, University of Iowa, Iowa, IA, USA
- Mervyn D. I. Vergouwen, University Medical Center Utrecht, Utrecht, Netherlands
- George K. C. Wong, Chinese University of Hong Kong, Hong Kong, China
- Jeff Singh, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada
- R. Loch Macdonald, Division of Neurosurgery, St. Michael's Hospital, University of Toronto, 30 Bond Street, Toronto, ON M5B 1W8, Canada