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Clinical prediction models for aneurysmal subarachnoid hemorrhage: a systematic review.

Publication ,  Journal Article
Jaja, BNR; Cusimano, MD; Etminan, N; Hanggi, D; Hasan, D; Ilodigwe, D; Lantigua, H; Le Roux, P; Lo, B; Louffat-Olivares, A; Mayer, S; Quinn, A ...
Published in: Neurocrit Care
February 2013

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.

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Published In

Neurocrit Care

DOI

EISSN

1556-0961

Publication Date

February 2013

Volume

18

Issue

1

Start / End Page

143 / 153

Location

United States

Related Subject Headings

  • Treatment Outcome
  • Subarachnoid Hemorrhage
  • Recovery of Function
  • Neurology & Neurosurgery
  • Humans
  • Decision Support Techniques
  • 4205 Nursing
  • 3209 Neurosciences
  • 3202 Clinical sciences
  • 1109 Neurosciences
 

Citation

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Jaja, B. N. R., Cusimano, M. D., Etminan, N., Hanggi, D., Hasan, D., Ilodigwe, D., … Macdonald, R. L. (2013). Clinical prediction models for aneurysmal subarachnoid hemorrhage: a systematic review. Neurocrit Care, 18(1), 143–153. https://doi.org/10.1007/s12028-012-9792-z
Jaja, Blessing N. R., Michael D. Cusimano, Nima Etminan, Daniel Hanggi, David Hasan, Don Ilodigwe, Hector Lantigua, et al. “Clinical prediction models for aneurysmal subarachnoid hemorrhage: a systematic review.Neurocrit Care 18, no. 1 (February 2013): 143–53. https://doi.org/10.1007/s12028-012-9792-z.
Jaja BNR, Cusimano MD, Etminan N, Hanggi D, Hasan D, Ilodigwe D, et al. Clinical prediction models for aneurysmal subarachnoid hemorrhage: a systematic review. Neurocrit Care. 2013 Feb;18(1):143–53.
Jaja, Blessing N. R., et al. “Clinical prediction models for aneurysmal subarachnoid hemorrhage: a systematic review.Neurocrit Care, vol. 18, no. 1, Feb. 2013, pp. 143–53. Pubmed, doi:10.1007/s12028-012-9792-z.
Jaja BNR, Cusimano MD, Etminan N, Hanggi D, Hasan D, Ilodigwe D, Lantigua H, Le Roux P, Lo B, Louffat-Olivares A, Mayer S, Molyneux A, Quinn A, Schweizer TA, Schenk T, Spears J, Todd M, Torner J, Vergouwen MDI, Wong GKC, Singh J, Macdonald RL. Clinical prediction models for aneurysmal subarachnoid hemorrhage: a systematic review. Neurocrit Care. 2013 Feb;18(1):143–153.
Journal cover image

Published In

Neurocrit Care

DOI

EISSN

1556-0961

Publication Date

February 2013

Volume

18

Issue

1

Start / End Page

143 / 153

Location

United States

Related Subject Headings

  • Treatment Outcome
  • Subarachnoid Hemorrhage
  • Recovery of Function
  • Neurology & Neurosurgery
  • Humans
  • Decision Support Techniques
  • 4205 Nursing
  • 3209 Neurosciences
  • 3202 Clinical sciences
  • 1109 Neurosciences