Title |
Clinical Prediction Models for Aneurysmal Subarachnoid Hemorrhage: A Systematic Review
|
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Published in |
Neurocritical Care, November 2012
|
DOI | 10.1007/s12028-012-9792-z |
Pubmed ID | |
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 |
Abstract |
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. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Netherlands | 1 | <1% |
Denmark | 1 | <1% |
Canada | 1 | <1% |
Unknown | 124 | 98% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 28 | 22% |
Student > Ph. D. Student | 13 | 10% |
Student > Master | 13 | 10% |
Student > Doctoral Student | 11 | 9% |
Student > Postgraduate | 8 | 6% |
Other | 27 | 21% |
Unknown | 27 | 21% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 58 | 46% |
Neuroscience | 15 | 12% |
Computer Science | 4 | 3% |
Agricultural and Biological Sciences | 3 | 2% |
Nursing and Health Professions | 2 | 2% |
Other | 7 | 6% |
Unknown | 38 | 30% |