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Updated: May 10, 2026

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The Helsinki Rat Microsurgical Sidewall Aneurysm Model
Published on: October 12, 2014
A predictive model of outcomes during cerebral aneurysm coiling
Kimon Bekelis1, Symeon Missios, Todd A Mackenzie
1Section of Neurosurgery, Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire, USA.
Journal of Neurointerventional Surgery
|July 6, 2013
Summary
A new predictive model helps anticipate negative outcomes after cerebral aneurysm coiling (CACo). This tool aids clinicians in tailoring treatments and improving patient care for cerebral aneurysms.
Area of Science:
- Neurosurgery
- Interventional Neurology
- Health Services Research
Background:
- Benchmarking complications is crucial for accountable care in neurosurgery.
- Developing predictive models for negative outcomes in cerebral aneurysm coiling (CACo) is essential.
Purpose of the Study:
- To create a predictive model for negative outcomes in patients undergoing cerebral aneurysm coiling.
- To identify risk factors associated with postoperative complications.
Main Methods:
- Retrospective cohort study of 10,607 patients undergoing CACo (2005-2009) from the Nationwide Inpatient Sample database.
- Development and validation of a predictive model using individual patient characteristics.
- Multivariate analysis to identify independent risk factors for various complications.
Main Results:
- The study analyzed outcomes for both unruptured (57.1%) and ruptured (42.9%) aneurysms.
- Identified significant inpatient postoperative risks including death, unfavorable discharge, stroke, and specific complications.
- The developed model demonstrated good predictive discrimination, validated by the area under the receiver operating characteristic curve.
Conclusions:
- The validated model can predict the incidence of postoperative complications following cerebral aneurysm coiling.
- This predictive tool can assist in personalizing treatment strategies for cerebral aneurysms.
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