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Outcomes and complications after endovascular treatment of brain arteriovenous malformations: a prognostication attempt using artificial intelligence

Asadi, Hamed, Kok, Hong Kuan, Looby, Seamus, Brennan, Paul, O'Hare, Alan and Thornton, John 2016, Outcomes and complications after endovascular treatment of brain arteriovenous malformations: a prognostication attempt using artificial intelligence, World neurosurgery, vol. 96, pp. 562-569.e1, doi: 10.1016/j.wneu.2016.09.086.

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Title Outcomes and complications after endovascular treatment of brain arteriovenous malformations: a prognostication attempt using artificial intelligence
Author(s) Asadi, HamedORCID iD for Asadi, Hamed orcid.org/0000-0003-2475-9727
Kok, Hong Kuan
Looby, Seamus
Brennan, Paul
O'Hare, Alan
Thornton, John
Journal name World neurosurgery
Volume number 96
Start page 562
End page 569.e1
Total pages 9
Publisher Elsevier
Place of publication Philadelphia, Pa.
Publication date 2016-12
ISSN 1878-8750
1878-8769
Keyword(s) arteriovenous malformation
endovascular embolization
interventional neuroradiology
neurosurgery
radiosurgery
Science & Technology
Life Sciences & Biomedicine
Clinical Neurology
Surgery
Neurosciences & Neurology
NATURAL-HISTORY
CLINICAL PRESENTATION
RANDOMIZED-TRIAL
GRADING SYSTEM
FOLLOW-UP
HEMORRHAGE
ARUBA
RISK
ANEURYSMS
PRESSURE
Summary PURPOSE: To identify factors influencing outcome in brain arteriovenous malformations (BAVM) treated with endovascular embolization. We also assessed the feasibility of using machine learning techniques to prognosticate and predict outcome and compared this to conventional statistical analyses.

METHODS: A retrospective study of patients undergoing endovascular treatment of BAVM during a 22-year period in a national neuroscience center was performed. Clinical presentation, imaging, procedural details, complications, and outcome were recorded. The data was analyzed with artificial intelligence techniques to identify predictors of outcome and assess accuracy in predicting clinical outcome at final follow-up.

RESULTS: One-hundred ninety-nine patients underwent treatment for BAVM with a mean follow-up duration of 63 months. The commonest clinical presentation was intracranial hemorrhage (56%). During the follow-up period, there were 51 further hemorrhagic events, comprising spontaneous hemorrhage (n = 27) and procedural related hemorrhage (n = 24). All spontaneous events occurred in previously embolized BAVMs remote from the procedure. Complications included ischemic stroke in 10%, symptomatic hemorrhage in 9.8%, and mortality rate of 4.7%. Standard regression analysis model had an accuracy of 43% in predicting final outcome (mortality), with the type of treatment complication identified as the most important predictor. The machine learning model showed superior accuracy of 97.5% in predicting outcome and identified the presence or absence of nidal fistulae as the most important factor.

CONCLUSIONS: BAVMs can be treated successfully by endovascular techniques or combined with surgery and radiosurgery with an acceptable risk profile. Machine learning techniques can predict final outcome with greater accuracy and may help individualize treatment based on key predicting factors.
Language eng
DOI 10.1016/j.wneu.2016.09.086
Field of Research 110399 Clinical Sciences not elsewhere classified
Socio Economic Objective 920111 Nervous System and Disorders
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2016, Elsevier
Persistent URL http://hdl.handle.net/10536/DRO/DU:30091508

Document type: Journal Article
Collections: Faculty of Health
School of Medicine
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