Predictors of aneurysm occlusion after treatment with flow diverters: a systematic literature review.
J Neurointerv Surg
; 2023 Jun 14.
Article
em En
| MEDLINE
| ID: mdl-37316195
ABSTRACT
BACKGROUND:
Flow diverters (FDs) have become an integral part of treatment for brain aneurysms.AIM:
To summarize available evidence of factors associated with aneurysm occlusion (AO) after treatment with a FD.METHODS:
References were identified using the Nested Knowledge AutoLit semi-automated review platform between January 1, 2008 and August 26, 2022. The review focuses on preprocedural and postprocedural factors associated with AO identified in logistic regression analysis. Studies were included if they met the inclusion criteria of study details (ie, study design, sample size, location, (pre)treatment aneurysm details). Evidence levels were classified by variability and significancy across studies (eg, low variability ≥5 studies and significance in ≥60% throughout reports).RESULTS:
Overall, 2.03% (95% CI 1.22 to 2.82; 24/1184) of screened studies met the inclusion criteria for predictors of AO based on logistic regression analysis. Predictors of AO with low variability in multivariable logistic regression analysis included aneurysm characteristics (aneurysm diameter), particularly complexity (absence of branch involvement) and younger patient age. Predictors of moderate evidence for AO included aneurysm characteristics (neck width), patient characteristics (absence of hypertension), procedural (adjunctive coiling) and post-deployment variables (longer follow-up; direct postprocedural satisfactory occlusion). Variables with a high variability in predicting AO following FD treatment were gender, FD as re-treatment strategy, and aneurysm morphology (eg, fusiform or blister).CONCLUSION:
Evidence of predictors for AO after FD treatment is sparse. Current literature suggests that absence of branch involvement, younger age, and aneurysm diameter have the highest impact on AO following FD treatment. Large studies investigating high-quality data with well-defined inclusion criteria are needed for greater insight into FD effectiveness.
Texto completo:
1
Base de dados:
MEDLINE
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
/
Systematic_reviews
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article