Coil type does not affect angiographic follow-up outcomes of cerebral aneurysm coiling: a systematic review and meta-analysis

Abstract

Background and purpose: Previous studies varied in their conclusions about the superiority of second-generation coils compared with bare platinum. In this systematic review and meta-analysis, we assessed differences in reported unfavorable angiographic outcomes of cerebral aneurysms treated with coil embolization as a function of coil type.

Materials and methods: This systematic review covered 1999-2011 through the use of Ovid MEDLINE and EMBASE. Search terms were "subarachnoid hemorrhage," "intracranial aneurysms," "endovascular treatment," and "coiling." Inclusion criteria were studies reporting >50 aneurysms with imaging follow-up. We defined "unfavorable angiographic outcome" as either "recanalization," <90% occlusion, or "incomplete occlusion" at follow-up. Rates of unfavorable outcomes were pooled through the use of random effects models and compared across various coil types. Multivariate random effects meta-regression models were used to further explore the differences in outcomes related to coil type.

Results: We included 82 studies, comprising 90 patient cohorts, among which, 65 (72%) used bare platinum coils, 8 (8.9%) used Matrix, 11 (12%) used HydroCoil, and 6 (6.7%) used Cerecyte. The overall unfavorable outcome rate was 19% (95% CI: 17%,21%). Unfavorable outcome rates were 20% (95% CI: 17%, 22%) for bare platinum coils, 23% (95% CI: 16%, 29%) for Matrix, 15% (95% CI: 9%, 21%) for HydroCoil, and 15% (95% CI: 7%, 23%) for Cerecyte, respectively. The difference in unfavorable outcome rates among the various coil types was not statistically significant after adjusting for baseline characteristics, including aneurysm size, rupture status, and follow-up duration.

Conclusions: The rate of unfavorable angiographic outcomes was not statistically different across the major approved coil types. The quality of the evidence, however, remains low because of high heterogeneity, small sample size, and potential publication bias.

Fig 1.

Search strategy in a flow chart along with reasons for exclusion.

Fig 2.

Forest plot shows the pooled outcome estimates from random effects analysis.

Fig 3.

Quality assessment of the included studies.