Bioactive versus bare platinum coils for the endovascular treatment of intracranial aneurysms: systematic review and meta-analysis of randomized clinical trials
Bibliographic record
Abstract
BACKGROUND: Bioactive coils were introduced in 2002 in an attempt to improve aneurysm healing and durability of angiographic results. Evidence demonstrating superior efficacy to justify the routine use of bioactive coils over bare coils is limited. We compared the periprocedural and clinical outcome after bioactive and bare platinum coiling for intracranial aneurysms. METHODS: MEDLINE, EMBASE, Cochrane Library, and ISI Web of Knowledge Conference Proceedings Citation Index-Science were searched for randomized clinical trials (RCTs) comparing bioactive and bare coils. The methodological quality was evaluated to assess bias risk. Periprocedural outcomes and mid-term outcomes were compared. RESULTS: Five independent RCTs comparing bioactive (n=1084) and bare coils (n=1084) were identified. Periprocedural outcome was similar for both groups. Bioactive coiling increased the rate of complete aneurysm occlusion (47% vs 40%; RR 1.17 (95% CI 1.05 to 1.31); p=0.006) and reduced the rate of residual aneurysm neck at 10 months compared with bare coiling in the mid-term (26% vs 31%; RR 0.82 (95% CI 0.70 to 0.96); p=0.01). There were no differences in aneurysm recurrence, aneurysm rupture, stroke, neurological death, modified Rankin Scale score and reinterventions. Subgroup analysis for the three RCTs on hydrogel coils demonstrated reduction of residual aneurysms compared with bare coiling (25% vs 34%; RR 0.76 (95% CI 0.58 to 0.99); p=0.04). CONCLUSIONS: Bioactive coils ensure a higher rate of medium-term complete aneurysm occlusion while reducing the rate of residual neck aneurysms compared with bare coiling in the mid-term. Hydrogel coils reduce residual aneurysms compared with bare coils. While there is level 1a evidence to show more complete aneurysm occlusion, longer term follow-up is needed to determine if this translates into clinical significance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.031 | 0.049 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".