Periprocedural complications of second-generation flow diverter treatment using Pipeline Flex for unruptured intracranial aneurysms: a systematic review and meta-analysis
Bibliographic record
Abstract
Background Flow diverters are a breakthrough treatment for large and giant intracranial aneurysms but carry a risk of periprocedural death or major stroke. Pipeline Flex is a second-generation device that is thought to have lower complication rates because of improvements in the delivery system as well as increased operator experience. Our objective was to analyze the risk of periprocedural death or major complications using Pipeline Flex for unruptured intracranial aneurysms. Methods A systematic search of three databases was performed for studies of ≥10 treatments using Pipeline Flex for unruptured intracranial aneurysms (2014–2019) using PRISMA guidelines. Random effects meta-analysis was used to pool the rates of periprocedural (<30 days) death, major ischemic stroke, symptomatic intracranial hemorrhage, and minor stroke/transient ischemic attack. Results We included eight studies reporting 901 treatments in 879 patients. Periprocedural mortality (<30 days) was 0.8% (5/901; 95% CI 0.4% to 1.5%; I2=0%). Rate of major complications (death, major ischemic stroke, or symptomatic intracranial hemorrhage) was 1.8% (14/901; 95% CI 1.0% to 2.7%; I2=0%). Aneurysm size ≥10 mm was a statistically significant predictor of a major complication (OR 6.4; 95% CI 2.0 to 20.7; p=0.002). Risk of a major complication in aneurysms <10 mm was 0.9% (95% CI 0.3% to 1.7%; I2=0%). The meta-analysis was limited by the predominance of anterior circulation aneurysms. Conclusion Treatment of unruptured intracranial aneurysms using the Pipeline Flex flow diverter has a low periprocedural risk of death (0.8%) or major complication (1.8%). The risk of a major complication is significantly higher for large/giant aneurysms (4.4%) and is very low for aneurysms <10 mm (0.9%).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.031 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".