Flow Diversion versus Coiling with or without Stenting for Unruptured Wide-Neck Intracranial Aneurysms: A Randomized Comparison
Bibliographic record
Abstract
ABSTRACT BACKGROUND AND PURPOSE: There are few randomized trials comparing coiling (with or without stenting) and flow diversion (FD) for the treatment of wide-necked unruptured intracranial aneurysms (UIAs). MATERIALS AND METHODS: EVIDENCE was an investigator-led randomized (1:1) trial conducted in 7 French university hospitals. Patients with 7-20mm intradural UIAs with a 4-10mm neck and a “dome/neck” ratio ≥1 were randomly allocated to coiling with or without adjunctive stenting or FD alone. The composite primary efficacy outcome was “treatment failure,” defined as initial failure to treat the aneurysm; aneurysm rupture or retreatment during follow-up; death or dependency (mRS> 2); or an angiographic residual aneurysm adjudicated by an independent core laboratory at 12 months. The primary hypothesis (revised for slow accrual) was that FD would decrease treatment failures from 35% to 10%, requiring 90 patients. Primary analyses were intent to treat. RESULTS: Among the 91 enrolled patients, 4 (2 in each group) withdrew consent; 87 patients were included in the analysis: 43 in the FD group and 44 in the control group. Most patients had < 10mm (57/87; 65.5%) asymptomatic ophthalmic aneurysms (75/87, 82.2%). A poor primary outcome, ascertainable in 86 patients, was reached in 8/43 FD patients (18.6%, 95%CI 9.7%-32.6%) as compared to 10/43 coiling patients (23.3%, 95 CI 13.1%-37.7%) (RR = 0.80, 95%CI [0.35-1.83]; p=0.60). Serious adverse events were similar. CONCLUSIONS: For patients with mostly unruptured, wide-necked ophthalmic aneurysms <10mm, FD was not shown superior to coiling with or without stenting. ABBREVIATIONS: FD＝ Flow Diversion; SAC＝Stent-Assisted Coiling; UIAs＝ Unruptured Intracranial Aneurysms.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".