A Pragmatic Randomized Trial Comparing Surgical Clipping and Endovascular Treatment of Unruptured Intracranial Aneurysms
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Surgical clipping and endovascular treatment are commonly used in patients with unruptured intracranial aneurysms. We compared the safety and efficacy of the 2 treatments in a randomized trial. MATERIALS AND METHODS: Clipping or endovascular treatments were randomly allocated to patients with one or more 3- to 25-mm unruptured intracranial aneurysms judged treatable both ways by participating physicians. The study hypothesized that clipping would decrease the incidence of treatment failure from 13% to 4%, a composite primary outcome defined as failure of aneurysm occlusion, intracranial hemorrhage during follow-up, or residual aneurysms at 1 year, as adjudicated by a core lab. Safety outcomes included new neurologic deficits following treatment, hospitalization of >5 days, and overall morbidity and mortality (mRS > 2) at 1 year. There was no blinding. RESULTS: Two hundred ninety-one patients were enrolled from 2010 to 2020 in 7 centers. The 1-year primary outcome, ascertainable in 290/291 (99%) patients, was reached in 13/142 (9%; 95% CI, 5%–15%) patients allocated to surgery and in 28/148 (19%; 95% CI, 13%–26%) patients allocated to endovascular treatments (relative risk: 2.07; 95% CI, 1.12–3.83; P = .021). Morbidity and mortality (mRS >2) at 1 year occurred in 3/143 and 3/148 (2%; 95% CI, 1%–6%) patients allocated to surgery and endovascular treatments, respectively. Neurologic deficits (32/143, 22%; 95% CI, 16%–30% versus 19/148, 12%; 95% CI, 8%–19%; relative risk: 1.74; 95% CI, 1.04–2.92; P = .04) and hospitalizations beyond 5 days (69/143, 48%; 95% CI, 40%–56% versus 12/148, 8%; 95% CI, 5%–14%; relative risk: 0.18; 95% CI, 0.11–0.31; P < .001) were more frequent after surgery. CONCLUSIONS: Surgical clipping is more effective than endovascular treatment of unruptured intracranial aneurysms in terms of the frequency of the primary outcome of treatment failure. Results were mainly driven by angiographic results at 1 year.
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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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".