Endovascular Treatment or Neurosurgical Clipping of Ruptured Intracranial Aneurysms
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The effects of aneurysm treatment modality (clipping or coiling) on the incidence of cerebral vasospasm and infarction after subarachnoid hemorrhage have not been clearly defined. We hypothesized that there may be a difference in angiographic and clinical vasospasm, cerebral infarction, and clinical outcome between patients undergoing clipping compared to coiling. METHODS: A retrospective, exploratory analysis of 413 patients randomized into the CONSCIOUS-1 trial was conducted. Patients underwent baseline and follow-up catheter angiography and computed tomography, as well as clinical assessments. Radiology end points were adjudicated by central blinded review, and angiographic vasospasm was quantified by measurements of arterial diameters on catheter angiography. The effect of method of aneurysm treatment (clipping [n=199] or coiling [n=214]) on angiographic vasospasm, delayed ischemic neurological deficit, cerebral infarction, and clinical outcome was analyzed using univariate and multivariate logistic regression. Propensity matching was used to adjust for differences in baseline risk factors between clipped and coiled patients. RESULTS: In all patients and the propensity-matched subset, aneurysm coiling was associated with a significantly reduced risk of angiographic vasospasm and delayed ischemic neurological deficit compared to clipping. Cerebral infarction and clinical outcome were not associated with clipping or coiling. CONCLUSIONS: In this exploratory analysis, aneurysm coiling was associated with less angiographic vasospasm and delayed ischemic neurological deficit than surgical clipping, whereas no effect on cerebral infarction or clinical outcome was observed. Whether this is attributable to differences in baseline risk factors between clipped and coiled patients or a true difference cannot be proven here.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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 teacher head, 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".