Embolization with larger-caliber coils can increase packing density: Evidence from the pilot phase of a randomized trial
Bibliographic record
Abstract
Background and purpose Endovascular coil embolization of cerebral aneurysms is associated with suboptimal angiographic results in up to 20-30% of patients. Coil packing density has been used as an index of the success of the initial procedure. The trial sought to study the effects of using 15-caliber coils, as compared with 10-caliber coils, on packing density. Methods Does Embolization with Larger coils lead to better Treatment of Aneurysms (DELTA) is an investigator-initiated multicenter prospective, randomized, controlled clinical trial. Patients are randomized 1:1 to embolization with either 10-caliber coils exclusively (control group) or the highest safely achievable proportion of 15-caliber coils and 10-caliber coils if necessary (intervention group) in 4-12-mm aneurysms. The endpoint of the pilot phase of the trial was the capacity to increase packing density of the initial procedure, calculated using a mathematical transformation of the dimensions entered into the case report forms. Secondary outcomes included the total number of coils used per aneurysm, total fluoroscopy time, initial angiographic outcomes and any adverse or undesirable event. Results Seventy patients were recruited between June 2014 and November 2015. Compared with 10-caliber coils, the 15-caliber coil group had a higher median packing density (44% vs 24%, p = 0.017). Results of other outcome measures were similar for the two groups. Conclusion Coiling of small and medium aneurysms randomized to 15-caliber coils achieved higher packing densities compared with coiling using 10-caliber coils.
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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 | 0.018 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".