Treatment of wide-necked bifurcation aneurysms with the eCLIPs device: 5-year experience of a single center
Bibliographic record
Abstract
BACKGROUND: The endovascular clip system (eCLIPs) is a novel device with both neck bridging and flow-diversion properties that make it suitable for the treatment of wide-necked bifurcation aneurysms. OBJECTIVE: To describe the clinical and radiologic outcomes of the eCLIPs device, including the first-in-man use of the latest version of the device. METHODS: This is a retrospective case series on all the wide-necked bifurcation aneurysms treated with the eCLIPs device in our center. The immediate and latest radiologic and clinical outcomes were assessed. RESULTS: The device was successfully implanted in 12 of 13 patients. After a median follow-up period of 19 months (range 3-64 months), all patients with available data (11/12) had a good radiologic outcome (modified Raymond-Roy classification scores of 1 or 2). Two patients (18.2%) underwent re-treatment with simple coiling through the device. One of these had a subarachnoid hemorrhage prior to re-treatment. There were no major complications (death or permanent neurologic deficits) associated with use of the device. CONCLUSION: Our series demonstrates occlusion rates that are similar to those of standard stent-assisted coiling and intrasaccular flow diversion for wide-necked bifurcation aneurysms. Larger registry-based studies are necessary to support our findings.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".