Efficacy of pCONUS Devices in the Management of Intracranial Aneurysms: Outcomes of 190 Patients
Bibliographic record
Abstract
Intracranial aneurysms (IAs) pose a significant health concern, necessitating effective treatment modalities. The pCONUS device has emerged as a promising option for managing complex IAs, particularly wide-necked bifurcation aneurysms. Evaluating its efficacy across multiple studies is essential for establishing therapeutic guidelines. A systematic review was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to identify studies assessing the efficacy of pCONUS devices in treating cerebral aneurysms. PubMed, Google Scholar, and Scopus were searched for relevant articles published from January 1, 2000, to December 31, 2021. Inclusion criteria encompassed clinical trials examining pCONUS device benefits for ruptured or unruptured cerebral aneurysms. Data extraction and quality assessment were performed independently by two reviewers. Out of 390 initially identified articles, eight studies met the inclusion criteria. These studies collectively involved 190 participants with intracranial aneurysms. The sample sizes ranged from seven to 40 patients, predominantly in retrospective designs. Complete occlusion rates varied from 46.8% to 100%, with a mean diameter of treated aneurysms ranging from 2.5 mm to 8.83 mm. This systematic review suggests that pCONUS devices are feasible and effective for treating complex bifurcation cerebral aneurysms, with acceptable complication rates. Despite limitations such as retrospective study designs and limited follow-up durations, the findings support the beneficial role of pCONUS devices in managing challenging intracranial aneurysms. Larger collaborative efforts with longer follow-up durations are warranted to validate these findings and establish wider therapeutic guidelines.
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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 | 0.012 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.013 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".