Editorial: Intracranial aneurysms, AVM and other vascular malformations, and connective tissue disorders as potential causes of stroke: advances in diagnosis and therapeutics including novel neurosurgical techniques
Bibliographic record
Abstract
The cerebral vasculature is a marvel of complexity and when disrupted by aneurysms, AVMs, or vascular malformations associated with connective tissue disorders, it becomes a critical substrate for ischemic and hemorrhagic stroke. This Research Topic in Frontiers in Neurology curates multidimensional contributions that unify genetics, computational modeling, clinical diagnostics, and procedural advances, collectively moving the field toward more individualized and proactive care models. Systemic inflammation and autoimmune disease have emerged as independent risk factors for aneurysm formation. (Shotar et al., 2024). Genetic investigations by Neyazi et al. found that CEACAM1 and IL-6 polymorphisms, along with sex-based immunologic differences, may underlie hemorrhagic risk in AVM carriers, suggesting that inflammation is both a symptom and a pathogenic driver (Neyazi et al., 2024). Finally, the issue turns a spotlight on connective tissue disorders where under-recognized risk meets preventable catastrophe. Kim, Brinjikji, and Kallmes reported aneurysm prevalence as high as 28% in patients with Ehlers-Danlos, Marfan, and Loeys-Dietz syndromes far exceeding the general population rate of 3% (Kim et al., 2016). These data argue for systematic screening in patients with heritable vasculopathies and call for collaboration between neurologists, geneticists, and vascular surgeons.In summary, this collection crystallizes three pillars of modern vascular neurology: inflammation and genetics as risk predictors, hemodynamic modeling as both diagnostic and therapeutic aid, and procedural refinement as a vehicle for safer, personalized interventions. Despite these gains, several gaps persist particularly in unifying risk scores, validating CFD parameters across platforms, and embedding genomic screening into standard practice. The future of stroke prevention in vascular malformations lies not in a single discipline but in cross-disciplinary synthesis, where predictive algorithms, surgical precision, and molecular insight converge at the bedside.
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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 | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.011 | 0.016 |
| Insufficient payload (model declined to judge) | 0.024 | 0.016 |
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".