Intracranial GCA: a comprehensive systematic review
Bibliographic record
Abstract
OBJECTIVES: GCA is increasingly recognized to occur in intracranial vessels with unknown clinical ramifications. We identified all reported cases of intracranial GCA (ICGCA) in the literature to describe common presentations, investigations, treatments and outcomes. METHODS: We conducted a systematic review using MEDLINE (Medical Literature Analysis and Retrieval System Online), Embase and PubMed databases to identify studies that reported cases of ICGCA. The study was registered on a systematic review database (PROSPERO 42023412373). We defined intracranial involvement as any vessel cranial to the dura mater that was confirmed by either histopathology or imaging. Data were summarized using descriptive statistics. RESULTS: Of 1554 studies identified, 102 studies underwent full-text review. These studies included 340 patients with ICGCA. The median age was 73.7 (interquartile range [IQR] 71.9-77.3) and 46.9% patients were female. Presentations of ICGCA included stroke in 240 (70.6%) patients and isolated intracranial imaging or histologic changes in 67 (19.7%) patients. The most common vessels involved were 180 (52.9%) vertebrobasilar, 166 (48.8%) internal carotid and 49 (14.4%) ophthalmic arteries. Treatment was reported in 214 individuals. Glucocorticoids were administered to 210 (98.1%); tocilizumab, cyclophosphamide and methotrexate were the most common adjunctive medications. Of the 181 patients with reported follow-up outcomes, relapse occurred in 40 (22.1%) patients and 59 (32.6%) individuals died. CONCLUSION: Our findings suggest that ICGCA is not a rare entity and may represent a more severe manifestation of GCA. Optimal therapy for ICGCA is unknown. Structured prospective evaluation is needed to better understand this manifestation of GCA.
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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 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.014 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".