Markers of Giant Cell Arteritis in Patients Presenting With Ischemic Stroke: A Scoping Review
Bibliographic record
Abstract
BACKGROUND: In patients with giant cell arteritis (GCA), 2.8%-8.2% present with ischemic stroke (IS) or transient ischemic attack (TIA). GCA diagnosis may be overlooked, and immunosuppressive treatment delayed if typical symptoms are absent or if a common cause of IS coexists. This study aimed to identify potential markers of GCA through clinical evaluation and baseline investigation of IS/TIA patients. METHODS: Two authors independently conducted a scoping review using MEDLINE and EMBASE databases to identify patients diagnosed with GCA after presenting with IS/TIA. All articles, including the gray literature, were considered from January 2000 onwards if individualized data were described. Only cases of IS/TIA with GCA later diagnosed as the etiology were included for analysis. RESULTS: A total of 101 publications were included, pooling data on 141 patients for analysis. The mean age was 73.6 years, and 61 were women. Patients experienced either single (56.0%) or multiple IS/TIA events (44.0%). Associated symptoms included GCA-related pain, such as headaches (50.4%), constitutional symptoms (47.5%), and temporal artery inflammation (27.0%). Neurological deficits involved corticospinal tracts (41.8%), and cerebellar functions (53.2%). Most patients had clinical or radiological evidence of vertebrobasilar involvement (83.7%). Multifocal involvement of the vertebrobasilar and carotid territories was supported when combining clinical-radiological manifestations (41.1%). Recurrent events were common (44.0%). CONCLUSION: GCA should be considered in IS/TIA patients aged ≥ 50 years with vertebrobasilar or multiterritorial involvement, or recurrent IS/TIA despite secondary prevention.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.019 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".