Comparison of the Topography of Carotid Territory Stenosis in North American and Iranian Stroke Patients
Bibliographic record
Abstract
Introduction: Atherosclerotic stenosis of carotid territory is the most common cause of ischemic stroke. A higher frequency of intracranial arterial stenosis has been reported in Africa and the Far East. Methods: 304 geriatric ischemic stroke patients admitted in Mackenzie hospital, Canada and the same number of geriatric ischemic stroke patients with similar sex ratio admitted in Valie-Asr hospital, Iran during 2003-2005 were enrolled in a double center and prospective study. Diagnosis of brain infarction in the carotid territory was made by stroke neurologists. All of the patients underwent transcranial and carotid doppler studies. Doppler studies performed were based on the standard method by a neurosonologist. Fisher exact test served for statistical analysis and p<0.05 was declared significant. Results: In Iranian group 71 patients (23.3%) and in North American group 83 patients (27.3%) had extracranial ICA stenosis without a significant difference df=1, p=0.305. Sever ³70% Extracranial ICA stenosis was found in 14 Iranian patients (4.6%) and 23 North American patients (7.5%) without a significant difference. df=1, p=0.17. In Iranian group, 14 cases (4.6%) and in North American group 5 cases (1.6%) had intracranial stenosis in carotid territory which was significantly different df=1, p=0.038. Mixed intracranial and extracranial carotid territory stenosis was present in 2 Iranian and 1 North American patient. Conclusion: Atherosclerotic stenosis of intracranial branches of carotid territory is more common in Iranian than North American populations.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".