Comparaison de l'étendue de l'accident vasculaire cérébral ischémique dû à une occlusion cérébrale proximale chez les patients afro-caribéens et caucasiens
Bibliographic record
Abstract
Purpose of the study : Comparison of the cerebral infarct extension between Afro-Caribbean and Caucasian population in large vessel occlusion (LVO) strokes eligible for endovascular treatment (EVT). The aim is to determine the impact of ethnicity on infarct volume at time of diagnosis. Material : A retrospective comparative study conducted from January 2021 to January 2023, between Afro-Caribbean patients from Guadeloupe and Caucasian patients from the European territory of France (ETIS registry). All patients were admitted for LVO stroke and candidates for EVT. The primary endpoint was the infarct core volume measured with ASPECTS (Alberta Stroke Program Early CT Score) score at time of diagnosis. Results : 76 patients from Guadeloupe were matched to 220 patients from ETIS registry on age, sexe, clinical severity (NIHSS), onset-to-imaging delay and occlusion site. ASPECTS was significantly lower in Guadeloupe patients (mean estimates 6.97) than in ETIS patients (mean estimates 7.55) with a mean difference of 0.58. After adjustment on cardiovascular risk factors (dyslipidemia, hypertension, diabetes and smoking), results remained unchanged, with a mean difference of 0.61. Conclusion : In this population of patients with LVO and candidates for EVT, we found a larger infarct core at diagnosis in the Afro Caribbean population in comparison with the Caucasian population.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".