Abstract 38: Hemorrhagic Strokes in Patients With Atrial Fibrillation: The Neuro-AFib Study
Bibliographic record
Abstract
Background: We aimed to compare the clinical features and short-term outcomes of hemorrhagic stroke (HS) to ischemic stroke (IS) in atrial fibrillation (AF) patients using a large contemporary cohort. Methods: The Neuro-AFib study is a multicenter effort to elucidate the current causes and consequences of IS and HS in AF patients. The retrospective phase of the study is underway, aimed at obtaining detailed clinical, laboratory and multimodal neuro- and cardiac imaging data from ~9,000 patients with AF admitted to 30 academic stroke centers in the US with an IS or HS between 1/2018-12/2019. Preliminary clinical data from 12 sites are presented in this abstract. Results: Of 4764 stroke admissions with AF, 820 (17.2%) had HS and 3944 IS. Patients with HS were younger (74.8 + 12 vs 76.8 + 12), more likely to be male (54% vs 46%) and had lower CHA 2 DS 2 -VASC (3.6 + 1.6 vs 3.9 + 1.6) than IS [all p<0.05]. Patients with HS were more likely to be on AC compared to IS (60% vs 38%, p<0.001). Within the HS cohort, 32% were on direct oral anticoagulant, 28% on warfarin, 16% on antiplatelet, and 24% on no antithrombotic. Patients with HS had worse outcomes than IS in terms of in hospital case fatality (32.4 vs 10.3%, p<0.001) and severe disability (modified Rankin Scale 4-5) at discharge (63.3% vs 53.7%, p=0.002) despite similar rates of severe disability before admission (7% vs 6.2%, p=0.73). All of the reported associations remained significant after adjustment for age, sex and other relevant covariates. Conclusions: Preliminary findings from the Neuro-AFib study show significantly worse outcomes for HS compared to IS in AF patients, with triple case fatality and elevated severe disability risks. These results showcase the importance of identifying AF patients at high HS risk. Detailed imaging markers of HS risk including microbleeds, superficial siderosis, leukoaraiosis within the full cohort will be analyzed and discussed during ISC 2021.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".