Abstract DP51: Migraine with Aura is Associated with Increased 90-day Ischemic Stroke Risk
Bibliographic record
Abstract
Background: Migraine with aura (MA) is recognized as an independent risk factor for acute ischemic stroke (AIS). However, the short-term risk of stroke, particularly within 90 days of hospitalization, has not been thoroughly evaluated on a national scale. This study aims to address this gap by examining the association between MA and 90-day AIS readmission. Methods: Using the National Readmission Database between 2016 and 2019, we identified patients admitted with a principal or non-principal diagnosis of migraine. The reference group for analysis contained all adult patients admitted during the study period without migraine. The primary outcome was subsequent AIS admission within 90 days. Diagnoses were identified using standard ICD-10-CM codes. A multivariable Cox regression model was employed to assess the risk of AIS readmission risk in patients with MA, adjusted for significant cardiovascular risk factors. Interaction analyses were conducted to determine whether traditional cardiovascular risk factors influenced the association between MA and subsequent AIS risk. Results: Among 106,608,073 patients (mean age 46.48, 57.86% female) admitted during the study period, 1,711,841 (1.61%) patients were admitted with any migraine diagnosis and 101,278 (0.10%) were admitted with MA. Within 90 days, 411,850 (0.39%) patients had a subsequent admission for AIS. After adjusting for sex, coronary artery disease, atrial fibrillation, hypertension, hyperlipidemia, diabetes mellitus, and smoking, patients with MA demonstrated an elevated risk for 90-day AIS (adjusted hazard ratio [aHR] 1.76, 95% CI 1.56-1.99, p < 0.001). Migraine without aura was not associated with increased AIS risk (aHR 1.02, 95% CI 0.84-1.23, p=0.846). Significant interactions were observed with age, sex, hypertension, and atrial fibrillation (Figure). Conclusions: In this large patient cohort, migraine with aura was associated with an increased risk of AIS readmission within 90 days, particularly in patients without traditional cardiovascular risk factors. These findings underscore the need for potentially more aggressive stroke prevention strategies in patients with MA. Future research should investigate the pathomechanisms underlying this association.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".