Abstract T MP43: Patient Characteristics and Outcomes in Pregnancy-Related Ischemic Stroke
Bibliographic record
Abstract
Background: Ischemic Stroke (IS) is a rare but serious event during pregnancy or the postpartum period. We compared the characteristics and outcomes of pregnant vs. non-pregnant women diagnosed with IS in the Get With The Guidelines Stroke Registry. Methods: We identified 24641 female patients aged 18-44 with IS, based on medical history or ICD-9 codes, from 2008-2013. Patient and hospital categorical variables were compared by Chi-square and continuous variables by Wilcoxon Rank-Sum. Stratified logistic regression assessed the effect of pregnancy on outcomes conditional on age and adjusted for patient and hospital characteristics. Results: There were 338 (1.4%) pregnant IS patients. Compared to non-pregnant patients, pregnant patients had fewer traditional stroke risk factors, were less often black, and were more likely to be insured by Medicaid, in a healthcare setting at stroke onset, and admitted to a stroke center. Both groups had similar initial mild stroke severity and exam findings most notable for weakness (Table). Discharge outcomes of in-hospital death (aOR 0.70, 95% CI 0.33-1.50), discharge to home (aOR 1.04, 95% CI 0.81-1.34), independent ambulation (aOR 1.03, 95% CI 0.79-1.34) or length of stay >4 days (aOR 1.27, 95% CI 0.96-1.68) did not differ between groups. Of the 145 cases where pregnancy stage was coded, 76 (52.4%) occurred postpartum and 65 (44.8%) antepartum, with no difference in discharge outcomes. Women with postpartum compared with antepartum IS were more likely to have hypertension, use antihypertensives pre-stroke, and have higher median initial post-stroke blood pressure. Conclusions: Pregnancy-related IS is uncommon and occurs in women with few traditional stroke risk factors, often within 6 weeks postpartum. Despite these differences, short term outcomes after stroke are similar to non-pregnant women. Further research is needed to determine if pregnancy, itself, independently contributes to stroke risk.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".