Abstract T P399: Patient Characteristics and Outcomes in Pregnancy-Related Subarachnoid Hemorrhage
Bibliographic record
Abstract
Background: Subarachnoid hemorrhage (SAH) accounts for up to 4.1% of all pregnancy-related in-hospital deaths, but is less often aneurysmal and is associated with better short term outcomes than in non-pregnant patients. We sought to describe the risk factors, management and outcomes of pregnant vs. non-pregnant patients with SAH in the Get With The Guidelines (GWTG) Stroke Registry. Methods: Using medical history or ICD-9 codes, we identified 152 pregnant and 5745 non-pregnant SAH female patients aged 18-44 with SAH in GWTG from 2008-2013. Differences in characteristics were compared by Chi-square tests for categorical and Wilcoxon Rank-Sum tests for continuous variables. Stratified logistic regression assessed the effect of pregnancy on outcomes conditional on age and adjusted for patient and hospital characteristics. Results: Pregnant SAH patients were younger, more often black and insured with Medicaid. They had higher initial blood pressure (BP) and were less likely to report prior hypertension. Arrival delays from stroke onset were common in both groups (median 340 vs. 277 min), but pregnant SAH patients were more often already hospitalized at stroke onset (16% vs. 10%). Fewer pregnant vs. non-pregnant SAH patients had initial neurologic exam findings recorded (Table). Pregnant SAH patients had lower in-hospital death than non-pregnant patients (aOR 0.17, 95% CI 0.06-0.45) and were more likely at discharge to ambulate independently (aOR 2.40, 95% CI 1.56-3.69) and return home (aOR 2.60, 95% CI 1.67-4.06). Conclusions: Several differences exist between pregnant and non-pregnant women with SAH. Many present with BP well below the threshold for hypertensive disorders of pregnancy, making prompt recognition and prevention of brain hemorrhage challenging. Overall, pregnancy-related SAH is associated with less morbidity and mortality than non-pregnancy related disease.
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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".