Abstract T P319: Patient Characteristics and Outcomes in Pregnancy-Related Intracerebral Hemorrhage
Bibliographic record
Abstract
Background: Mortality rates as high as 20% have been reported for pregnant patients with intracerebral hemorrhage (ICH). The aim of this study is to describe the risk factors, management and outcomes of pregnant compared to non-pregnant patients with ICH in the Get With The Guidelines (GWTG) Stroke Registry. Methods: Using medical history or ICD-9 codes, we identified 178 pregnant and 4817 non-pregnant female patients aged 18-44 with ICH in GWTG from 2008-2013. Differences in patient and care characteristics were compared by Chi-square tests for categorical variables 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 ICH patients were younger, had fewer preexisting stroke risk factors and used fewer associated medications. Median initial blood pressures, initial neurologic exam findings and measures of guideline-based care were similar between groups (Table). Stroke onset did not occur in a healthcare setting for >85% of all patients, but pregnant patients took longer to arrive (median 268 vs. 186 min), used EMS less often (29% vs. 39%) and went to larger hospitals with higher annual ICH admissions than non-pregnant patients. Risk adjusted odds of in-hospital death in pregnant women were about half that of non-pregnant women (aOR 0.57, 95% CI 0.34-0.94), but length of stay >6 days (aOR 1.39, 95% CI 0.86-2.27), independent ambulation at discharge (aOR 1.12, 95% CI 0.81-1.54) and discharge to home (aOR 1.10, 95% CI 0.81-1.51) outcomes were similar. Conclusions: Pregnant women with ICH are younger and healthier than their non-pregnant counterparts but have similar presenting symptoms. Despite later arrival times, in-hospital mortality is lower, suggesting differences in underlying disease pathophysiology.
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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".