Abstract 82: Patient and Hospital Characteristics of Pregnancy-Related Stroke from the Get With The Guidelines Stroke Registry
Bibliographic record
Abstract
Background: Stroke accounts for 14% of maternal deaths. Our knowledge of the risk factors and etiologies of pregnancy-related stroke (PRS) is limited, as most data are derived from small, single center series or large, administrative datasets lacking clinical detail. We sought to describe the patient and hospital characteristics of PRS by analyzing the Get with the Guidelines (GWTG) Stroke Registry. Methods: All female patients aged 18-44 entered into GWTG from 2008-2013 with PRS were ascertained by medical history of pregnancy (i.e. pregnant or <6 weeks postpartum) plus a principal diagnosis ICD-9 code (430, 431) (58%), PRS ICD-9 code (671.5x, 673.04, 674.0x) as the principal diagnosis alone (18%), or with a medical history of pregnancy (24%). Proportions for categorical and medians for continuous variables are reported. Results: We identified 46043 patients with stroke from 1554 sites, of whom 668 (1.5%) had PRS. Ischemic stroke (IS) occurred in 338 (51%), intracerebral hemorrhage (ICH) in 178 (27%) and subarachnoid hemorrhage (SAH) in 152 (23%). Many patient and hospital characteristics differed significantly by stroke subtype (Table). Hypertension, smoking and pre-stroke therapy with antithrombotics or antihypertensives were common; 7.4% of IS were recurrent. About 86% of all strokes did not occur in a healthcare setting and only 27% of patients arrived by EMS. Median initial blood pressure (BP) was higher in HS (ICH and SAH) than in IS, and half of all patients had initial BP below the threshold for pre-eclampsia (140/90 mmHg). HS patients were more often treated at larger, academic hospitals. Conclusions: PRS constituted 1.5% of all strokes aged 18-44 in a large contemporary stroke registry and 50% were HS. Most PRS occurred out of hospital, and half of all cases presented with normal BP levels. Further research is needed to better define PRS etiology.
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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".