Stroke Education for Obstetric Providers: A Single-Center Pilot Following a Case of Delayed Recognition of Postpartum Intracerebral Hemorrhage
Bibliographic record
Abstract
Background: Stroke is three times more likely in obstetric patients than in age-adjusted non-pregnant women. No studies have focused on obstetric provider education for stroke management. A case of a postpartum woman with intracerebral hemorrhage at a large obstetrics hospital spurred modification of the code stroke protocol and an educational seminar on neurologic emergencies geared towards obstetric providers. The effectiveness of stroke triage training to improve understanding of management in obstetric patients was assessed. Methods: Obstetric providers were assessed before and after attending a 1-h educational seminar by stroke experts from the affiliated comprehensive stroke center at an associated large academic institution. The knowledge assessment included seven questions about concerning symptoms and initial steps in management of suspected stroke. Results: Twenty-eight out of 48 participants completed before and after knowledge assessments. The average increase in point score was 1.25 (21%). The greatest post-education increases occurred regarding blood pressure augmentation during a stroke alert (18% to 82% correct) and initial tests needed for evaluation (36% to 89% correct). Providers learned head imaging must be obtained to differentiate between types of strokes before treating hypertension, and labs, except finger stick glucose, are not needed before administering a thrombolytic. Conclusions: Obstetric patients are at increased risk of stroke, and targeted clinician education can improve knowledge of initial management steps. Obstetric practices should consider additional education for nurses and providers on managing stroke, as proper stroke management is time sensitive and can reduce maternal mortality. J Clin Gynecol Obstet. 2024;13(1):1-7 doi: https://doi.org/10.14740/jcgo943
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".