Normal Systolic Blood Pressure at Presentation With Acute Ischemic Stroke Predicts Cardioembolic Etiology
Bibliographic record
Abstract
Background Early insight into the possible etiology of ischemic stroke allows for early initiation of mechanism-specific secondary stroke prevention. Initial systolic blood pressure during acute ischemic stroke may relate to stroke etiology. We sought to determine whether normotension at presentation with acute ischemic stroke predicts cardioembolic etiology. Methods and Results All patients presenting with acute ischemic stroke within 12 hours of symptom onset at a comprehensive stroke center from January 2015 to December 2017 were assessed. Normotension was defined as systolic blood pressure ≤130 mm Hg. The primary exposure was blood pressure on arrival at the hospital, and the primary outcome was cardioembolic etiology. Multivariable regression with stepwise selection was used to adjust for relevant covariates. We included 683 patients in our analysis, 303 (44%) of whom were diagnosed with cardioembolic etiology at 6 months. The probability of cardioembolic etiology was inversely associated with systolic blood pressure, and initial systolic blood pressure was significantly associated with cardioembolic etiology (odds ratio: 1.15; 95% CI, 1.05 to 1.26). Normotension was associated with 2.62-fold increased odds of cardioembolic etiology (95% CI, 1.46 to 4.72). Conclusions Normotension at presentation with acute ischemic stroke strongly predicts cardioembolic etiology. These patients may especially benefit from early and prolonged cardiac investigations.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".