Abstract WP280: Systolic Blood Pressure During Presentation of Acute Ischemic Stroke Predicts Cardioembolic Etiology
Bibliographic record
Abstract
Introduction: Determining stroke etiology is essential to stroke prevention. Deciding which patients require extensive cardiac investigations, and with what priority, is a topic of controversy. Hypothesis: We hypothesize that a lack of hypertension at the time of presentation with acute ischemic stroke predicts cardioembolic etiology. Methods: Patients presenting with acute (< 6 hours) ischemic stroke were consecutively enrolled from a single institution between 2015 and 2017. The primary outcome was cardioembolic etiology diagnosis at 6 months. Presenting systolic blood pressure was categorized as: hypotensive (<110 mmHg), normotensive (110-149 mmHg), and hypertensive (>150 mmHg). Multivariable logistic regression was used to adjust for relevant covariates, which were selected via exploratory univariate analysis (p<0.1). Results: Of the 151 patients included in primary analysis, 64 (42%) were diagnosed with a cardioembolic source at 6 months. After adjusting for age, known cardiac disease (atrial fibrillation, congestive heart failure, valvular disease), and clinical severity, patients presenting with hypo or normotensive systolic pressure were significantly associated with cardioembolic diagnosis at 6 months (n= 37, aOR 3.25, 95% CI: 1.17- 9.06). The association between systolic pressure and cardioembolic diagnosis increased in a dose-like manner (hypotensive: aOR 7.66, 95% CI: 0.80-73.30, normotensive: aOR 2.99, 95% CI: 1.04-8.58). Conclusions: This study provides preliminary confirmation of our hypothesis that patients who are not hypertensive at the time of acute ischemic stroke are more likely to have suffered a stroke that is cardioembolic in origin. These patients may warrant more thorough cardiac investigations or other alterations to management.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".