Headache as a Predictive Factor of Severe Systolic Hypertension in Acute Ischemic Stroke
Bibliographic record
Abstract
BACKGROUND: Elevation of blood pressure (BP) is common in acute cerebral infarction, with several studies reporting a high plasma catecholamine level or previous hypertension as a contributory factor. However, more comprehensive studies on associated clinical parameters are lacking. Our main aim in undertaking this study was to correlate clinical variables associated with a BP elevation in acute ischemic stroke. METHODS: Consecutive patients who were admitted to the emergency room and diagnosed with an acute cerebral infarction within 24 hours after the onset of symptoms were investigated. A BP elevation was defined as a high systolic (> or = 200mmHg) or diastolic (> or = 110 mmHg) pressure. The mean systolic and diastolic BP were compared between the different stroke subtypes, lesion locations (carotid vs. vertebrobasilar), and hemispheric sides. The frequency of symptoms, risk factors, location of the infarct, stroke severity, vascular status and laboratory abnormalities were analyzed in order to build a regression model. RESULTS: On hundred thirty-one patients were recruited (M:F = 60:71, mean age 66 +/- 12 years) and an elevated BP was identified in 33 patients (25.2%). The mean systolic and diastolic BP did not differ significantly between the stroke subtypes, lesion locations, and hemispheric sides. According to univariate logistic regression, an elevated systolic BP correlated with headache (p = 0.01) and underlying hypertension (p = 0.02) while an elevated diastolic BP correlated with underlying hypertension (p = 0.01). Multivariate logistic regression analysis revealed previous hypertension (OR 5.21, 95% CI 1.40-19.37) and headache (OR 4.09, 95% CI 1.44-11.66) to be independent predictors of an elevated systolic BP. CONCLUSIONS: Headache itself is closely associated with severe systolic BP elevation in acute ischemic stroke. Whether treatment of elevated BP improves headache and clinical outcome is not yet known, necessitating future controlled studies.
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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 | 0.000 | 0.003 |
| 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".