Midterm Blood Pressure Variability Is Associated with Poststroke Cognitive Impairment: A Prospective Cohort Study
Bibliographic record
Abstract
Objective The aim of this study was to investigate the relationship between blood pressure variability (BPV) and post stroke cognitive impairment (PSCI). Methods Seven-hundred and ninety-six patients with acute ischemic stroke were included in this study. Mid-term BPV was evaluated by calculating the standard deviation (SD) and coefficient of variation (CV, 100 × SD/mean) of systolic blood pressure (SBP) and diastolic blood pressure during the 7 days after stroke onset. Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA) at admission and at all follow-up visits. Patients with MoCA scores <26 were considered to have PSCI. Results The incidence of PSCI reached its peak (72%) 3 months after stroke onset and decreased to 30.3% at 12 months post-stroke. After adjusting for covariables, the increase in the prevalence of PSCI at 3 months was independently associated with increases in the coefficient of variation of blood pressure during the 7 days after stroke ( odds ratios and 95%CI for patients in the second to fifth quintiles of SBP CV were 2.28(1.18,4.39), 2.33(1.18,4.62), 2.69(1.31,5.53), 4.76(1.95,11.67), respectively ). Sub-analysis of the MoCA scores revealed that the patients had impairments in visuoperceptual abilities and executive functions, as well as in naming and delayed recall (p < 0.05). Conclusions Mid-term blood pressure variability during the early phase of acute ischemic stroke is independently associated with post-stroke cognitive impairment, especially in the visuoperceptual, executive, and delayed recall domains.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".