MétaCan
Menu
Back to cohort
Record W4397010895 · doi:10.31083/j.rcm2505174

Association between Blood Pressure and Post-Stroke Cognitive Impairment: A Meta-Analysis

2024· review· en· W4397010895 on OpenAlexaboutno aff
Huifen Huang, Yanli Zhan, Linling Yu, Shan Li, Xueli Cai

Bibliographic record

VenueReviews in Cardiovascular Medicine · 2024
Typereview
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMeta-analysisConfidence intervalStroke (engine)Internal medicineBlood pressureOdds ratioCochrane LibrarySubgroup analysisObservational study

Abstract

fetched live from OpenAlex

Background: Post-stroke cognitive impairment (PSCI) represents a serious post-stroke complication with poor cognitive consequences. A vascular consequence after a stroke is that the occurrence and progression of PSCI may be closely related to blood pressure (BP). Thus, we systematically reviewed and performed a meta-analysis of the literature to examine the correlations between BP and PSCI. Methods: We systematically queried databases, including PubMed, the Cochrane Library, Embase, and Scopus, and conducted meta-analyses on studies reporting odds ratios (ORs) related to the association between BP and PSCI. Two authors autonomously assessed all titles, abstracts, and full texts and extracted data following the Meta-Analysis of Observational Studies in Epidemiology guidelines. The quality of the studies was evaluated using the modified Newcastle–Ottawa scale. Results: Meta-analyses incorporated 12 articles comprising a cumulative participant cohort of 21,732 individuals. The quality assessment indicated good in five studies, fair in one study, and poor in six. Through meta-analyses, we found that hypertension, systolic or diastolic BP (SBP or DBP) was significantly associated with PSCI (OR 1.53, 95% confidence interval (CI), 1.18–1.99; p = 0.001, I2 = 66%; OR 1.13, 95% CI, 1.05–1.23; p = 0.002, I2 = 52%; OR 1.38, 95% CI, 1.11–1.72; p = 0.004, I2 = 90%, respectively). In the subgroup analysis, SBP <120 mmHg, 120–139 mmHg, 140–159 mmHg, 160–179 mmHg, and DBP ≥100 mmHg highly predicted the occurrence of PSCI (OR 1.15, p = 0.0003; OR 1.26, p = 0.010; OR 1.15, p = 0.05; OR 1.02, p = 0.009; OR 1.96, p < 0.00001, respectively). However, the predictive effect of BP for PSCI declines when SBP ≥180 mmHg and DBP ≤99 mmHg (p > 0.05). Statistical heterogeneity was moderate to high, and publication bias was detected in SBP for PSCI. Conclusions: Considering the multifactorial etiology of PSCI, it is difficult to conclude that BP is an independent risk factor for PSCI. Given the restricted inclusion of studies, caution is advised when interpreting the findings from this meta-analysis. Subsequent investigations with substantial sample sizes are essential to exploring BP as a prospective target for addressing PSCI. Trial Registration Number: CRD42023437783 from PROSPERO.

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 imitation

Not 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.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.027
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0190.069
Bibliometrics0.0070.007
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.065
GPT teacher head0.347
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations3
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueReviews in Cardiovascular MedicineSame topicAcute Ischemic Stroke ManagementFrench-language works237,207