20. Effect of Successive Systolic Blood Pressure Variability Following Intravenous Thrombolysis in Acute Ischemic Stroke – A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: Previous studies have shown contradictory findings regarding the effects of systolic blood pressure variability (SBPV) after intravenous thrombolysis (IVT) on functional outcomes and risk of intracranial hemorrhage (ICH) in acute ischemic stroke (AIS). Objective: The purpose of this systematic review and meta-analysis was to ascertain how SBPV indices, successive variance of SBPV (SPBVsv), following IVT affected the outcome in AIS. Method: We searched for articles published before October 2022 in the following databases: PubMed, Scopus, ScienceDirect, and ProQuest. The pooled multivariate odds ratios (ORs) and 95% confidence intervals (CIs) were obtained using Jeffrey's Amazing Statistics Program (JASP). The outcomes included favorable functional result using modified Rankin Scale (mRS) score less than 2 within 90 days and intracranial hemorrhage event within 36 hours after IVT. The Newcastle Ottawa Scale (NOS) was used to rate the reliability of the studies. Result: Initial search revealed 2089 studies, of which 8 studies including 31791 patients with AIS and underwent IVT met the inclusion criteria. Increased of SBPVsv following IVT was substantially related with a poorer functional result in AIS (OR = 2.72, 95% CI 1.38 to 5.36, I2 = 93.8%, p value of Q test 0.004) and increase risk of ICH (OR = 1.46, 95% CI 1.01 to 2.12, I2 = 73.6%, p value of Q test 0.043) Conclusion: Successive systolic blood pressure variability has a negative relationship with 90-days outcome in AIS patients who received IVT while the risk of ICH within 36 hours after IVT is increase.
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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 | 0.020 | 0.044 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.054 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".