Evidence map›Paper›PMID 38533986›Full record

ArticleJournal of the American Heart Association2024

Baseline Uric Acid Levels and Intravenous Thrombolysis Outcomes in Patients With Acute Ischemic Stroke: A Prospective Cohort Study.

Peng Zhang, Rui Wang, Zhen-Ni Guo, Hang Jin, Yang Qu, Qing Zhen, Yi Yang

Abstract read
In one paragraph

Article in Journal of the American Heart Association, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Peng ZhangDepartment of Epidemiology and Biostatistics, School of Public Health Jilin University Changchun China.ORCID 0000-0001-5536-0255
Rui WangDepartment of Epidemiology and Biostatistics, School of Public Health Jilin University Changchun China.
Zhen-Ni GuoDepartment of Epidemiology and Biostatistics, School of Public Health Jilin University Changchun China.ORCID 0000-0002-8922-3862
Hang JinDepartment of Epidemiology and Biostatistics, School of Public Health Jilin University Changchun China.
Yang QuDepartment of Epidemiology and Biostatistics, School of Public Health Jilin University Changchun China.ORCID 0000-0001-8598-3517
Qing ZhenDepartment of Thoracic Surgery the First Hospital of Jilin University Changchun China.ORCID 0000-0002-2816-4539
Yi YangDepartment of Epidemiology and Biostatistics, School of Public Health Jilin University Changchun China.ORCID 0000-0002-9729-8522

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe study aimed to investigate the relationship between uric acid (UA) levels and functional outcomes at 3 months in patients with acute ischemic stroke (AIS) who underwent intravenous thrombolysis (IVT). METHODS AND

resultsThis prospective cohort study included 1001 consecutive patients with AIS who underwent IVT. The correlation between UA levels and post-IVT AIS outcomes was examined. Any nonlinear relationship was assessed using a restricted cubic spline function. The nonlinear

conclusionsAn inverted U-shaped nonlinear relationship was observed between UA levels and favorable and excellent outcomes at 3 months in patients with AIS who underwent IVT. Higher UA levels predict favorable outcomes in patients without hyperuricemia but unfavorable outcomes in those with hyperuricemia.

Indexed as

Brain IschemiaHyperuricemiaIschemic StrokeStrokeFibrinolytic AgentsHumansProspective StudiesThrombolytic TherapyTreatment OutcomeUric AcidFibrinolytic AgentsUric Acidacute ischemic strokeintravenous thrombolysisoutcomeuric acid

Identifiers

PMID38533986
PMCPMC11179752

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.