Evidence map›Paper›PMID 40794699›Full record

ArticlePloS one2025

Clinical outcomes in patients with muscle disorders and acute ischemic stroke.

Adeel S Zubair, Lauren Littig, Daniel B DiCapua, Adam de Havenon

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Adeel S ZubairDepartment of Neurology, Yale University School of Medicine, New Haven, Connecticut.
Lauren LittigDepartment of Neurology, Yale University School of Medicine, New Haven, Connecticut.ORCID https://orcid.org/0009-0005-7389-0328
Daniel B DiCapuaDepartment of Neurology, Yale University School of Medicine, New Haven, Connecticut.
Adam de HavenonDepartment of Neurology, Yale University School of Medicine, New Haven, Connecticut.ORCID https://orcid.org/0000-0001-8178-8597

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesStroke is a leading cause of morbidity in the United States, which prompts an exploration into its associated risk factors. Muscle disorders have been linked to an increased risk of stroke; however, research on stroke prevalence and clinical outcomes in this population is limited by small sample sizes. Although the diagnostic and treatment protocols for acute ischemic stroke are largely identical in patients with and without muscle disorders, it remains unclear whether clinical outcomes differ. This study aimed to address this gap using a large, nationally representative dataset. MATERIALS AND

methodsWe conducted a retrospective analysis of the 2016-2022 National Inpatient Sample to compare clinical outcomes in patients with and without muscle disorders hospitalized for an acute ischemic stroke.

resultsPatients with pre-existing muscle disorders had significantly higher rates of intubation, PEG tube placement, and in-hospital mortality, as well as a lower likelihood of discharge to home, compared to those without muscle disorders.

conclusionsThese findings suggest that patients with muscle disorders experience worse outcomes following an ischemic stroke. Further research is needed to identify the underlying factors driving these disparities and to inform targeted strategies for improving outcomes in this vulnerable population.

Indexed as

Ischemic StrokeMuscular DiseasesAgedAged, 80 and overFemaleHospital MortalityHumansMaleMiddle AgedRetrospective StudiesRisk FactorsUnited States

Identifiers

PMID40794699
PMCPMC12342303

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.