Evidence map›Paper›PMID 39575848›Full record

ArticleEuropean journal of neurology2025

Outcomes of cerebrovascular disease in muscular dystrophies: A propensity-matched nationwide analysis.

Ali Al-Salahat, Danielle B Dilsaver, Saif Bawaneh, Yu-Ting Chen

Abstract read
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Article in European journal of neurology, 2025. 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

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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.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Ali Al-SalahatNeurology Department, Creighton University, Omaha, Nebraska, USA.ORCID 0000-0003-4047-0835
Danielle B DilsaverDepartment of Clinical Research and Public Health, Creighton University, Omaha, Nebraska, USA.ORCID 0009-0004-9203-7552
Saif BawanehNeurology Department, Creighton University, Omaha, Nebraska, USA.
Yu-Ting ChenNeurology Department, Creighton University, Omaha, Nebraska, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

background and purposeThe literature lacks large studies on outcomes of cerebrovascular disease (CVD) in patients with muscular dystrophies (MDs). Previous studies primarily focused on ischemic stroke. CVD can add considerable morbidity in patients with MD. We aimed to study the outcomes of CVD in patients with MDs using a national database.

methodsData were abstracted from the 2010-2021 Nationwide Readmission Database. We identified hospitalizations for CVDs including ischemic stroke, intracerebral hemorrhage, subarachnoid hemorrhage, and other unspecified CVDs. We used propensity-score matching to account for selection bias and baseline differences between MD and non-MD patients in type of CVD, age, biological sex, time of discharge, and comorbidity burden. Outcomes were inpatient mortality, 30-day and 90-day readmissions, length of stay, costs and discharge disposition.

resultsThere were an estimated 6,129,132 CVD hospitalizations, of which 0.03% (weighted N = 2098) were for patients with MD. Ischemic stroke was the most common type, followed by intracerebral hemorrhage. MD was associated with 41% lower odds of a routine discharge, 9% greater costs, and 30% lower odds of 90-day all-cause readmissions. Inpatient mortality was higher in the MD cohort, but the difference was not statistically significant. There were no significant differences in other outcomes.

conclusionThe findings of this study provide new insights into the outcomes of CVD in MD patients, highlighting the need for enhanced access to post-discharge care in such patients. Improved post-discharge care may help reduce readmissions and avoid longer hospital stays. This study could be valuable for neurologists, rehabilitation physicians, healthcare administrators and economists.

Indexed as

Cerebrovascular DisordersMuscular DystrophiesPropensity ScoreAdolescentAdultAgedChildDatabases, FactualFemaleHumansLength of StayMaleMiddle AgedPatient ReadmissionUnited StatesYoung Adultcerebrovascular diseaseintracerebral hemorrhageischemic strokemuscular dystrophiesmuscular dystrophynationwide readmission databasestroke

Identifiers

PMID39575848
PMCPMC11625959

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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.