Evidence map›Paper›PMID 26386884›Full record

ArticleAnnals of emergency medicine2016

Neighborhood Influences on Emergency Medical Services Use for Acute Stroke: A Population-Based Cross-sectional Study.

William J Meurer, Deborah A Levine, Kevin A Kerber, Darin B Zahuranec, James Burke, Jonggyu Baek, Brisa Sánchez, Melinda A Smith, Lewis B Morgenstern, Lynda D Lisabeth

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Annals of emergency medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact, top 90% of its field
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

8 citing papers in PubMed, 18 citations in OpenAlex.

  1. Article
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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

10 authors at 1 institution in 1 country.

William J MeurerDepartment of Emergency Medicine, University of Michigan, Ann Arbor, MI; Department of Neurology, University of Michigan, Ann Arbor, MI; Michigan Center for Integrative Research in Critical Care, University of Michigan, Ann Arbor, MI; Institute of Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI; Stroke Program, University of Michigan, Ann Arbor, MI.
Deborah A LevineInstitute of Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI; Stroke Program, University of Michigan, Ann Arbor, MI; Department of Internal Medicine, University of Michigan, Ann Arbor, MI.
Kevin A KerberDepartment of Neurology, University of Michigan, Ann Arbor, MI; Institute of Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI.
Darin B ZahuranecDepartment of Neurology, University of Michigan, Ann Arbor, MI; Institute of Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI; Stroke Program, University of Michigan, Ann Arbor, MI.
James BurkeDepartment of Neurology, University of Michigan, Ann Arbor, MI; Institute of Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI; Stroke Program, University of Michigan, Ann Arbor, MI.
Jonggyu BaekDepartment of Biostatistics, University of Michigan, Ann Arbor, MI.
Brisa SánchezInstitute of Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI; Stroke Program, University of Michigan, Ann Arbor, MI; Department of Biostatistics, University of Michigan, Ann Arbor, MI.
Melinda A SmithDepartment of Neurology, University of Michigan, Ann Arbor, MI.
Lewis B MorgensternDepartment of Emergency Medicine, University of Michigan, Ann Arbor, MI; Department of Neurology, University of Michigan, Ann Arbor, MI; Institute of Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI; Stroke Program, University of Michigan, Ann Arbor, MI; Department of Epidemiology, University of Michigan, Ann Arbor, MI.
Lynda D LisabethDepartment of Neurology, University of Michigan, Ann Arbor, MI; Institute of Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI; Stroke Program, University of Michigan, Ann Arbor, MI; Department of Epidemiology, University of Michigan, Ann Arbor, MI. Electronic address: llisabet@umich.edu.
University of Michigan–Ann Arbor · US

Funding

STROKE SURVEILLANCE IN A BIETHNIC COMMUNITYR01NS038916 · NINDS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI LISABETH, LYNDA D, MORGENSTERN, LEWIS B · 1999 to 2023
$20.9M
NINDS NIH HHS R01 NS038916
6 · The paper itself

Abstract

STUDY

objectiveDelay to hospital arrival limits acute stroke treatment. Use of emergency medical services (EMS) is key in ensuring timely stroke care. We aim to identify neighborhoods with low EMS use and to evaluate whether neighborhood-level factors are associated with EMS use.

methodsWe conducted a secondary analysis of data from the Brain Attack Surveillance in Corpus Christi project, a population-based stroke surveillance study of ischemic stroke and intracerebral hemorrhage cases presenting to emergency departments in Nueces County, TX. The primary outcome was arrival by EMS. The primary exposures were neighborhood resident age, poverty, and violent crime. We estimated the association of neighborhood-level factors with EMS use, using hierarchic logistic regression, controlling for individual factors (stroke severity, ethnicity, and age).

resultsDuring 2000 to 2009 there were 4,004 identified strokes, with EMS use data available for 3,474. Nearly half (49%) of stroke cases arrived by EMS. Adjusted stroke EMS use was lower in neighborhoods with higher family income (odds ratio [OR] 0.86; 95% confidence interval [CI] 0.75 to 0.97) and a larger percentage of older adults (OR 0.70; 95% CI 0.56 to 0.89). Individual factors associated with stroke EMS use included white race (OR 1.41; 95% CI 1.13 to 1.76) and older age (OR 1.36 per 10-year age increment; 95% CI 1.27 to 1.46). The proportion of neighborhood stroke cases arriving by EMS ranged from 17% to 71%. The fully adjusted model explained only 0.3% (95% CI 0% to 1.1%) of neighborhood EMS stroke use variance, indicating that individual factors are more strongly associated with stroke EMS use than neighborhood factors.

conclusionAlthough some neighborhood-level factors were associated with EMS use, patient-level factors explained nearly all variability in stroke EMS use. In this community, strategies to increase EMS use should target individuals rather than specific neighborhoods.

Indexed as

Residence CharacteristicsAgedAge FactorsBayes TheoremCrimeCross-Sectional StudiesEmergency Medical ServicesFemaleHumansMalePovertyRisk FactorsStrokeTexas

Identifiers

PMID26386884
PMCPMC4769663
OpenAlexW2191446112

What OpenQuestion holds

Textmetadata
LicenceTDM
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.