Evidence map›Paper›PMID 39461451›Full record

ArticleJournal of stroke and cerebrovascular diseases : the official journal of National Stroke Association2024

Navigating stroke care: Geospatial assessment of regional stroke center accessibility: Geospatial Assessment of Stroke Centers.

Stephen Halada, Kirsten Mm Beyer, Yuhong Zhou, Benjamin W Weston

Abstract read
In one paragraph

Article in Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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.

Stephen HaladaMedical Student, Medical College of Wisconsin, Milwaukee, WI, 53226, USA. Electronic address: shalada@mcw.edu.
Kirsten Mm BeyerInstitute for Health & Equity, Medical College Wisconsin, 8701 W Watertown Plank Rd, Milwaukee, WI, 53226, USA. Electronic address: kbeyer@mcw.edu.
Yuhong ZhouInstitute for Health & Equity, Medical College Wisconsin, 8701 W Watertown Plank Rd, Milwaukee, WI, 53226, USA. Electronic address: yuzhou@mcw.edu.
Benjamin W WestonDepartment of Emergency Medicine, Medical College Wisconsin, 8701 W Watertown Plank Rd, Milwaukee, WI, 53226, USA. Electronic address: beweston@mcw.edu.

Funding

Medical Student Summer Research Training ProgramT35HL072483 · NHLBI · MEDICAL COLLEGE OF WISCONSIN · PI RAMCHANDRAN, RAMANI · 2003 to 2025
$3.0M
NHLBI NIH HHS T35 HL072483
6 · The paper itself

Abstract

introductionReducing time between stroke onset and hospital intervention is crucial for positive outcomes in stroke patients. While EMS utilization decreases time to intervention, many US regions are not within timely proximity to an advanced-care-capable stroke center (ASC), defined as a comprehensive or thrombectomy-capable center. This study aims to utilize geographic methodology to identify regions in Wisconsin with both high stroke mortality and low physical accessibility to certified stroke centers (SCs), particularly ASCs.

methodsGeocoded mortality records for stroke death between 2015 and 2020 were accessed from the Wisconsin Department of Health Services. Indirectly age-standardized mortality ratios (SMRs) were estimated continuously across Wisconsin using adaptive spatial filtering and mortality records at the census block group level; the surface was then averaged by census tract for tract level SMRs. Addresses for SC locations within Wisconsin and bordering states were collected, and drive times from Wisconsin census tract centroids to the nearest SC subtypes were estimated. Drive times and mortality ratios were evaluated at the tract level alongside Rural-Urban Commuting Area (RUCA) codes. Spatial error regression modeling was used to determine RUCA classifications with the highest stroke risk independent of accessibility to stroke centers.

resultsApproximately 50%, 68%, and 78% of Wisconsin residents resided within 30, 45, and 60 minutes of an ASC, respectively. Median drive time from census tract centroids to the nearest ASC were highest for rural tracts (M=90 minutes, IQR=68-115) compared to small-town (M=82 minutes, IQR=49-113), micropolitan (M=53 minutes, IQR=43-77), and metropolitan tracts (M=19 minutes, IQR=11-35; p<0.001). Clusters of high stroke SMRs were found in urban centers as well as rural areas irrespective of county declinations. Spatial regression modeling suggested small-town census tracts had the highest SMR irrespective of physical accessibility to care and spatial correlation. In small-town census tracts >45 minutes from the nearest ASC, the median stroke SMR was 1.12 (IQR=0.94-1.40) with 226,000 residents and 150 stroke deaths per year.

conclusionSmall-town areas are associated with both long drive distance to ASC locations and high stroke mortality. Geographical analyses reveal apparent stroke care deserts and may inform strategic allocation of emergency medicine resources and coverage.

Indexed as

Health Services AccessibilityStrokeTime-to-TreatmentAgedFemaleHealthcare DisparitiesHumansMaleRisk FactorsRural Health ServicesThrombectomyTime FactorsUrban HealthUrban Health ServicesWisconsinAccessibilityCardiovascular/strokeGeospatial analysisPublic health

Identifiers

PMID39461451
PMCPMC11570335

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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.