Evidence map›Paper›PMID 38759133›Full record

ArticleNeurology2024

Prediction of Large Vessel Occlusion Stroke Using Clinical Registries for Research.

Adam de Havenon, Iyanuoluwa Ayodele, Brooke Alhanti, Brian Mac Grory, Ying Xian, Gregg Fonarow, Eric E Smith, Bradford B Worrall

Abstract read
In one paragraph

Article in Neurology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 3 pooled it
–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

8 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. 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

8 authors.

Adam de HavenonFrom the Yale University (A.H.), New Haven, CT; Duke Clinical Research Institute (I.A., B.A.), Durham; Duke University (B.M.G.), Durham, NC; UT-Southwestern Medical Center (Y.X.), Dallas, TX; University of California Los Angeles (G.F.); University of Calgary (E.E.S.), Canada; University of Virginia (B.B.W.), Charlottesville, VA.ORCID 0000-0001-8178-8597
Iyanuoluwa AyodeleFrom the Yale University (A.H.), New Haven, CT; Duke Clinical Research Institute (I.A., B.A.), Durham; Duke University (B.M.G.), Durham, NC; UT-Southwestern Medical Center (Y.X.), Dallas, TX; University of California Los Angeles (G.F.); University of Calgary (E.E.S.), Canada; University of Virginia (B.B.W.), Charlottesville, VA.ORCID 0000-0003-4480-1697
Brooke AlhantiFrom the Yale University (A.H.), New Haven, CT; Duke Clinical Research Institute (I.A., B.A.), Durham; Duke University (B.M.G.), Durham, NC; UT-Southwestern Medical Center (Y.X.), Dallas, TX; University of California Los Angeles (G.F.); University of Calgary (E.E.S.), Canada; University of Virginia (B.B.W.), Charlottesville, VA.
Brian Mac GroryFrom the Yale University (A.H.), New Haven, CT; Duke Clinical Research Institute (I.A., B.A.), Durham; Duke University (B.M.G.), Durham, NC; UT-Southwestern Medical Center (Y.X.), Dallas, TX; University of California Los Angeles (G.F.); University of Calgary (E.E.S.), Canada; University of Virginia (B.B.W.), Charlottesville, VA.
Ying XianFrom the Yale University (A.H.), New Haven, CT; Duke Clinical Research Institute (I.A., B.A.), Durham; Duke University (B.M.G.), Durham, NC; UT-Southwestern Medical Center (Y.X.), Dallas, TX; University of California Los Angeles (G.F.); University of Calgary (E.E.S.), Canada; University of Virginia (B.B.W.), Charlottesville, VA.ORCID 0000-0002-1237-1162
Gregg FonarowFrom the Yale University (A.H.), New Haven, CT; Duke Clinical Research Institute (I.A., B.A.), Durham; Duke University (B.M.G.), Durham, NC; UT-Southwestern Medical Center (Y.X.), Dallas, TX; University of California Los Angeles (G.F.); University of Calgary (E.E.S.), Canada; University of Virginia (B.B.W.), Charlottesville, VA.
Eric E SmithFrom the Yale University (A.H.), New Haven, CT; Duke Clinical Research Institute (I.A., B.A.), Durham; Duke University (B.M.G.), Durham, NC; UT-Southwestern Medical Center (Y.X.), Dallas, TX; University of California Los Angeles (G.F.); University of Calgary (E.E.S.), Canada; University of Virginia (B.B.W.), Charlottesville, VA.ORCID 0000-0003-3956-1668
Bradford B WorrallFrom the Yale University (A.H.), New Haven, CT; Duke Clinical Research Institute (I.A., B.A.), Durham; Duke University (B.M.G.), Durham, NC; UT-Southwestern Medical Center (Y.X.), Dallas, TX; University of California Los Angeles (G.F.); University of Calgary (E.E.S.), Canada; University of Virginia (B.B.W.), Charlottesville, VA.ORCID 0000-0001-9386-4091

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Cardioembolism as a Mechanism of Central Retinal Artery OcclusionK23HL161426 · NHLBI · DUKE UNIVERSITY · PI Brian Mac Grory · 2022 to 2026
$951k
NCATS NIH HHS UL1 TR001863NHLBI NIH HHS K23 HL161426
6 · The paper itself

Abstract

objectivesA reliable method of predicting large vessel occlusion (LVO) stroke in data sets without neuroimaging could be retrospectively applied to expand research efforts.

methodsWe conducted a retrospective, cross-sectional cohort analysis of the Get With The Guidelines (GWTG)-Stroke registry. We included adult patients with a final diagnosis of ischemic stroke from 2016 to 2021 who had brain and vascular imaging and excluded those with missing data or posterior circulation stroke.

resultsWe included 416,022 patients of which 125,381 (30.1%) had LVO. The mean age was 71 years, and 48.2% were female. The area under the receiver operating curve (AUC) for the final model, including age, sex, hypertension, dyslipidemia, atrial fibrillation, diabetes, TOAST stroke mechanism, and NIH Stroke Scale (NIHSS), was 0.79 (95% CI 0.79-0.80). Without TOAST mechanism, the AUC was 0.74. The specificity did not exceed 0.5 using different cut points for the NIHSS. DISCUSSION: We found that 30% of adult acute ischemic stroke patients in GWTG-Stroke have LVO and that the combination of clinical covariates and NIHSS is only moderately predictive of LVO status. These results are consistent with previous studies and suggest it may not be possible to retrospectively predict LVO with high accuracy in data sets without vascular neuroimaging.

Indexed as

Ischemic StrokeRegistriesAgedAged, 80 and overCohort StudiesCross-Sectional StudiesFemaleHumansMaleMiddle AgedRetrospective StudiesStroke

Identifiers

PMID38759133
PMCPMC11175650

What OpenQuestion holds

Textmetadata
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.