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Record W4406993657 · doi:10.1161/str.56.suppl_1.wp135

Abstract WP135: Race-Ethnic Specific Hospital Arrival Time of Acute Ischemic Stroke by State in the U.S.

2025· article· en· W4406993657 on OpenAlexaff
Bing Yu Chen, Jie‐Lena Sun, Gregg C. Fonarow, Brooke Alhanti, Brian Mac Grory, Eric E. Smith, Lee H. Schwamm, Deepak L. Bhatt, Jeffrey L. Saver, Ying Xian, Ken Uchino, Shumei Man

Bibliographic record

VenueStroke · 2025
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineIschemic strokeRace (biology)Stroke (engine)Ethnic groupArrival timeAcute strokeEmergency medicineInternal medicineIschemiaTissue plasminogen activator

Abstract

fetched live from OpenAlex

Introduction: Arriving at the hospital after 4.5 hours of stroke onset makes a patient ineligible for intravenous thrombolytic therapy. In the U.S., pre-hospital triage is governed by each state. We aimed to understand hospital arrival times by state and race/ethnicity. Methods: This cross-sectional observational study included adult patients with acute ischemic stroke treated at the Get With The Guidelines-Stroke (GWTG-Stroke) participating hospitals from January 2021 to August 2023. The primary outcome was the proportion of patients with onset-to-arrival (OTA)>4.5 hours. Multivariable logistic regression models were adjusted for patient- and hospital-level potential confounding factors. Results: This study included 691,689 patients (66.2% White, 17.1% Black, 8.8% Hispanic, 3.4% Asian, and 4.4% other / undetermined), 49.8% with OTA >4.5 hours. OTA>4.5 hours occurred in 55% of Asian patients, 54% of Black patients, 52% of Hispanic patients, and 48% of White patients. Compared to White patients, Asian [adjusted odds ratio (aOR), 1.24; 95% CI 1.20-1.28], Black (aOR, 1.18; 95% CI 1.16-1.19), and Hispanic patients (aOR, 1.10; 95% CI 1.07-1.12) were more likely to present after 4.5 hours of stroke onset. The percentages of patients with OTA>4.5 hours in each race and ethnicity by state are depicted in the Figure. States with the highest percentages of OTA>4.5 hours were North Dakota for Asian patients (83%); and Vermont for Black (90%), Hispanic (100%), and White (55%) patients. After risk adjustment, compared to Texas which had the highest diversity index, states with the highest odds of OTA>4.5 hours in all patients were Vermont (1.31; 95% CI, 1.13-1.52), Mississippi (1.15; 95% CI, 1.04-1.28), North Carolina (1.15; 95% CI, 1.06-1.24) and Kentucky (1.15; 95% CI, 1.06-1.25). For the combined group of underrepresented Asian, Black, and Hispanic patients, the adjusted analysis showed that the highest odds of OTA>4.5 hours were in Vermont (5.68, 95% CI 4.30-7.51), District of Columbia (1.39, 95% CI 1.06-1.83), Utah (1.37, 95% CI 1.08-1.75) and Rhode Island (1.36, 95% CI 1.15-1.60) compared to Texas. Conclusions: Asian, Black, and Hispanic patients are more likely to arrive after 4.5 hours of stroke onset than White patients, with a state-specific pattern. Further studies and interventions of these states and culturally tailored interventions are warranted to improve arrival times and time-dependent stroke treatment.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.259
Teacher spread0.251 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2025
Admission routes1
Has abstractyes

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