Abstract HUP7: Significant Difference in Stroke Knowledge by Race: Evidence from the Time is Brain Observational Study

Introduction: Stroke education is a key determinant of timely hospital arrival. While considerable evidence indicates that Black patients experience greater prehospital delay, few studies have investigated whether these gaps extend to stroke knowledge. Methods: Time is Brain is a multicenter, prospective, observational study investigating social, psychological, and demographic determinants of prehospital delay. Demographics, clinical characteristics, and stroke knowledge were collected from patients with acute stroke syndrome presenting to two tertiary care centers in the Northeast. Stroke knowledge was assessed through a validated 19-item stroke knowledge test. A Mann-Whitney U test was performed to compare stroke knowledge scores between Black and White participants of any ethnicity. Rank-based median regression was then used to evaluate the association between race and stroke knowledge while adjusting for sex, age, education level, cognitive status, socioeconomic status (SES), NIH Stroke Scale (NIHSS) and healthcare distrust. Results: A total of 321 patients with acute stroke syndrome were enrolled between January 2023 and July 2025 (mean age = 66.30, SD = 15.64, 43.9% Female, median NIHSS = 2). A total of 60 participants (19%) self-identified as Black and 240 as White (75%). All other racial groups were underpowered for statistical analysis (n<5). Stroke knowledge was non-normal (Shapiro-Wilk p <0.001, skewness=-0.85, kurtosis=0.53). In the unadjusted analysis, Black participants had significantly lower stroke knowledge scores than White participants (median [IQR] 8.5 [6.25-11.0] vs. 11.0 [9.0-13.0], p <0.001). In the adjusted median regression model, Black race was significantly associated with lower stroke knowledge scores (β = -2.35, 95% CI [-3.60, -1.10], p =0.002), independent of sex, age, education level, cognitive status, SES, NIHSS and healthcare distrust. In this model, fewer years of education completed (β = 0.24 [0.07,0.41], p <0.01) and lower cognitive status scores (β = -0.11 [-0.20,-0.02], p =0.020) were also associated with lower stroke knowledge. Conclusion: In this multicenter cohort, Black participants had significantly lower stroke knowledge than White participants, a difference that remained significant when adjusting for demographic, educational, and clinical factors. This difference warrants further investigation into the underlying causes and potential interventions to improve stroke knowledge in Black patients.

Authors

Institutions

Publication Details

Journal
Stroke
Published
2026-01-29
DOI
https://doi.org/10.1161/str.57.suppl_1.hup7
Primary Topic
Acute Ischemic Stroke Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract HUP7: Significant Difference in Stroke Knowledge by Race: Evidence from the Time is Brain Observational Study

Vrushali Dhongade, George Usmanov, Ian Johnson, Alison Champagne et al.
Stroke
Acute Ischemic Stroke Management
article

Abstract HUP7: Significant Difference in Stroke Knowledge by Race: Evidence from the Time is Brain Observational Study

Vrushali Dhongade, George Usmanov, Ian Johnson, Alison Champagne, Brandon D. L. Marshall, Hailey Brigger, Emma Peasley, Nana Bediako, Amar Dhand, Zach Rothfeld-Wehrwein, Annabelle Shanks, Eliana Williamson, Steph Maynez, Kevin Sheth
article en

Abstract

Introduction: Stroke education is a key determinant of timely hospital arrival. While considerable evidence indicates that Black patients experience greater prehospital delay, few studies have investigated whether these gaps extend to stroke knowledge. Methods: Time is Brain is a multicenter, prospective, observational study investigating social, psychological, and demographic determinants of prehospital delay. Demographics, clinical characteristics, and stroke knowledge were collected from patients with acute stroke syndrome presenting to two tertiary care centers in the Northeast. Stroke knowledge was assessed through a validated 19-item stroke knowledge test. A Mann-Whitney U test was performed to compare stroke knowledge scores between Black and White participants of any ethnicity. Rank-based median regression was then used to evaluate the association between race and stroke knowledge while adjusting for sex, age, education level, cognitive status, socioeconomic status (SES), NIH Stroke Scale (NIHSS) and healthcare distrust. Results: A total of 321 patients with acute stroke syndrome were enrolled between January 2023 and July 2025 (mean age = 66.30, SD = 15.64, 43.9% Female, median NIHSS = 2). A total of 60 participants (19%) self-identified as Black and 240 as White (75%). All other racial groups were underpowered for statistical analysis (n<5). Stroke knowledge was non-normal (Shapiro-Wilk p <0.001, skewness=-0.85, kurtosis=0.53). In the unadjusted analysis, Black participants had significantly lower stroke knowledge scores than White participants (median [IQR] 8.5 [6.25-11.0] vs. 11.0 [9.0-13.0], p <0.001). In the adjusted median regression model, Black race was significantly associated with lower stroke knowledge scores (β = -2.35, 95% CI [-3.60, -1.10], p =0.002), independent of sex, age, education level, cognitive status, SES, NIHSS and healthcare distrust. In this model, fewer years of education completed (β = 0.24 [0.07,0.41], p <0.01) and lower cognitive status scores (β = -0.11 [-0.20,-0.02], p =0.020) were also associated with lower stroke knowledge. Conclusion: In this multicenter cohort, Black participants had significantly lower stroke knowledge than White participants, a difference that remained significant when adjusting for demographic, educational, and clinical factors. This difference warrants further investigation into the underlying causes and potential interventions to improve stroke knowledge in Black patients.

StrokeVol. 57(Suppl_1)
Brigham and Women's Hospital (US), Brown University (US), Yale University (US)
Quality Education
Openalex Percentile: Top 72%
Acute Ischemic Stroke Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.