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Delayed Hospital Arrival for Acute Stroke: The Minnesota Stroke Survey

Maureen A. Smith, MD; Katherine M. Doliszny, PhD; Eyal Shahar, MD; Paul G. McGovern, PhD; Donna K. Arnett, PhD; and Russell V. Luepker, MD
[+] Article and Author Information

For author affiliations and current author addresses, see end of text. Grant Support: By the National Heart, Lung, and Blood Institute (RO1-HL-23727). Acknowledgments: The authors thank Mary Porter, Sherri Nooyen, Aaron Timbo, and the dedicated nurse-abstracters who contributed to this research. They also thank the hospitals in Minneapolis-St. Paul for their commitment to this project for more than a decade. Requests for Reprints: Russell V. Luepker, MD, Division of Epidemiology, School of Public Health, University of Minnesota, 1300 South Second Street, Suite 300, Minneapolis, MN 55454-1015. Current Author Addresses: Dr. Smith: Division of Health Management and Policy, School of Public Health, University of Minnesota, 420 Delaware Street SE, Box 97 Mayo D355, Minneapolis, MN 55455-0381.


Copyright ©2004 by the American College of Physicians


Ann Intern Med. 1998;129(3):190-196. doi:10.7326/0003-4819-129-3-199808010-00005
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Background: Although recent advances have been made in the treatment of acute stroke, patients often arrive at the hospital too late to receive the maximum benefit from these new therapies.

Objective: To investigate characteristics that influence the time from symptom onset to hospital arrival (delay time) for patients with acute stroke.

Design: Retrospective medical record review.

Setting: Minneapolis-St. Paul metropolitan hospitals.

Patients: A 50% random sample of all patients 30 to 79 years of age who were hospitalized with acute stroke from 1991 to 1993.

Measurements: Patients were identified through discharge diagnosis lists by using the International Classification of Diseases, 9th Revision. Trained nurses abstracted the medical records. Stroke events were validated by using neuroimaging reports and additional clinical criteria (1895 patients). An accelerated failure time model was used to identify patient characteristics that independently predicted delay time. For 70% of patients (n = 1334), delay time was calculated from the medical record by subtracting the recorded time of symptom onset from the admission time. For the remaining 30% of patients (n = 561), the time of symptom onset was not recorded, and an approximate delay time was estimated from all available information.

Results: Among patients with a calculated delay time, half arrived within 3 hours of symptom onset and 90% arrived within 24 hours. Patients with approximated delay times tended to have longer delays, and less than 40% of these patients arrived within 24 hours of symptom onset. Some characteristics associated (P < 0.05) with longer delay included Asian/Pacific Islander ethnicity, dependence in any activities of daily living before stroke, and several symptoms at stroke onset. Characteristics associated (P < 0.05) with shorter delay included admission through the emergency department, presence of syncope or seizures at stroke onset, previous myocardial infarction, abnormal mental status, and greater disability at presentation (measured by the Rankin scale).

Conclusions: Most patients arrive at the hospital too late to receive the maximum benefit from emerging stroke therapies. Efforts to reduce delays in hospital arrival after acute stroke can maximize the effectiveness of these therapies by specifically targeting persons at risk for longer delay.

Figures

Grahic Jump Location
Figure 1.
Frequency distribution of delay time for patients hospitalized for acute stroke, with calculated delay times (n = 1334) and approximated delay times (n = 561).
Grahic Jump Location
Grahic Jump Location
Figure 2.
Frequency distribution of delay time for hospitalized patients with acute stroke and calculated delay times only (n = 1334).
Grahic Jump Location

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