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Related Concept Videos

Hemorrhagic Stroke l: Introduction01:17

Hemorrhagic Stroke l: Introduction

34
A hemorrhagic stroke is an acute neurological event that occurs when a weakened cerebral blood vessel ruptures, allowing blood to accumulate within or around the brain. The sudden release of blood forms a focal hematoma that increases intracranial pressure, displaces neural tissue, and can obstruct cerebrospinal fluid pathways. These effects may be compounded by intraventricular extension of the hemorrhage, cerebral edema, or compression of adjacent structures, all of which contribute to...
34

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The Stroke Preclinical Assessment Network Multi-Laboratory Model of Thromboembolic Stroke with Thrombolysis: TE-MCAo
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One-year all-cause mortality after stroke: a prediction model.

Barbara E Bates1, Dawei Xie2, Pui L Kwong3

  • 1Veterans Affairs Medical Center, Albany, NY; Physical Medicine and Rehabilitation, Albany Medical College, VAMC (117), 113 Holland Avenue, Albany, NY 12208(∗).

PM & R : the Journal of Injury, Function, and Rehabilitation
|November 12, 2013
PubMed
Summary

A new stroke mortality index uses readily available data to predict 1-year survival for hospitalized veterans. This tool stratifies patients into risk groups, aiding post-discharge care planning.

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Area of Science:

  • Neurology
  • Public Health
  • Biostatistics

Background:

  • Acute stroke hospitalization presents a significant risk for 1-year all-cause mortality among veterans.
  • Effective risk stratification is crucial for optimizing post-discharge care and resource allocation.

Purpose of the Study:

  • To develop and internally validate a prediction index for 1-year all-cause mortality in patients hospitalized for acute stroke.
  • To utilize data from Department of Veterans Affairs (VA) national databases for index creation.

Main Methods:

  • An observational cohort study was conducted using VA national databases.
  • Data included 12,565 veterans discharged between October 1, 2006, and September 30, 2008, with a new stroke diagnosis.
  • A predictive model was developed using 17 risk factors identified at hospital discharge.

Main Results:

  • The final model identified 17 risk factors, including age, stroke type, comorbidities, and hospitalization details.
  • The 1-year mortality prediction index stratified patients into four risk strata (low to highest likelihood).
  • Mortality risk ranged from 2.24% (lowest quartile) to 29.50% (highest quartile) with good model discrimination (AUC 0.785-0.787).

Conclusions:

  • A simple, feasible index using readily available data can effectively stratify stroke patients by 1-year mortality risk.
  • This index can inform post-discharge planning and care management based on identified risk levels.