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Related Experiment Video

Updated: May 22, 2026

A Preclinical Model to Assess Brain Recovery After Acute Stroke in Rats
10:15

A Preclinical Model to Assess Brain Recovery After Acute Stroke in Rats

Published on: November 6, 2019

Towards a predictive model for post-stroke delirium.

Milena Kostalova1, Josef Bednarik, Adela Mitasova

  • 1Department of Neurology, University Hospital and Masaryk University, Brno, Czech Republic.

Brain Injury
|May 11, 2012
PubMed
Summary

This study identified key risk factors for post-stroke delirium, including advanced age, intracerebral hemorrhage, and larger stroke volumes. A predictive model was developed to identify patients at higher risk for delirium.

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Area of Science:

  • Neurology
  • Geriatrics
  • Critical Care Medicine

Background:

  • Post-stroke delirium is a common complication associated with poor outcomes.
  • Identifying risk factors is crucial for prevention and management.

Purpose of the Study:

  • To identify predisposing and precipitating risk factors for post-stroke delirium.
  • To develop a predictive model for post-stroke delirium.

Main Methods:

  • Prospective observational study of 100 patients with ischemic stroke or intracerebral hemorrhage.
  • Daily delirium assessment using DSM-IV criteria during the first week post-admission.
  • Multivariate logistic regression analysis to identify independent risk factors.

Main Results:

Related Experiment Videos

Last Updated: May 22, 2026

A Preclinical Model to Assess Brain Recovery After Acute Stroke in Rats
10:15

A Preclinical Model to Assess Brain Recovery After Acute Stroke in Rats

Published on: November 6, 2019

  • Delirium occurred in 43% of patients.
  • Independent predictors included advanced age, intracerebral hemorrhage, lesion volume > 40 ccm, elevated liver enzymes (gamma-glutamyl transferase, bilirubin), or high Sequential Organ Failure Assessment (SOFA) score (>2).
  • Total anterior circulation infarctions were significantly associated with delirium (OR = 6.66).

Conclusions:

  • Higher age, metabolic disturbances, intracerebral hemorrhage, and larger ischemic hemispheric strokes are significant risk factors for post-stroke delirium.
  • The developed predictive model demonstrated acceptable sensitivity (69.0%) and specificity (80.7%).