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Related Experiment Videos

Risk classification after aneurysmal subarachnoid hemorrhage

T P Germanson1, G Lanzino, G L Kongable

  • 1Department of Neurosurgery, University of Virginia, Charlottesville 22908, USA.

Surgical Neurology
|February 11, 1998
PubMed
Summary

Level of consciousness (LOC) effectively predicts patient outcomes after aneurysmal subarachnoid hemorrhage (SAH). This simple clinical measure is as accurate as complex multivariate models for risk stratification.

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Area of Science:

  • Neurology
  • Neurosurgery
  • Critical Care Medicine

Background:

  • Predicting patient outcomes is crucial for managing aneurysmal subarachnoid hemorrhage (SAH).
  • Multivariate risk classification methods like CART and logistic regression are complex.
  • Level of consciousness (LOC) is a known single predictor of outcome.

Purpose of the Study:

  • To evaluate the prognostic value of Classification and Regression Trees (CART) and multiple logistic regression.
  • To compare these multivariate approaches with the level of consciousness (LOC) for predicting outcome in aneurysmal SAH.
  • To determine the most practical and accurate method for risk stratification.

Main Methods:

  • Utilized data from the NICSAH I study (n=885) to develop prediction models.

Related Experiment Videos

  • Employed CART and stepwise logistic regression, incorporating factors like LOC, age, aneurysm location, and glucose levels.
  • Compared multivariate models with LOC predictions in an independent dataset, NICSAH II (n=353).

    • Main Results:

    • All three classification systems demonstrated similar risk discrimination in the testing sample (NICSAH II).
    • Low-, medium-, and high-risk groups defined by LOC showed unfavorable outcome rates of 8%, 19%, and 52%, respectively.
    • These rates closely approximated those from the more complex multivariate systems.

    Conclusions:

    • Multivariate classification systems effectively characterize multiple risk factors' relationship to outcome.
    • Level of consciousness (LOC) offers a concise and practical approach for predicting unfavorable outcomes in aneurysmal SAH.
    • LOC is favored for its simplicity and clinical utility in risk stratification.