Intracerebral hemorrhage: external validation and extension of a model for prediction of 30-day survival

Ann Neurol. 1991 Jun;29(6):658-63. doi: 10.1002/ana.410290614.

Abstract

We report validation of a previously reported logistic regression model for predicting 30-day survival after supratentorial intracerebral hemorrhage using independent, prospectively collected data. The original model, using initial Glasgow Coma Scale score, hemorrhage size, and pulse pressure, accounted for mortality or survival at 30 days in 92% of patients in the Pilot Stroke Data Bank with a sensitivity of 0.84 and a specificity of 0.96. For external validation, the model was used to predict 30-day status for each patient in the Main Phase Stroke Data Bank for whom complete risk factor information was available. Overall, 90% of patients' outcomes were correctly predicted with a sensitivity of 0.85 and a specificity of 0.92. Two factors not collected in the Pilot Stroke Data Bank, hyperglycemia and intraventricular hemorrhage extension, were assessed to determine if they provided additional predictive information on 30-day mortality. Intraventricular hemorrhage extension contributed significant predictive information in a logistic regression, whereas hyperglycemia did not. The resulting four-factor model with an interaction term (intraventricular hemorrhage extension and Glasgow Coma Scale score) correctly classified the survival status of 94% of patients at 30 days. A more general outcome, death or failure to achieve a "good" Activities of Daily Living Score by one year, was analyzed with respect to the same four factors. The resulting model correctly classified 95% of the patients in the cohort.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Blood Glucose / analysis
  • Cerebral Hemorrhage / mortality*
  • Cerebral Hemorrhage / pathology
  • Cohort Studies
  • Glasgow Coma Scale
  • Hemodynamics
  • Humans
  • Logistic Models
  • Models, Biological
  • Odds Ratio
  • Predictive Value of Tests
  • Risk Factors
  • Survival Analysis

Substances

  • Blood Glucose