Objective: To develop a model for predicting outcome in the first few hours after the onset of an ischemic stroke on the basis of the clinical findings obtained during a rapid bedside examination.
Design: Clinical records were retrieved from the data bank of a randomized multicenter trial. The resulting case series was split into two subgroups that served as a "training set" and a "test set." Logistic regression was applied to the training set to select the prognostic predictors among baseline clinical findings. The performances of the model based on independent prognostic predictors were then validated in the test set.
Setting: Eleven primary care institutions (either hospitals or university clinics) participating in the Italian Acute Stroke Study on the efficacy of hemodilution and monosialoganglioside in acute ischemic stroke.
Patients: Consecutive noncomatose patients (N = 300) observed within the first 6 hours after the onset of a first supratentorial ischemic stroke.
Main outcome measure: Death or disablement 4 months after the index stroke. Disablement was defined as a score of 3 or higher on the Rankin Scale.
Results: Age and CNS score defined six risk groups with a predicted 4-month poor outcome rate ranging from 10% (patients aged 70 years or younger and with an initial CNS score of 7 or higher) to 89% (patients older than 70 years and with a CNS score of 4.5 or lower). When a risk of poor outcome of 60% was taken as a cutoff, the accuracy of the prediction was 78% +/- 6% in the training set and 72% +/- 9% in the test set.
Conclusion: Long-term outcome can be predicted in the first few hours following an acute ischemic stroke by means of a simple model based on age and CNS score.