Population-based validation of the iScore for predicting mortality and early functional outcome in ischemic stroke patients

Background: We aimed to determine the accuracy of the iScore for predicting mortality and early disability following ischemic stroke in a French population-based study.

Methods: All patients with acute ischemic stroke were identified among residents of the city of Dijon, France, between 2006 and 2011, using a population-based stroke registry. The 30-day iScore and 1-year iScore were calculated. A logistic regression model was used to assess the performance of the iScore for predicting both 30-day and 1-year mortality, and poor functional outcome at discharge (modified Rankin Scale score of 3-6). The discrimination and calibration of the model were assessed using the c-statistic and the Hosmer-Lemeshow goodness-of-fit test, respectively.

Results: Among the 1,199 ischemic stroke patients recorded, 107 (8.9%) were excluded because at least one item of data was missing. For the remaining 1,092 patients, the c-statistic was 0.85 (95% CI: 0.82-0.89) for 30-day and 0.84 (0.81-0.87) for 1-year mortality, and calibration was good (p = 0.82 and p = 0.96, respectively, for the Hosmer-Lemeshow test). Similar results were found for disability (c-statistic 0.81, 95% CI: 0.79-0.84, and p = 0.45 for the Hosmer-Lemeshow test).

Conclusion: This is the first population-based study to demonstrate the accuracy of the iScore for predicting mortality and early disability in ischemic stroke patients.