Development of a prediction model for 1-year poor prognosis in patients with acute ischemic stroke

Abstract

The goals of this study were to develop a new prediction model to predict 1-year poor prognosis (death or modified Rankin scale score of ≥3) in patients with acute ischemic stroke (AIS) and to compare the performance of the new prediction model with other prediction scales. Baseline data of 772 patients with AIS were collected, and univariate and multivariate logistic regression analyses were performed to identify independent risk factors for 1-year poor prognosis in patients with AIS. The area under the receiver operating characteristics curve (AUC) value of the new prediction model and the THRIVE, iScore and ASTRAL scores was compared. The Hosmer-Lemeshow test was used to assess the goodness of fit of the model. We identified 196 (25.4%) patients with poor prognosis at 1-year follow-up, and of these 68 (68/196, 34.7%) had died. Multivariate logistic regression and receiver operating characteristic curve analyses showed that age ≥70 years, consciousness (lethargy or coma), history of stroke or transient ischemic attack, cancer, abnormal fasting blood glucose levels ≥7.0 mmol/L, and National Institutes of Health Stroke Scale score were independent risk factors for 1-year poor prognosis in patients with AIS. Scores were assigned for each variable by rounding off β coefficient to the integer score, and a new prediction model with a maximum total score of 9 points was developed. The AUC value of the new prediction model was higher than the THRIVE score (p<0.05). The χ² value for the Hosmer-Lemeshow test was 7.337 (p>0.05), suggesting that the prediction model had a good fit. The new prediction model can accurately predict 1-year poor prognosis in Chinese patients with AIS.