Comparison of illness severity scoring systems for mortality prediction in Neurointensive Care Unit in India

Abstract

Background: Illness severity scoring systems (SSs) are increasingly being used to provide information about patients’ severity of illness and outcome in terms of mortality or length of Intensive care Unit (ICU) and hospital stay. In this retrospective study, we compared the predictive power of Acute Physiology and Chronic Health Evaluation (APACHE) II and IV, Simplified Acute Physiology Score (SAPS), Mortality Prediction Model at 24 h and Glasgow Coma Scale (GCS) with actual in-hospital 28 day mortality in patients admitted to neuro-ICU over a period of 6 months. Methods: The data required for calculation of above scores was retrieved from medical records. The 28-day post-admission outcome including in-hospital mortality was measured by Glasgow Outcome Scale (GOS). Logistic regression was used to determine the mortality prediction power of each SS. Results: A total of 197 adult patients with varied neurological diagnosis were included in this study. The in-hospital 28-day mortality rate was 19.8%, and the scores of all the SSs correlated significantly with GOS (P < 0.001). All the scores were significantly different between survivors and non-survivors. The accuracy of all the SSs to predict survival and non-survival was more than 80%. The highest accuracy rate was seen for GCS and SAPS (84.3% and 83.8%, respectively). Conclusions: The SSs used in this study had good predictive power, and they had good discriminative ability between survivors and non-survivors. GCS and SAPS have the highest predictive ability, GCS having added advantage of being simple and practical.