Comparison of PRISM III and PIM II Score in Predicting Mortality in Paediatric Intensive Care Unit: An Observational Study

Introduction: Prognostic scores play a vital role in predicting the outcome of children admitted in Paediatric Intensive Care Unit (PICU) thereby reducing the mortality. For paediatric population, Paediatric Risk of Mortality (PRISM III) and Paediatric Index of Mortality (PIM II) are the principal scores. As limited PICU beds are available in many tertiary care centres, PRISM III score helps in predicting mortality risk and admission to PICU.

Aim: To compare PRISM III and PIM II in predicting the mortality in sick children in a PICU and their relation between observed and predicted mortality.

Materials and Methods: This was a prospective observational study, conducted in Chengalpattu Medical College Hospital, Chennai, Tamil Nadu, India, from July 2018 to June 2019 that enrolled 102 children who were admitted to PICU. At first hour of admission, PIM II score was assessed and at 24 hours of admission, PRISM III score was assessed and the mortality was predicted. Children were followed-up until discharge or death, and the predicted mortality was compared with actual mortality and validation of scores was done using Statistical Package for the Social Sciences (SPSS) version 16.0.

Results: Mean age of the population was 37.6 months, and majority of the children were aged less than 12 months. Male children were predominant (52%). Major system involvement was respiratory system 38 (37.3%) and mortality was 18 (17.6%). The mean score for death in PRISM III and PIM II were 11.8 and 19.9, respectively. The mean score for survival in PRISM III and PIM II were 4.4 and 9, respectively. Total PRISM III and PIM II score was lower in children who survived and mortality has been observed with higher scores. On comparison, PRISM III score was better to predict the mortality than PIM II. The Area Under Curve (AUC) and sensitivity for PRISM III score were 0.881 with 95% CI (0.769 to 0.992) and 94.44% respectively versus the AUC and sensitivity for PIM II score were 0.768 with CI (0.628 to 0.908) and 61.11%, respectively. Using logistic regression, risk of mortality was analysed and found that increase in one score has 0.62 times the increased risk of death in PRISM III score and thus, it predicts the mortality better.

Conclusion: The PRISM III score was better than PIM II score for risk stratification and to optimise available limited resources. Both scores underestimate the predicted mortality in comparison to observed mortality.