Analysis of Outcomes of Critically ill Surgical Patients using SAPS II Score - Paudel, Prakash; Rai, Subash; Shrestha, Sunil; Pradhan, Giridhar B N; Bhattachan, Chitra L (Journal of Institute of Medicine Nepal, 2019)
Introduction: Several prognostic models have been implemented for risk assessment and mortality prediction in critically ill patients admitted in ICU. The availability of such sophisticated methods has facilitated in clinical decision making and comparison of outcomes. However, none are universally accepted as standard method to predict mortality. We have decided to use SAPS II score because of the simplicity and easy availability of its variables to analyse the outcomes of critically ill surgical patients admitted to ICU at our centre. Methods: The study was conducted between September 2016 and August 2018 at Nepal Medical College and Teaching Hospital, Kathmandu, Nepal. We prospectively collected data on surgical patients consecutively admitted to the ICU during the study period. The variables of SAPS II score were collected from the physiological, laboratory, and patient characteristics mentioned in the ICU scoring data sheet at 24 hours. The SAPS II score and predicted mortality was calculated using computer software programme. The predictive mortality based on the score was compared with the actual outcome to derive the standardized mortality ratio (SMR). Results: During the period of study, 64 patients met the inclusion criteria. The mean age of the patients was 54±17.9 (20- 84) years and length of ICU stay was 5.3 ±3.5 (3-22) days. GI malignancy was most common pathology comprising 43.8% (n=28). The mean SAPS II score was 24.9±16.4 (3-68). There was no statistical difference in mean SAPS II score between patients with different gender, nature of disease and type of surgical intervention The mean predicted mortality was 13.4% and the observed ICU mortality was 15.6% (n=10). The calculated mean SAPS II score and predicted mortality was higher in non-survivors compared to survivors (p<0.0001). The calculated SMR for our study population was 0.85 ranging from 0.01 to 5.2. The number of patients with SMR greater than 1 was only 17 % (11/64). There was significant correlation of mortality with SMR greater than 1 (p=<0.0001). Conclusion: The variables in SAPS II score are readily available. Neither special samples nor cumbersome procedures are required. SAPS II can be used as simple and rapid tool to predict mortality in critically ill surgical patients in our set up.