Efficacy of the P-POSSUM scoring system in prediction of post-operative mortality and morbidity in patients undergoing emergency exploratory laparotomy in a tertiary institute in East India

Abstract

Background: The tenet of any surgery is to reduce the morbidity and mortality. The outcome is not solely dependent on surgeon’s operative expertise alone, but also significantly influencedby a lot of patient factors. The Physiological and Operative Severity Score for the enUmeration of Morbidity and Mortality (POSSUM), a risk-adjusted scoring system, has already been used in various parts of India. There is scarcity of published research using this tool in the population of Eastern India. Aims and Objectives: The aim of the study was to determine the efficacy of modified version Portsmouth-POSSUM (P-POSSUM) scoring system in predicting the postoperative morbidity and mortality in population of East India. Materials and Methods: The study was carried out in 50 patients of either gender, of age group 13–80 years, undergoing emergency laparotomy and followed up to 30-day post-operative follow-up of all patients till the sample size of 50 was reached. The physiological scores were recorded during admission and the operative severity score was recorded according to the intra-operative findings of operating surgeon. Any post-operative morbidity or death was recorded during hospital stay or on follow-up for a period of 30 days. The Hosmer–Lemeshow test was used for goodness-of-fit in logistics regression for mortality risk prediction model. The ratio of observed and expected rates (O: E ratio) was calculated. Results: Using the scoring tool, no significant difference was observed between the expected and observed mortality (Chi-square 2.166; df=8; P=0.976, O: E ratio 1.4) but a considerable difference was observed between the observed between the expected morbidity rates (χ²=22.806, df=8, P=0.004, O: E ratio 1.137). Conclusion: The P-POSSUM score was able to accurately predict the mortality in Eastern India surgical settings. However, the model was not that accurate in prediction of morbidity.