Assessing the risk: Scoring systems for outcome prediction in emergency laparotomies.

Emergency laparotomy is the commonest emergency surgical procedure in most hospitals and includes over 400 diverse surgical procedures. Despite the evolution of medicine and surgical practices, the mortality in patients needing emergency laparotomy remains abnormally high. Although surgical risk assessment first started with the ASA Physical Status score in 1941, efforts to find an ideal scoring system that accurately estimates the risk of mortality, continues till today. While many scoring systems have been developed, no single scoring system has been validated across multiple centers and geographical locations. While some scoring systems can predict the risk merely based upon preoperative findings and parameters, some rely on intra-operative assessment and histopathology reports to accurately stratify the risk of mortality. Although most scoring systems can potentially be used to compare risk-adjusted mortality across hospitals and amongst surgeons, only those which are based on preoperative findings can be used for risk prognostication and identify high-risk patients before surgery for an aggressive treatment. The recognition of the fact, that in the absence of outcome data in these patients, it would be impossible to evaluate the impact of quality improvement initiatives on risk-adjusted mortality, hospital groups and surgical societies have got together and started to pool data and analyze it. Appropriate scoring systems for emergency laparotomies would help in risk prognostication, risk-adjusted audit and assess the impact of quality improvement initiative in patient care across hospitals. Large multi-centric studies across varied geographic locations and surgical practices need to assess and validate the ideal and most apt scoring system for emergency laparotomies. While APACHE-II and P-POSSUM continue to be the most commonly used scoring system in emergency laparotomies,studies need to compare them in their ability to predict mortality and explore if either has a higher sensitivity and specificity than the other.