Published online Aug 26, 2019. doi: 10.12998/wjcc.v7.i16.2227
Peer-review started: February 24, 2019
First decision: June 21, 2019
Revised: June 28, 2019
Accepted: July 20, 2019
Article in press: July 20, 2019
Published online: August 26, 2019
Various scoring systems have been used historically to predict outcomes in patients who are at increased risk of morbidity and mortality during their hospital stay. Emergency laparotomy, despite being one of the commonest surgical procedures, continued to have reasonably high postoperative mortality. Doctors are legally bound to discuss with their patients and relatives the potential risk of complications and adverse outcomes. A robust scoring system enables us to quantify the risk and serves as a tool to measure risk-based outcomes and enable audit of clinical results and impact of improvement initiatives.
Portsmouth modification of Physiological and operative severity for the enumeration of mortality and morbidity (P-POSSUM) and the acute physiology and chronic health evaluation II (APACHE-II) have been the most widely used scoring systems for emergency laparotomies. P-POSSUM remains the tool of choice in the United Kingdom. However, it is subject to observational bias while quantifying intraoperative blood loss and peritoneal contamination. It is always better that we have a single scoring system to predict outcomes and audit healthcare organizations. Besides, delay in histopathology reports would delay the P-POSSUM score of the patient, and patients managed conservatively or refused surgery could not be scored. In these circumstances, the APACHE-II score had the advantage of being available in the pre-operative period itself. However, to date no study with statistically significant sample size has compared P-POSSUM and APACHE-II in their ability to predict mortality in emergency laparotomies. This study aims to bridge this gap and assess if APACHE-II can be used as a single scoring system to predict outcomes and for audit of outcomes across healthcare organizations.
The study was conducted to compare the predictability of APACHE-II and P-POSSUM scoring systems on postoperative mortality and to see any correlation between these scoring systems and length of stay, requirement of postoperative ventilatory support, inotropic support, development of acute kidney injury (AKI), cardiac morbidity, and need for re-exploration. While the study showed that both APACHE-II and P-POSSUM can equally predict mortality, it also demonstrated comparability in predicting increased length of stay and need for postoperative ventilatory support, higher incidence of AKI, and increased risk of cardiac morbidity. However, P-POSSUM was a better predictor of the need for re-exploration as compared to APACHE-II. The study was successful in demonstrating that both APACHE-II and P-POSSUM can be interchangeably used not only for postoperative mortality but also for effectively predicting morbidity. With the advantage that the APACHE-II scoring can be done preoperatively, the study justifies the fact that APACHE-II can be the single scoring system to predict outcomes and audit healthcare organizations for emergency laparotomies.
All patients undergoing emergency laparotomy at Tata Main Hospital (Jamshedpur, India) form December 2013 to November 2014 were included in the study. All patients were scored with APACHE-II and P-POSSUM scoring systems. Receiver operating characteristics curve (ROC) was used as a statistical method to measure the diagnostic accuracy. Area under the curve (AUC) was used to measure the “size” of the prediction, and it consisted of graphically plotting “sensitivity” and the “1–specificity” relationship. The ROC curve was used to display the optimal cut-off point when sensitivity and specificity reached an optimum for both values, by which the point on the ROC curved line was closest to the upper left corner on the curve.
Out of a total of 159 patients who met the inclusion criteria, only 157 could be included in the study. For APACHE-II, the cut off value was found to be 24 for predicting mortality by ROC analysis. In comparison, for P-POSSUM, the cut off value was found to be 63 to predict mortality using ROC analysis. Multivariate logistic regression model was used to identify independent risk factors for mortality. A ROC, the graphic display between the “sensitivity” and the “1–specificity” relationship to measure diagnostic accuracy of the true positives versus the false positives for APACHE-II and P-POSSUM, depicted that AUC was 0.965 (using a cut-off value of 24) for APACHE-II and 0.989 (using a cut-off value 63) for P-POSSUM. Both the scores were significantly good in predicting postoperative mortality in patients undergoing emergency laparotomy and on comparing the sensitivity and specificity of APACHE-II and P-POSSUM, there appears to be no statistically significant difference between their ability to predict postoperative mortality. Except for APACHE-II's inability to predict re-exploration, both can predict all the secondary outcomes in a statistically significant manner.
This is possibly the first adequately powered study with alpha value (0.05) and a beta value (0.2) and statistically significant sample size that has compared P-POSSUM and APACHE-II in predicting mortality in emergency laparotomies. P-POSSUM above 63 and APACHE-II above 24 not only indicates higher risk, it also increases the risk of postoperative morbidity. However, APACHE-II, being a physiologic score, was a poor indicator of the need for a re-exploration after laparotomy. P-POSSUM is a significantly better predictor of the possibility of re-exploration. While P-POSSUM continues to be the most commonly used scoring system for audit purposes, risk-based outcome comparisons across hospitals and impact of quality improvement initiatives using APACHE-II would ensure that a single scoring system can be used not only for individual patient’s risk assessment and prognostication but also used interchangeably with P-POSSUM for audit purposes as well.
This study demonstrates that compared to the more widely used P-POSSUM, which needs 18 data points, APACHE-II needs only 12 data points, is easily available for risk assessment in the preoperative period, and does not need subjective assessments (intraoperative blood loss or peritoneal contamination) or wait for histopathology reports. While this study was an adequately powered single center study, future research should focus on multi-center trials to strengthen the findings of our study.