OBJECTIVES: To assess whether intraperitoneal contamination index (ICI) (Hajibandeh index) derived from combined levels of CRP, lactate, neutrophils, lymphocytes, and albumin can predict the nature of intraperitoneal contamination in patients with acute abdominal pathology and to assess whether ICI can predict postoperative mortality in patients undergoing emergency laparotomy. METHODS: In order to prospectively validate the ICI, developed and validated retrospectively in our previous study, a multicentre prospective cohort study was conducted between January 2019 and June 2020 including all adult patients who presented with acute abdominal pathology requiring emergency laparotomy. ROC curve analysis was performed to determine discrimination and cut-off values of preoperative ICI that could predict the nature of intraperitoneal contamination and postoperative mortality. RESULTS: Overall, 269 patients were included in the prospective validation cohort which were compared with 234 patients in the primary cohort and 234 patients in the retrospective validation cohort. The analyses identified ICI of 24.76 as cut-off value for purulent contamination (AUC: 0.78, P < 0.0001; sensitivity: 82.4%, specificity: 60.9%); ICI of 33.84 as cut-off value for feculent contamination (AUC: 0.78, P < 0.0001; sensitivity: 82%, specificity: 67.8%), and ICI of 33.47 as cut-off value for postoperative mortality (AUC: 0.70, P < 0.0001; sensitivity: 72.7%, specificity: 58.47%). The results of the prospective validation cohort were comparable with the results of the primary and retrospective validation cohorts. CONCLUSIONS: Hajibandeh index predicts the presence of purulent and feculent intraperitoneal contamination in patients with acute abdominal pathology and postoperative mortality in patients undergoing emergency laparotomy. Future studies should investigate the effect of ICI use on the accuracy of preoperative prognostic scoring tools and on patient selection for operative or non-operative management of underlying abdominal pathology.
OBJECTIVES: To assess whether intraperitoneal contamination index (ICI) (Hajibandeh index) derived from combined levels of CRP, lactate, neutrophils, lymphocytes, and albumin can predict the nature of intraperitoneal contamination in patients with acute abdominal pathology and to assess whether ICI can predict postoperative mortality in patients undergoing emergency laparotomy. METHODS: In order to prospectively validate the ICI, developed and validated retrospectively in our previous study, a multicentre prospective cohort study was conducted between January 2019 and June 2020 including all adult patients who presented with acute abdominal pathology requiring emergency laparotomy. ROC curve analysis was performed to determine discrimination and cut-off values of preoperative ICI that could predict the nature of intraperitoneal contamination and postoperative mortality. RESULTS: Overall, 269 patients were included in the prospective validation cohort which were compared with 234 patients in the primary cohort and 234 patients in the retrospective validation cohort. The analyses identified ICI of 24.76 as cut-off value for purulent contamination (AUC: 0.78, P < 0.0001; sensitivity: 82.4%, specificity: 60.9%); ICI of 33.84 as cut-off value for feculent contamination (AUC: 0.78, P < 0.0001; sensitivity: 82%, specificity: 67.8%), and ICI of 33.47 as cut-off value for postoperative mortality (AUC: 0.70, P < 0.0001; sensitivity: 72.7%, specificity: 58.47%). The results of the prospective validation cohort were comparable with the results of the primary and retrospective validation cohorts. CONCLUSIONS: Hajibandeh index predicts the presence of purulent and feculent intraperitoneal contamination in patients with acute abdominal pathology and postoperative mortality in patients undergoing emergency laparotomy. Future studies should investigate the effect of ICI use on the accuracy of preoperative prognostic scoring tools and on patient selection for operative or non-operative management of underlying abdominal pathology.