Predictive Power of the

Abstract

Background: In spite of the global implementation of standardized surgical safety checklists and evidence-based practices, general surgery remains associated with a high residual risk of preventable perioperative complications and adverse events. This study was designed to validate the hypothesis that a new "Trigger Tool" represents a sensitive predictor of adverse events in general surgery. Methods: An observational multicenter validation study was performed among 31 hospitals in Spain. The previously described "Trigger Tool" based on 40 specific triggers was applied to validate the predictive power of predicting adverse events in the perioperative care of surgical patients. A prediction model was used by means of a binary logistic regression analysis. Results: The prevalence of adverse events among a total of 1,132 surgical cases included in this study was 31.53%. The "Trigger Tool" had a sensitivity and specificity of 86.27% and 79.55% respectively for predicting these adverse events. A total of 12 selected triggers of overall 40 triggers were identified for optimizing the predictive power of the "Trigger Tool". Conclusions: The "Trigger Tool" has a high predictive capacity for predicting adverse events in surgical procedures. We recommend a revision of the original 40 triggers to 12 selected triggers to optimize the predictive power of this tool, which will have to be validated in future studies.