TH6.12 Predicting Mortality and Morbidity in Oesophageal perforation: A Review of Current Tools. (9th August 2022)

• Record Type: Journal Article
• Authors: Alasmar, Mohamed; Shehata, Zak; Altarawni, Mohammad; Casey, Patrick; Melhado, Rachel; Sultan, Javed
• Is Part Of: British journal of surgery. Volume 109(2022)Supplement 5
• Publication Date: 2022-08-09
• Subjects: Surgery -- Periodicals; 617.005
• DOI: 10.1093/bjs/znac248.252
• Languages: English
• ISSNs: 0007-1323

Abstract

Abstract: Aim: Oesophageal perforation is a challenging condition associated with high mortality and morbidity. There is a lack of consensus regarding the optimal treatment strategy, when and whom to operate on. The aim of this study is to identify the optimal morbidity and mortality risk prediction tool for patients with oesophageal perforation. Methods: We compared and validated commonly used risk prediction models, including the Pittsburgh Severity Score (PSS), the National Emergency Laparotomy Audit score (NELA score), the Portsmouth Physiological and Operative Severity Score for the enumeration of Mortality (P-POSSUM), and the Surgical Outcome Risk Tool (SORT) using a dataset of 83 patients ranging from 2009 to 2021. The ability to predict morbidity was assessed using the comprehensive complication index (CCI). The CCI was calculated for both operative and non-operative cohorts. Results: Of the scores assessed, NELA showed the most robust predictive value for in-hospital mortality, 30-day mortality, and 90 mortality (AUROC 0.812, 0.8602, 0.8302, respectively). The PSS also showed significant predictive value for in-hospital mortality, 30-day mortality, and 90 mortality (AUROC 0.792, 0.856, 0.813 respectively). Furthermore, NELA had the strongest correlation between score and CCI (rs 0.644 p<0.001). Conclusion: Despite not being validated for oesophageal pathology, NELA appears to be the optimum scoring model to predict mortality and morbidity for this patient population. This is the first study to compare the efficacy of different risk prediction models in oesophageal perforations and could be used to inform shared decision making and peri-operative outcomes. Further large-scale validation of risk prediction tools is required to corroborate these findings.