Endoluminal Vacuum Therapy for the Management of Boerhaave Syndrome: A Case Series.

Introduction: Boerhaave syndrome is a rare condition associated with high morbidity and mortality. Prompt intervention greatly improves outcomes, with surgery traditionally being the mainstay of management. Recent advances in therapeutic endoscopy have led to increasing interest in endoluminal vacuum therapy (EVT), a minimally invasive technique, allowing wound debridement and drainage, encouraging granulation tissue formation. EVT has been associated with positive clinical outcomes, including lower mortality rates compared to surgery and stenting for the management of anastomotic leaks, and to a lesser extent, oesophageal perforations. EVT has been adopted into practice across Europe; however, only few cases have been reported from the UK. Case Presentations: We report three cases of Boerhaave syndrome, successfully managed with EVT, using the Eso-SPONGE ® (B.Braun Medical Ltd, Sheffield, UK). EVT involves the placement of a polyurethane sponge into the wound cavity. The cavity is initially assessed, then an overtube is introduced through which the sponge is inserted, and then the overtube is removed. Sponge position is confirmed and adjusted if necessary. The sponge is connected via a trans-nasal drain to continuous negative pressure suction and is changed every 3-5 days. Having been deemed surgically unfit, all 3 patients were referred for EVT. All patients made excellent recovery and were discharged home. Conclusion: EVT is an effective management strategy for surgically unfit Boerhaave syndrome patients. Eso-SPONGE use aided drainage of the septic focus and closure of the defect, leading to complete recovery. Our findings support the existing evidence that EVT is a promising solution for Boerhaave syndrome.

Evaluating risk stratification scoring systems to predict mortality in patients with COVID-19.

BACKGROUND: The COVID-19 pandemic has necessitated efficient and accurate triaging of patients for more effective allocation of resources and treatment. OBJECTIVES: The objectives are to investigate parameters and risk stratification tools that can be applied to predict mortality within 90 days of hospital admission in patients with COVID-19. METHODS: A literature search of original studies assessing systems and parameters predicting mortality of patients with COVID-19 was conducted using MEDLINE and EMBASE. RESULTS: 589 titles were screened, and 76 studies were found investigating the prognostic ability of 16 existing scoring systems (area under the receiving operator curve (AUROC) range: 0.550-0.966), 38 newly developed COVID-19-specific prognostic systems (AUROC range: 0.6400-0.9940), 15 artificial intelligence (AI) models (AUROC range: 0.840-0.955) and 16 studies on novel blood parameters and imaging. DISCUSSION: Current scoring systems generally underestimate mortality, with the highest AUROC values found for APACHE II and the lowest for SMART-COP. Systems featuring heavier weighting on respiratory parameters were more predictive than those assessing other systems. Cardiac biomarkers and CT chest scans were the most commonly studied novel parameters and were independently associated with mortality, suggesting potential for implementation into model development. All types of AI modelling systems showed high abilities to predict mortality, although none had notably higher AUROC values than COVID-19-specific prediction models. All models were found to have bias, including lack of prospective studies, small sample sizes, single-centre data collection and lack of external validation. CONCLUSION: The single parameters established within this review would be useful to look at in future prognostic models in terms of the predictive capacity their combined effect may harness.