451. PREDICTIVE FACTORS FOR PNEUMONIA AND ANASTOMOTIC LEAK AFTER TRANSTHORACIC ESOPHAGECTOMY FOR CANCER AND FAILURE TO RESCUE ANALYSIS ON 1355 PATIENTS

Abstract

Abstract Background Pneumonia (PN) and anastomotic leak (AL) represent the most feared complications after transthoracic esophagectomy for cancer, the former more commonly observed after open and the latter after minimally-invasive (MI) procedures. Studies comparing these two complications with focus on predictive risk factors and procedure-related failure-to-rescue (FTR) are sparse. Aim of the study was to explore such aspects with a large multicentric dataset. Methods All patients who underwent an Ivor Lewis transthoracic esophagectomy for cancer between 2008 and 2022 in four tertiary centers were queried. Predictive risk factors for pneumonia, anastomotic leak and in-hospital mortality were analyzed with univariable models. FTR was defined as in-hospital death following a major complication. Patients were then classified and compared according to the type of operation [open, hybrid-laparoscopic, hybrid-robotic, standard minimally-invasive (MIE) or robotic minimally-invasive (RAMIE)]. Pneumonia and anastomotic leak associated FTR was calculated and compared across the groups. Machine-learning models (neuronal nets, support vector machines and random forests classifier) were applied to predict complications and FTR. Results In total, 1,355 patients were included. Significant (p<0.05) predictors for PN (n=211, 15.6%) were ASA=4, preexisting cardiac and pulmonary conditions, conversion (thoracotomy), neoadjuvant therapy and age. Those for AL (n=160, 11.8%) were preexisting cardiac condition, conversion (thoracotomy) and operation time. Overall FTR-rate was 3.6%. Age>65y, preexisting cardiac and pulmonary condition, AL, PN, postoperative bleeding, sepsis, pulmonary embolism, myocardial infarction, arrhythmia and need for blood transfusion were the risk factors significantly associated with in-hospital mortality. PN- and AL- associated FTR rates did not significantly differ among the different operation types (Figure 1). Machine-learning models were unable to predict complications or FTR properly. Conclusions Our study showed that there is a greater number of factors associated with pneumonia rather than anastomotic leak, probably making the prevention of this complication more challenging to achieve. However, pneumonia- and leak-associated FTR-rates did not significantly differ among the groups, demonstrating that the implementation of minimally-invasive procedures can be safely carried out, if experience is provided.