Nomographic predictive models for complications after minimally invasive esophagectomy: Current status and future perspectives

Perioperative morbidity of esophagectomy significantly affects the surgical outcome, like any major gastrointestinal procedure. Despite introduction of minimally invasive esophagectomy, the morbidity is still close to 30%-40%. The common complications following esophagectomy are pulmonary infections, cardiac events, anastomotic leakage, bleeding, chylous leak, and recurrent laryngeal nerve palsy which in turn lead to longer hospital stay, increased treatment cost and poor quality of life. A nomographic model comprising preoperative (patient, disease and treatment related) and intraoperative factors in combination with Artificial Intelligence may accurately identify the patients at higher risk of morbidity. This will aid in optimizing the modifiable risk factors preoperatively, and closely monitor these patients post operatively for early identification of complications and to initiate early corrective measures to improve the surgical outcome.